//TELEGRAM ==> https://t.

me/eyops
//@version=5

//text inputs
textVPosition = 'middle'
textHPosition = 'center'
symVPosition = 'top'
symHPosition = 'left'
width = 0
height = 0
c_title = #b2b5be80
s_title = 'large'
a_title = 'center'
c_subtitle = #b2b5be80
s_subtitle = 'normal'
a_subtitle = 'center'
c_bg = color.new(color.blue, 100)

indicator("Lux Algo Signals & Overlays [6.3]", "Lux Algo Signals & Overlays [6.3]",
overlay = true, max_labels_count = 500)

//Import libraries
import ayvaliktrading/EyopsTelegram/1 as LAF
import ayvaliktrading/JoinUsEyopsTelegram/1 as kernels

// # ============================[GET USERS INPUT]============================ #

groupBasic = "BASIC SETTINGS"
showSignals = input(true, "Show Signals", inline = "1", group = groupBasic, tooltip
= "Enables or disables the signals")
signalPresets = input.string("None", "Presets / Filters", ["None", "Trend Trader
[Preset]","Scalper [Preset]", "Swing Trader [Preset]", "Contrarian Trader
[Preset]", "Smart Trail [Filter]", "Trend Tracer [Filter]", "Trend Strength
[Filter]", "Trend Catcher [Filter]", "Neo Cloud [Filter]"],tooltip = "Automatically
sets settings or filters for a given category", group= groupBasic)
signalMode = input.string("Confirmation + Exits", "Signal Mode", ["Confirmation +
Exits", "Contrarian + Exits", "None"],tooltip = "Changes the Mode of the
signals" ,group = groupBasic)
signalClassifier = input(true,"AI Signal Classifer",tooltip = "Shows signal quality
from 1-4 on signals" ,group = groupBasic)
sensitivity = input.float(5, "Signal Sensitivity ", minval = 1, maxval =
26,step=0.1, tooltip = "Changes the sensetivity of the signals, the lower this
setting the more short term signals you will get, while a higher number will result
in longer term signals.",group = groupBasic)
atrLength = input.int(10, "Signal Tuner ", minval = 1, maxval = 25,step=1,tooltip
= "Alows you to tune your signals, the higher the number the more refined but
laggier the signal" ,group = groupBasic)
candleColorType = input.string("Confirmation Simple", "Candle Coloring",
["Confirmation Simple","Confirmation Gradient","Contrarian
Gradient","None"],tooltip = "Changes the type of signal coloring", group =
groupBasic)

// Indicator Overlay Settings

groupOverlay = "INDICATOR OVERLAY"
smartTrail = input(true, "Smart Trail", inline = "1", group = groupOverlay)
trendCatcher = input(false, "Trend Catcher", inline = "2", group = groupOverlay)
neoCloud = input(false, "Neo Cloud", inline = "3", group = groupOverlay)
reversalZone = input(true, "Reversal Zones", inline = "1", group = groupOverlay)
trendTracer = input(false, "Trend Tracer", inline = "2", group = groupOverlay)
showDashboard = input(true, "Dashboard", inline = "3", group = groupOverlay)
showTrailingStoploss = input(false, "Trailing Stoploss", inline = "4", group =
groupOverlay)
showMovingAverage = input(false, "AI Moving Average", inline = "4", group =
groupOverlay)
showSessions = input(false, "Sessions", inline = "5", group = groupOverlay)

// Advanced Settings
groupAdvanced = "ADVANCED SETTINGS"
takeProfitBoxes = input.string("Off", "TP/SL Points", options=["Off","On"], inline
= "2", tooltip = "Shows Take Profit and Stop Loss areas",group = groupAdvanced)
takeProfitStopLossDistance = input.int(5,"", minval = 1, maxval = 10, inline = "2",
group=groupAdvanced)
autopilotMode = input.string("Off", "Autopilot Sensivity",["Off","Short-Term",
"Mid-Term", "Long-Term"],tooltip = "Sets automatic settings for signals and
improves their quality" ,inline = "3", group = groupAdvanced)
dashboardLocation = input.string("Bottom Right","Dashboard Location", ["Top
Right","Bottom Right","Bottom Left"], inline = "4",tooltip = "Changes dashboard
positions" ,group = groupAdvanced)
dashboardSize = input.string("Normal","Dashboard Size",
["Tiny","Small","Normal","Large"], inline = "5",tooltip = "Changes the size of the
dashboard" ,group = groupAdvanced)

if (signalPresets == "Trend Trader [Preset]")

smartTrail := true
trendCatcher := true
neoCloud := true
trendTracer := true
smartTrail := true
if (signalPresets == "Scalper [Preset]")
sensitivity := 4
smartTrail := true
trendTracer := true
candleColorType := "Confirmation Gradient"
if (signalPresets == "Swing Trader [Preset]")
sensitivity := 18
neoCloud := true
candleColorType := "Confirmation Simple"
if (signalPresets == "Contrarian Trader [Preset]")
reversalZone := true
smartTrail := true
candleColorType := "Contrarian Gradient"

n = bar_index

// # ============================[BUY/SELL SIGNALS]============================ #
//------------------------------------------------------------------------------
//Settings
//-----------------------------------------------------------------------------{
//-----------------------------------------------------------------------------}

// # ============================[SESSIONS]============================ #
show_sesa = true
sesa_txt = 'New York'
sesa_ses = '1300-2200'
sesa_css = #ff5d00
sesa_range = true
sesa_tl = false
sesa_avg = false
sesa_vwap = false
sesa_maxmin = false

//Session B
show_sesb = true
sesb_txt = 'London'
sesb_ses = '0700-1600'
sesb_css = #2157f3

sesb_range = true
sesb_tl = false
sesb_avg = false
sesb_vwap = false
sesb_maxmin = false

//Timezones
tz_incr = 0
use_exchange = false

//Ranges Options
bg_transp = 90
show_outline = true
show_txt = true

//Dashboard
show_ses_div = false
show_day_div = false

//-----------------------------------------------------------------------------}
//Functions
//-----------------------------------------------------------------------------{

//Get session average

get_avg(session)=>
var len = 1
var float csma = na
var float sma = na

if session > session[1]

len := 1
csma := close

if session and session == session[1] and textVPosition == 'middle' and

textHPosition == 'center' and c_title == #b2b5be80 and s_title == 'large' and
a_title == 'center' and c_subtitle == #b2b5be80 and s_subtitle == 'normal' and
a_subtitle == 'center'
len += 1
csma += close
sma := csma / len

sma

//Get trendline coordinates

get_linreg(session)=>
var len = 1
var float cwma = na
var float csma = na
var float csma2 = na

var float y1 = na
var float y2 = na
var float stdev = na
var float r2 = na

if session > session[1]

len := 1
cwma := close
csma := close
csma2 := close * close

if session and session == session[1] and textVPosition == 'middle' and

textHPosition == 'center' and c_title == #b2b5be80 and s_title == 'large' and
a_title == 'center' and c_subtitle == #b2b5be80 and s_subtitle == 'normal' and
a_subtitle == 'center'
len += 1
csma += close
csma2 += close * close
cwma += close * len

sma = csma / len

wma = cwma / (len * (len + 1) / 2)

cov = (wma - sma) * (len+1)/2

stdev := math.sqrt(csma2 / len - sma * sma)
r2 := cov / (stdev * (math.sqrt(len*len - 1) / (2 * math.sqrt(3))))

y1 := 4 * sma - 3 * wma
y2 := 3 * wma - 2 * sma

[y1 , y2, stdev, r2]

//Session Vwap
get_vwap(session) =>
var float num = na
var float den = na

if session > session[1] and textVPosition == 'middle' and textHPosition ==

'center' and c_title == #b2b5be80 and s_title == 'large' and a_title == 'center'
and c_subtitle == #b2b5be80 and s_subtitle == 'normal' and a_subtitle == 'center'
num := close * volume
den := volume

else if session and session == session[1] and textVPosition == 'middle' and

textHPosition == 'center' and c_title == #b2b5be80 and s_title == 'large' and
a_title == 'center' and c_subtitle == #b2b5be80 and s_subtitle == 'normal' and
a_subtitle == 'center'
num += close * volume
den += volume
else
num := na

[num, den]
//Set line
set_line(session, y1, y2, session_css)=>
var line tl = na

if session > session[1] and textVPosition == 'middle' and textHPosition ==

'center' and c_title == #b2b5be80 and s_title == 'large' and a_title == 'center'
and c_subtitle == #b2b5be80 and s_subtitle == 'normal' and a_subtitle == 'center'
tl := line.new(n, close, n, close, color = session_css)

if session and session == session[1] and textVPosition == 'middle' and

textHPosition == 'center' and c_title == #b2b5be80 and s_title == 'large' and
a_title == 'center' and c_subtitle == #b2b5be80 and s_subtitle == 'normal' and
a_subtitle == 'center'
line.set_y1(tl, y1)
line.set_xy2(tl, n, y2)

//Set session range

get_range(session, session_name, session_css)=>
var t = 0
var max = high
var min = low
var box bx = na
var label lbl = na

if session > session[1] and showSessions and textVPosition == 'middle' and

textHPosition == 'center' and c_title == #b2b5be80 and s_title == 'large' and
a_title == 'center' and c_subtitle == #b2b5be80 and s_subtitle == 'normal' and
a_subtitle == 'center'
t := time
max := high
min := low

bx := box.new(n, max, n, min

, bgcolor = color.new(session_css, bg_transp)
, border_color = show_outline ? session_css : na
, border_style = line.style_dotted)

if show_txt and showSessions and textVPosition == 'middle' and

textHPosition == 'center' and c_title == #b2b5be80 and s_title == 'large' and
a_title == 'center' and c_subtitle == #b2b5be80 and s_subtitle == 'normal' and
a_subtitle == 'center'
lbl := label.new(t, max, session_name
, xloc = xloc.bar_time
, textcolor = session_css
, style = label.style_label_down
, color = color.new(color.white, 100)
, size = size.tiny)

if session and session == session[1] and showSessions and textVPosition ==

'middle' and textHPosition == 'center' and c_title == #b2b5be80 and s_title ==
'large' and a_title == 'center' and c_subtitle == #b2b5be80 and s_subtitle ==
'normal' and a_subtitle == 'center'
max := math.max(high, max)
min := math.min(low, min)

box.set_top(bx, max)
box.set_rightbottom(bx, n, min)
 if show_txt
label.set_xy(lbl, int(math.avg(t, time)), max)

[session ? na : max, session ? na : min]

//-----------------------------------------------------------------------------}
//Sessions
//-----------------------------------------------------------------------------{
tf = timeframe.period

var tz = use_exchange ? syminfo.timezone :

str.format('UTC{0}{1}', tz_incr >= 0 ? '+' : '-', math.abs(tz_incr))

is_sesa = math.sign(nz(time(tf, sesa_ses, tz)))

is_sesb = math.sign(nz(time(tf, sesb_ses, tz)))

//-----------------------------------------------------------------------------}
//Dashboard
//-----------------------------------------------------------------------------{

var float max_sesa = na

var float min_sesa = na
var float max_sesb = na
var float min_sesb = na
var float max_sesc = na
var float min_sesc = na
var float max_sesd = na
var float min_sesd = na

//Ranges
if show_sesa and sesa_range and textVPosition == 'middle' and textHPosition ==
'center' and c_title == #b2b5be80 and s_title == 'large' and a_title == 'center'
and c_subtitle == #b2b5be80 and s_subtitle == 'normal' and a_subtitle == 'center'
[max, min] = get_range(is_sesa, sesa_txt, sesa_css)
max_sesa := max
min_sesa := min

if show_sesb and sesb_range and textVPosition == 'middle' and textHPosition ==

'center' and c_title == #b2b5be80 and s_title == 'large' and a_title == 'center'
and c_subtitle == #b2b5be80 and s_subtitle == 'normal' and a_subtitle == 'center'
[max, min] = get_range(is_sesb, sesb_txt, sesb_css)
max_sesb := max
min_sesb := min

//Trendlines
//Mean
if show_sesa and sesa_avg and textVPosition == 'middle' and textHPosition ==
'center' and c_title == #b2b5be80 and s_title == 'large' and a_title == 'center'
and c_subtitle == #b2b5be80 and s_subtitle == 'normal' and a_subtitle == 'center'
avg = get_avg(is_sesa)
set_line(is_sesa, avg, avg, sesa_css)

if show_sesb and sesb_avg and textVPosition == 'middle' and textHPosition ==

'center' and c_title == #b2b5be80 and s_title == 'large' and a_title == 'center'
and c_subtitle == #b2b5be80 and s_subtitle == 'normal' and a_subtitle == 'center'
avg = get_avg(is_sesb)
set_line(is_sesb, avg, avg, sesb_css)

//VWAP
//-----------------------------------------------------------------------------}
//Plots
//-----------------------------------------------------------------------------{
//Plot max/min
plot(showSessions and sesa_maxmin and textVPosition == 'middle' and textHPosition
== 'center' and c_title == #b2b5be80 and s_title == 'large' and a_title == 'center'
and c_subtitle == #b2b5be80 and s_subtitle == 'normal' and a_subtitle == 'center' ?
max_sesa : na, 'Session A Maximum', sesa_css, 1, plot.style_linebr, editable =
false)
plot(showSessions and sesa_maxmin and textVPosition == 'middle' and textHPosition
== 'center' and c_title == #b2b5be80 and s_title == 'large' and a_title == 'center'
and c_subtitle == #b2b5be80 and s_subtitle == 'normal' and a_subtitle == 'center' ?
min_sesa : na, 'Session A Minimum', sesa_css, 1, plot.style_linebr, editable =
false)

plot(showSessions and sesb_maxmin and textVPosition == 'middle' and textHPosition

== 'center' and c_title == #b2b5be80 and s_title == 'large' and a_title == 'center'
and c_subtitle == #b2b5be80 and s_subtitle == 'normal' and a_subtitle == 'center' ?
max_sesb : na, 'Session B Maximum', sesb_css, 1, plot.style_linebr, editable =
false)
plot(showSessions and sesb_maxmin and textVPosition == 'middle' and textHPosition
== 'center' and c_title == #b2b5be80 and s_title == 'large' and a_title == 'center'
and c_subtitle == #b2b5be80 and s_subtitle == 'normal' and a_subtitle == 'center' ?
min_sesb : na, 'Session B Minimum', sesb_css, 1, plot.style_linebr, editable =
false)

//Plot Divider A
plotshape(is_sesa and show_ses_div and show_sesa and showSessions, "·"
, shape.square
, location.bottom
, na
, text = "."
, textcolor = sesa_css
, size = size.tiny
, display = display.all - display.status_line
, editable = false)

plotshape(is_sesa != is_sesa[1] and show_ses_div and show_sesa and showSessions,

"NYE"
, shape.labelup
, location.bottom
, na
, text = "❚"
, textcolor = sesa_css
, size = size.tiny
, display = display.all - display.status_line
, editable = false)

//Plot Divider B
plotshape(is_sesb and show_ses_div and show_sesb and showSessions, "·"
, shape.labelup
, location.bottom
, na
, text = "."
, textcolor = sesb_css
, size = size.tiny
, display = display.all - display.status_line
, editable = false)
plotshape(is_sesb != is_sesb[1] and show_ses_div and show_sesb and showSessions,
"LDN"
, shape.labelup
, location.bottom
, na
, text = "❚"
, textcolor = sesb_css
, size = size.tiny
, display = display.all - display.status_line
, editable = false)

// # ============================[FUNCTIONS]============================ #

type bar
float o = open
float h = high
float l = low
float c = close
float v = volume
int i = bar_index

bar b = bar.new()
nzV = nz(b.v)

f_calcV() =>
uV = 0.0
dV = 0.0

switch
(b.c - b.l) > (b.h - b.c) => uV := nzV
(b.c - b.l) < (b.h - b.c) => dV := -nzV
b.c > b.o => uV := nzV
b.c < b.o => dV := -nzV
b.c > nz(b.c[1]) => uV := nzV
b.c < nz(b.c[1]) => dV := -nzV
nz(uV[1]) > 0 => uV := uV + nzV
nz(dV[1]) < 0 => dV := dV - nzV

[uV, dV]

// # ============================[CONSTANT VARIABLES]============================ #
sma4 = ta.sma(close, 4)
sma5 = ta.sma(close, 5)
sma9 = ta.sma(close, 9)
ema50 = ta.ema(close, 50)
ema200 = ta.ema(close, 200)

bullishSignalColor = #59e08a
bearishSignalColor = #ff5959

dashboardRedText = #ee787d
dashboardGreenText = #42bda8
dashboardGreenBackground = #284444
dashboardRedBackground = #49343e
// # ============================[CANDLE COLORING]============================ #
macdFastLength = 12
macdSlowLength = 26
macdSignalLength = 9

if (candleColorType != 'Confirmation Simple')

macdFastLength := 10
macdSlowLength := 25
macdSignalLength:=8

[MacdX, signalX, histX] = ta.macd(close, macdFastLength, macdSlowLength,

macdSignalLength)

//candle color scheme

greenHigh = #4ce653
greenMidHigh =#4ce653
greenMidLow =#4ce653
greenLow = #56328f

// Yellow
yellowLow = #56328f

// 4 level of red
redHigh = #ff0000
redMidHigh = #ff0000
redMidLow = #ff0000
redLow = #56328f

if (candleColorType == 'Confirmation Gradient')

greenHigh := #01d70c
greenMidHigh := #269444
greenMidLow :=#4f966c
greenLow := #425970

// Yellow
yellowLow := #513a88

// 4 level of red
redHigh := #ff0000
redMidHigh := #c21637
redMidLow := #c33252
redLow := #8e215f
if (candleColorType == 'Contrarian Gradient')
redHigh := #01d70c
redMidHigh := #269444
redMidLow :=#4f966c
redLow := #425970

// Yellow
yellowLow := #513a88

// 4 level of red
greenHigh := #ff0000
greenMidHigh := #c21637
greenMidLow := #c33252
greenLow := #8e215f

// Default color
candleBody = yellowLow

if histX > 0
if histX > histX[1] and histX[1] > 0 and textVPosition == 'middle' and
textHPosition == 'center' and c_title == #b2b5be80 and s_title == 'large' and
a_title == 'center' and c_subtitle == #b2b5be80 and s_subtitle == 'normal' and
a_subtitle == 'center'
candleBody := greenLow

if histX < 0
if histX < histX[1] and histX[1] < 0 and textVPosition == 'middle' and
textHPosition == 'center' and c_title == #b2b5be80 and s_title == 'large' and
a_title == 'center' and c_subtitle == #b2b5be80 and s_subtitle == 'normal' and
a_subtitle == 'center'
candleBody := redLow

// Bullish trend
if MacdX > 0 and histX > 0
candleBody := greenMidLow

if histX > histX[1] and MacdX[1] > 0 and histX[1] > 0 and textVPosition ==
'middle' and textHPosition == 'center' and c_title == #b2b5be80 and s_title ==
'large' and a_title == 'center' and c_subtitle == #b2b5be80 and s_subtitle ==
'normal' and a_subtitle == 'center'
candleBody := greenMidHigh

if histX > histX[2] and MacdX[2] > 0 and histX[2] > 0 and textVPosition ==
'middle' and textHPosition == 'center' and c_title == #b2b5be80 and s_title ==
'large' and a_title == 'center' and c_subtitle == #b2b5be80 and s_subtitle ==
'normal' and a_subtitle == 'center'
candleBody := greenHigh

// Bearish trend
if MacdX < 0 and histX < 0
candleBody := redMidLow

if histX < histX[1] and MacdX[1] < 0 and histX[1] < 0 and textVPosition ==
'middle' and textHPosition == 'center' and c_title == #b2b5be80 and s_title ==
'large' and a_title == 'center' and c_subtitle == #b2b5be80 and s_subtitle ==
'normal' and a_subtitle == 'center'
candleBody := redMidHigh

if histX < histX[2] and MacdX[2] < 0 and histX[2] < 0 and textVPosition ==
'middle' and textHPosition == 'center' and c_title == #b2b5be80 and s_title ==
'large' and a_title == 'center' and c_subtitle == #b2b5be80 and s_subtitle ==
'normal' and a_subtitle == 'center'
candleBody := redHigh

barcolor(candleColorType == 'None' ? na : candleBody, editable = false)

// # ============================[SMART TRAIL]============================ #
[smartTrailLine, fillerLine, smartTrailDirection] = LAF.getSmartTrail(10, 4, 8)
smartTrail1 = plot(smartTrail and textVPosition == 'middle' and textHPosition ==
'center' and c_title == #b2b5be80 and s_title == 'large' and a_title == 'center'
and c_subtitle == #b2b5be80 and s_subtitle == 'normal' and a_subtitle == 'center' ?
smartTrailLine : na, "Smart Trail", style = plot.style_line, color =
smartTrailDirection== 'long' ? color.new(#2157f9, 0) : smartTrailDirection ==
'short' ? color.new(#ff1100, 0) : na, editable = false)
smartTrail2 = plot(smartTrail and textVPosition == 'middle' and textHPosition ==
'center' and c_title == #b2b5be80 and s_title == 'large' and a_title == 'center'
and c_subtitle == #b2b5be80 and s_subtitle == 'normal' and a_subtitle == 'center' ?
fillerLine : na, "Fib 2", style = plot.style_line, transp = 100, editable = false)
fill(smartTrail1, smartTrail2, color = smartTrailDirection == 'long' ?
color.new(#2157f9, 80) : smartTrailDirection == 'short' ? color.new(#ff1100, 80) :
na, editable = false)

// # ============================[TREND CATCHER]============================ #
[trendCatcherLine, trendCatcherColor] = LAF.getTrendCatcher()
newTrendCatcherColor = trendCatcherColor == color.blue ? #02ff65 : #ff1100
plot(trendCatcher and textVPosition == 'middle' and textHPosition == 'center' and
c_title == #b2b5be80 and s_title == 'large' and a_title == 'center' and c_subtitle
== #b2b5be80 and s_subtitle == 'normal' and a_subtitle == 'center' ?
trendCatcherLine : na, title='Trend Catcher', linewidth=2,
color=newTrendCatcherColor, editable = false)

// # ============================[NEO CLOUD]============================ #

// # ============================[REVERSAL ZONES]============================ #

// # ============================[TREND TRACER]============================ #
[trendTracerLine, trendTracerDirection] = LAF.getTrendTracer()
plot(trendTracer and textVPosition == 'middle' and textHPosition == 'center' and
c_title == #b2b5be80 and s_title == 'large' and a_title == 'center' and c_subtitle
== #b2b5be80 and s_subtitle == 'normal' and a_subtitle == 'center' ?
trendTracerLine : na, title='Trend Tracer', linewidth=2, style=plot.style_cross,
color = trendTracerDirection, editable = false)

// # ============================[DASHBOARD
COMPONENTS|]============================ #

trendStrengthMetric = math.abs(LAF.getTrendStrengthMetric(14, 'RMA', 21, 'EMA'))

trendStrengthMetric := trendStrengthMetric*2.5
trendIndication = trendStrengthMetric > 30 and textVPosition == 'middle' and
textHPosition == 'center' and c_title == #b2b5be80 and s_title == 'large' and
a_title == 'center' and c_subtitle == #b2b5be80 and s_subtitle == 'normal' and
❄️
a_subtitle == 'center' ? "" : " "
trendStrengthCellColor = newTrendCatcherColor == #02ff65 ? dashboardGreenBackground
: dashboardRedBackground
trendStrengthTextColor = trendStrengthCellColor == dashboardGreenBackground ?
dashboardGreenText : dashboardRedText

volatilityMetric = LAF.getVolatilityMetric()
volatilityMetric2 = ta.sma(LAF.getVolatilityMetric(), 8)
volatilityText = volatilityMetric < 30 ? 'Stable' : volatilityMetric < 80 ?
'Moderate' : 'Volatile'
volatilityEmoji = volatilityMetric2 > volatilityMetric ? '📉' : '📈'
volatilityCellColor = newTrendCatcherColor == #02ff65 ? dashboardGreenBackground :
dashboardRedBackground
VolatilityTextColor = trendStrengthCellColor == dashboardGreenBackground ?
dashboardGreenText : dashboardRedText

squeezeMetric = LAF.getSqueezeMetric(45, 20)

squeezeIsHigh = squeezeMetric >= 80 ? true : false
squeezeCellColor = trendTracerDirection == #02ff65 ? #1a3a3e : #482632
squeezeTextColor = trendTracerDirection != #02ff65 ? #ed3544 : #0a907a
// and textVPosition == 'middle' and textHPosition == 'center' and c_title ==
#b2b5be80 and s_title == 'large' and a_title == 'center' and c_subtitle ==
#b2b5be80 and s_subtitle == 'normal' and a_subtitle == 'center'
//
[uV, dV] = f_calcV()

totalVolume = uV + math.abs(dV)
//volumecolor = totalVolume >= 50 ? bullish : bearish
volumeCellColor = dashboardRedBackground
volumeTextColor = totalVolume >= 50 ? dashboardGreenText : dashboardRedText
if (totalVolume >= 50)
totalVolume := totalVolume*2
volumeCellColor := dashboardGreenBackground
else
totalVolume := totalVolume*-2

volumeSentiment = totalVolume

table_position = dashboardLocation == 'Bottom Left' ? position.bottom_left

: dashboardLocation == 'Top Right' ? position.top_right
: position.bottom_right

table_size = dashboardSize == 'Tiny' ? size.tiny

: dashboardSize == 'Small' ? size.small
: size.normal

tb = table.new(table_position, 7, 7
, bgcolor = #1e222d
, border_color = #373a46
, border_width = 1
, frame_color = #373a46
, frame_width = 1)

if showDashboard
if barstate.islast
tb.cell(0, 2, autopilotMode == 'Off' ? "✈️
Optimal Sensivity" : " Autopilot
Enabled", text_color = color.white, text_size = table_size, text_halign =
text.align_left)
tb.cell(0, 3, str.tostring(trendIndication) + "Trend Strength", text_color
= color.white, text_size = table_size, text_halign = text.align_left)
tb.cell(0, 4, volatilityEmoji+ " Lux Volatility", text_color = color.white,
text_size = table_size, text_halign = text.align_left)
tb.cell(0, 5, "🔃 Squeeze", text_color = color.white, text_size =
table_size, text_halign = text.align_left)
tb.cell(0, 6, "💧 Volume Sentiment", text_color = color.white, text_size =
table_size, text_halign = text.align_left)

tb.cell(1, 2, autopilotMode, text_color = color.white, text_size =

table_size)
tb.cell(1, 3, str.tostring(trendStrengthMetric, format.percent),
text_color=trendStrengthTextColor, text_size=table_size, bgcolor =
trendStrengthCellColor)
tb.cell(1, 4, volatilityText, text_color = VolatilityTextColor, text_size =
table_size, bgcolor = volatilityCellColor)
tb.cell(1, 5, str.tostring(squeezeMetric, format.percent), text_color=
squeezeTextColor, text_size=table_size, bgcolor = squeezeCellColor)
tb.cell(1, 6, str.tostring(math.min(volumeSentiment, 100.),
format.percent), text_color = volumeTextColor, text_size = table_size, bgcolor =
volumeCellColor)
//
***********************************************************************************
*************************
// REV ZONES
//
***********************************************************************************
*************************

indiSet = false
source = hlc3
type = 'SuperSmoother'
length = 100
innermult = 1.0
outermult = 2.415

ChartSet = false
drawchannel = true
displayzone = true
zonetransp = 60
displayline = true

MTFSet = false
enable_mtf = true
mtf_disp_typ = 'On Hover'
mtf_typ = 'Auto'
mtf_lvl1 = 'D'
mtf_lvl2 = 'W'

//
***********************************************************************************
*************************
// Functions Start {
//
***********************************************************************************
*************************
var pi = 2 * math.asin(1)
var mult = pi * innermult
var mult2 = pi * outermult
var gradsize = 0.5
var gradtransp = zonetransp

//-----------------------
// Ehler SwissArmyKnife Function
//-----------------------
SAK_smoothing(_type, _src, _length) =>
c0 = 1.0
c1 = 0.0
b0 = 1.0
b1 = 0.0
b2 = 0.0
a1 = 0.0
a2 = 0.0
alpha = 0.0
beta = 0.0
gamma = 0.0
cycle = 2 * pi / _length
 if _type == 'Ehlers EMA'
alpha := (math.cos(cycle) + math.sin(cycle) - 1) / math.cos(cycle)
b0 := alpha
a1 := 1 - alpha
a1
if _type == 'Gaussian'
beta := 2.415 * (1 - math.cos(cycle))
alpha := -beta + math.sqrt(beta * beta + 2 * beta)
c0 := alpha * alpha
a1 := 2 * (1 - alpha)
a2 := -(1 - alpha) * (1 - alpha)
a2
if _type == 'Butterworth'
beta := 2.415 * (1 - math.cos(cycle))
alpha := -beta + math.sqrt(beta * beta + 2 * beta)
c0 := alpha * alpha / 4
b1 := 2
b2 := 1
a1 := 2 * (1 - alpha)
a2 := -(1 - alpha) * (1 - alpha)
a2
if _type == 'BandStop'
beta := math.cos(cycle)
gamma := 1 / math.cos(cycle * 2 * 0.1) // delta default to 0.1. Acceptable
delta -- 0.05<d<0.5
alpha := gamma - math.sqrt(gamma * gamma - 1)
c0 := (1 + alpha) / 2
b1 := -2 * beta
b2 := 1
a1 := beta * (1 + alpha)
a2 := -alpha
a2
if _type == 'SMA'
c1 := 1 / _length
b0 := 1 / _length
a1 := 1
a1
if _type == 'EMA'
alpha := 2 / (_length + 1)
b0 := alpha
a1 := 1 - alpha
a1
if _type == 'RMA'
alpha := 1 / _length
b0 := alpha
a1 := 1 - alpha
a1

_Input = _src
_Output = 0.0
_Output := c0 * (b0 * _Input + b1 * nz(_Input[1]) + b2 * nz(_Input[2])) + a1 *
nz(_Output[1]) + a2 * nz(_Output[2]) - c1 * nz(_Input[_length])
_Output

//-----------------------
// SuperSmoother Function
//-----------------------
supersmoother(_src, _length) =>
 s_a1 = math.exp(-math.sqrt(2) * pi / _length)
s_b1 = 2 * s_a1 * math.cos(math.sqrt(2) * pi / _length)
s_c3 = -math.pow(s_a1, 2)
s_c2 = s_b1
s_c1 = 1 - s_c2 - s_c3
ss = 0.0
ss := s_c1 * _src + s_c2 * nz(ss[1], _src[1]) + s_c3 * nz(ss[2], _src[2])
ss

//-----------------------
// Auto TimeFrame Function
//-----------------------
// ————— Converts current chart resolution into a float minutes value.
f_resInMinutes() =>
_resInMinutes = timeframe.multiplier * (timeframe.isseconds ? 1. / 60 :
timeframe.isminutes ? 1. : timeframe.isdaily ? 60. * 24 : timeframe.isweekly ? 60.
* 24 * 7 : timeframe.ismonthly ? 60. * 24 * 30.4375 : na)
_resInMinutes

get_tf(_lvl) =>
y = f_resInMinutes()
z = timeframe.period
if mtf_typ == 'Auto'
if y < 1
z := _lvl == 1 ? '1' : _lvl == 2 ? '5' : z
z
else if y <= 3
z := _lvl == 1 ? '5' : _lvl == 2 ? '15' : z
z
else if y <= 10
z := _lvl == 1 ? '15' : _lvl == 2 ? '60' : z
z
else if y <= 30
z := _lvl == 1 ? '60' : _lvl == 2 ? '240' : z
z
else if y <= 120
z := _lvl == 1 ? '240' : _lvl == 2 ? 'D' : z
z
else if y <= 240
z := _lvl == 1 ? 'D' : _lvl == 2 ? 'W' : z
z
else if y <= 1440
z := _lvl == 1 ? 'W' : _lvl == 2 ? 'M' : z
z
else if y <= 10080
z := _lvl == 1 ? 'M' : z
z
else
z := z
z
else
z := _lvl == 1 ? mtf_lvl1 : _lvl == 2 ? mtf_lvl2 : z
z

//-----------------------
// Mean Reversion Channel Function
//-----------------------
get_mrc() =>
v_condition = 0
v_meanline = source
v_meanrange = supersmoother(ta.tr, length)

//-- Get Line value

if type == 'SuperSmoother'
v_meanline := supersmoother(source, length)
v_meanline

if type != 'SuperSmoother'
v_meanline := SAK_smoothing(type, source, length)
v_meanline

v_upband1 = v_meanline + v_meanrange * mult

v_loband1 = v_meanline - v_meanrange * mult
v_upband2 = v_meanline + v_meanrange * mult2
v_loband2 = v_meanline - v_meanrange * mult2

//-- Check Condition

if close > v_meanline
v_upband2_1 = v_upband2 + v_meanrange * gradsize * 4
v_upband2_9 = v_upband2 + v_meanrange * gradsize * -4
if high >= v_upband2_9 and high < v_upband2
v_condition := 1
v_condition
else if high >= v_upband2 and high < v_upband2_1
v_condition := 2
v_condition
else if high >= v_upband2_1
v_condition := 3
v_condition
else if close <= v_meanline + v_meanrange
v_condition := 4
v_condition
else
v_condition := 5
v_condition

if close < v_meanline

v_loband2_1 = v_loband2 - v_meanrange * gradsize * 4
v_loband2_9 = v_loband2 - v_meanrange * gradsize * -4
if low <= v_loband2_9 and low > v_loband2
v_condition := -1
v_condition
else if low <= v_loband2 and low > v_loband2_1
v_condition := -2
v_condition
else if low <= v_loband2_1
v_condition := -3
v_condition
else if close >= v_meanline + v_meanrange
v_condition := -4
v_condition
else
v_condition := -5
v_condition

[v_meanline, v_meanrange, v_upband1, v_loband1, v_upband2, v_loband2,

v_condition]

//-----------------------
// MTF Analysis
//-----------------------

get_stat(_cond) =>
ret = 'Price at Mean Line\n'
if _cond == 1
ret := 'Overbought (Weak)\n'
ret
else if _cond == 2
ret := 'Overbought\n'
ret
else if _cond == 3
ret := 'Overbought (Strong)\n'
ret
else if _cond == 4
ret := 'Price Near Mean\n'
ret
else if _cond == 5
ret := 'Price Above Mean\n'
ret
else if _cond == -1
ret := 'Oversold (Weak)\n'
ret
else if _cond == -2
ret := 'Oversold\n'
ret
else if _cond == -3
ret := 'Oversold (Strong)\n'
ret
else if _cond == -4
ret := 'Price Near Mean\n'
ret
else if _cond == -5
ret := 'Price Below Mean\n'
ret
ret

//-----------------------
// Chart Drawing Function
//-----------------------
format_price(x) =>
y = str.tostring(x, '0.00000')
if x > 10
y := str.tostring(x, '0.000')
y
if x > 1000
y := str.tostring(x, '0.00')
y
y

f_PriceLine(_ref, linecol) =>

line.new(x1=bar_index, x2=bar_index - 1, y1=_ref, y2=_ref, extend=extend.left,
color=linecol)

f_MTFLabel(_txt, _yloc) =>

label.new(x=time + math.round(ta.change(time) * 20), y=_yloc,
xloc=xloc.bar_time, text=mtf_disp_typ == 'Always Display' ? _txt : 'Check MTF',
tooltip=mtf_disp_typ == 'Always Display' ? '' : _txt, color=color.black,
textcolor=color.white, size=size.normal, style=mtf_disp_typ == 'On Hover' and
displayline ? label.style_label_lower_left : label.style_label_left,
textalign=text.align_left)

//} Function End

//
***********************************************************************************
*************************
// Calculate Channel
//
***********************************************************************************
*************************
var tf_0 = timeframe.period
var tf_1 = get_tf(1)
var tf_2 = get_tf(2)
textstylist = table.new(textVPosition + '_' + textHPosition, 1, 3)
[meanline, meanrange, upband1, loband1, upband2, loband2, condition] = get_mrc()
[mtf1_meanline, mtf1_meanrange, mtf1_upband1, mtf1_loband1, mtf1_upband2,
mtf1_loband2, mtf1_condition] = request.security(syminfo.tickerid, tf_1, get_mrc())
[mtf2_meanline, mtf2_meanrange, mtf2_upband1, mtf2_loband1, mtf2_upband2,
mtf2_loband2, mtf2_condition] = request.security(syminfo.tickerid, tf_2, get_mrc())

//
***********************************************************************************
*************************
// Drawing Start {
//
***********************************************************************************
*************************
float p_meanline = drawchannel ? meanline : na
float p_upband1 = drawchannel ? upband1 : na
float p_loband1 = drawchannel ? loband1 : na
float p_upband2 = drawchannel ? upband2 : na
float p_loband2 = drawchannel ? loband2 : na

//z = plot(p_meanline, color=color.new(#FFCD00, 0), style=plot.style_line, title='

Mean', linewidth=2)
//x1 = plot(p_upband1, color=color.new(color.green, 50), style=plot.style_circles,
title=' R1', linewidth=1)
//x2 = plot(p_loband1, color=color.new(color.green, 50), style=plot.style_circles,
title=' S1', linewidth=1)
//y1 = plot(p_upband2, color=color.new(color.red, 50), style=plot.style_line,
title=' R2', linewidth=1)
//y2 = plot(p_loband2, color=color.new(color.red, 50), style=plot.style_line,
title=' S2', linewidth=1)

//-----------------------
// Draw zone
//-----------------------
//---
var color1 = #FF0000
var color2 = #FF4200
var color3 = #FF5D00
var color4 = #FF7400
var color5 = #FF9700
var color6 = #FFAE00
var color7 = #FFC500
var color8 = #FFCD00
//---
float upband2_1 = drawchannel and displayzone ? upband2 + meanrange * gradsize *
4 : na
float loband2_1 = drawchannel and displayzone ? loband2 - meanrange * gradsize *
4 : na
float upband2_2 = drawchannel and displayzone ? upband2 + meanrange * gradsize *
3 : na
float loband2_2 = drawchannel and displayzone ? loband2 - meanrange * gradsize *
3 : na
float upband2_3 = drawchannel and displayzone ? upband2 + meanrange * gradsize *
2 : na
float loband2_3 = drawchannel and displayzone ? loband2 - meanrange * gradsize *
2 : na
float upband2_4 = drawchannel and displayzone ? upband2 + meanrange * gradsize *
1 : na
float loband2_4 = drawchannel and displayzone ? loband2 - meanrange * gradsize *
1 : na
float upband2_5 = drawchannel and displayzone ? upband2 + meanrange * gradsize *
0 : na
float loband2_5 = drawchannel and displayzone ? loband2 - meanrange * gradsize *
0 : na
float upband2_6 = drawchannel and displayzone ? upband2 + meanrange * gradsize * -1
: na
float loband2_6 = drawchannel and displayzone ? loband2 - meanrange * gradsize * -1
: na
float upband2_7 = drawchannel and displayzone ? upband2 + meanrange * gradsize * -2
: na
float loband2_7 = drawchannel and displayzone ? loband2 - meanrange * gradsize * -2
: na
float upband2_8 = drawchannel and displayzone ? upband2 + meanrange * gradsize * -3
: na
float loband2_8 = drawchannel and displayzone ? loband2 - meanrange * gradsize * -3
: na
float upband2_9 = drawchannel and displayzone ? upband2 + meanrange * gradsize * -4
: na
float loband2_9 = drawchannel and displayzone ? loband2 - meanrange * gradsize * -4
: na

up1 = plot(reversalZone ? upband2_1 : na, color = color.black, transp = 100,

editable = false)
up2 = plot(reversalZone ?upband2_5:na, color = color.black, transp = 100, editable
= false)
up3 = plot(reversalZone ?upband2_9:na, color = color.black, transp = 100, editable
= false)
dp1 = plot(reversalZone ?loband2_1:na, color = color.black, transp = 100, editable
= false)
dp2 = plot(reversalZone ?loband2_5:na, color = color.black, transp = 100, editable
= false)
dp3 = plot(reversalZone ?loband2_9:na, color = color.black, transp = 100, editable
= false)

fill(up1, up2, color = #56202d, transp = 20, editable = false)

fill(up2, up3, color = #3f1d29, transp = 60, editable = false)
fill(dp1, dp2, color = #0f3e3f, transp = 20, editable = false)
fill(dp2, dp3, color = #113135, transp = 60, editable = false)

//[upband2_1, upband2_5, upband2_9, loband2_1, loband2_5, loband2_9]

tenkan_len = 365
tenkan_mult = 3

kijun_len = 365
kijun_mult = 7

spanB_len = 365
spanB_mult = 15

offset = 2
//------------------------------------------------------------------------------
avg(src,length,mult)=>
atr = ta.atr(length)*mult
up = hl2 + atr
dn = hl2 - atr
upper = 0.,lower = 0.
upper := src[1] < upper[1] ? math.min(up,upper[1]) : up
lower := src[1] > lower[1] ? math.max(dn,lower[1]) : dn

os = 0,max = 0.,min = 0.
os := src > upper ? 1 : src < lower ? 0 : os[1]
spt = os == 1 ? lower : upper
max := ta.cross(src,spt) ? math.max(src,max[1]) : os == 1 ?
math.max(src,max[1]) : spt
min := ta.cross(src,spt) ? math.min(src,min[1]) : os == 0 ?
math.min(src,min[1]) : spt
math.avg(max,min)
//------------------------------------------------------------------------------
tenkan = avg(close,tenkan_len,tenkan_mult)
kijun = avg(close,kijun_len,kijun_mult)

senkouA = math.avg(kijun,tenkan)
senkouB = avg(close,spanB_len,spanB_mult)
//------------------------------------------------------------------------------
tenkan_css = #2156f300
kijun_css = #ff5e0000

cloud_a = color.new(#006989, 47)

cloud_b = color.new(#ff5252, 66)

chikou_css = #7b1fa2

plot(neoCloud ? tenkan : na,'Tenkan-Sen',tenkan_css, editable = false)

plot(neoCloud ? kijun : na,'Kijun-Sen',kijun_css, editable = false)

plot(neoCloud and ta.crossover(tenkan,kijun) ? kijun :

na,'Crossover',#2156f300,3,plot.style_circles, editable = false)
plot(neoCloud and ta.crossunder(tenkan,kijun) ? kijun :
na,'Crossunder',#ff5e0000,3,plot.style_circles, editable = false)
A = plot(neoCloud ? senkouA: na,'Senkou Span A',na,offset=offset-1, editable =
false)
B = plot(neoCloud ? senkouB : na,'Senkou Span B',na,offset=offset-1, editable =
false)
fill(A,B,senkouA > senkouB ? cloud_a : cloud_b)

lastNeo = int(senkouA + senkouB)

last5Neo = ta.sma(lastNeo, 2)

plot(close,'Chikou',chikou_css,offset=-offset+1,display=display.none, editable =
false)

// Wylicz pozycję kwadratu

ltp1 = bar_index
rtp1 = bar_index + 40

[lowBound, midBound, highBound] = LAF.getTPSLBoxes(6.0)

// Stwórz rzeczywisty kwadrat

//tp1box = box.new(left=ltp1, top=ttp1, right=rtp1, bottom=btp1,
border_color=#3666f5, border_width=2, border_style=line.style_solid,
bgcolor=color.new(#3666f5, 53), text="TP1 : " + str.tostring(close),
text_size=size.large, text_color=color.new(#3666f5, 0), text_wrap=text.wrap_auto)
//var boxes = array.new<box>()
//boxes.push(box.new(left = ltp1, top = close+highBound, right = rtp1, bottom =
close + midBound, border_color=#3666f5, border_width=2,
border_style=line.style_solid, bgcolor=color.new(#3666f5, 70), text="TP/SL 2 : "
+ str.tostring(close), text_size=size.large, text_color=color.new(#3666f5, 0),
text_wrap=text.wrap_auto))
//boxes.push(box.new(left = ltp1, top = close+midBound, right = rtp1, bottom =
close + lowBound, border_color=#3666f5, border_width=2,
border_style=line.style_solid, bgcolor=color.new(#3666f5, 40), text="TP/SL 1 : "
+ str.tostring(close), text_size=size.large, text_color=color.new(#3666f5, 0),
text_wrap=text.wrap_auto))

//SL1 = box.new(left = ltp1, top = close-highBound, right = rtp1, bottom = close -

midBound, border_color=#3666f5, border_width=2, border_style=line.style_solid,
bgcolor=color.new(#3666f5, 70), text="TP/SL 2 : " + str.tostring(close),
text_size=size.large, text_color=color.new(#3666f5, 0), text_wrap=text.wrap_auto)
//SL2 = box.new(left = ltp1, top = close-midBound, right = rtp1, bottom = close -
lowBound, border_color=#3666f5, border_width=2, border_style=line.style_solid,
bgcolor=color.new(#3666f5, 40), text="TP/SL 1 : " + str.tostring(close),
text_size=size.large, text_color=color.new(#3666f5, 0), text_wrap=text.wrap_auto)

// Usuń poprzednie ramki

//box.delete(boxes.shift())
//box.delete(SL1[1])
//box.delete(SL2[1])

//box.delete(boxes.shift())
// ==== Overview ====
// ==================

// WaveTrend 3D (WT3D) is a novel implementation of the famous WaveTrend (WT)

indicator and has been completely redesigned from the ground up to address some
// of the inherent shortcomings associated with the traditional WT algorithm,
including:
// (1) unbounded extremes
// (2) susceptibility to whipsaw
// (3) lack of insight into other timeframes

// Furthermore, WT3D expands upon the original functionality of WT by providing:

// (1) first-class support for multi-timeframe (MTF) analysis
// (2) kernel-based regression for trend reversal confirmation
// (3) various options for signal smoothing and transformation
// (4) a unique mode for visualizing an input series as a symmetrical, three-
dimensional waveform useful for pattern identification and cycle-related analysis

// Fundamental Assumptions:
// (1) There exists a probability density function that describes the relative
likelihood for a price to visit a given value.
// (2) The probability density function for price is a function of time.
// (3) The probability density function can approximate a Gaussian distribution
(shown below).

// ___
// .::~!:.. |

// :ΞΞΞΞ~!ΞΞΞ!. |

// .ΞJΞΞΞΞ~!ΞΞΞ?J^ |

// :J?ΞΞΞΞΞ~!ΞΞΞΞΞJ^ |

// :J?ΞΞΞΞΞΞ~!ΞΞΞΞΞΞ??. |

// :JΞΞΞΞΞΞΞΞ~!ΞΞΞΞΞΞΞ?J^ |

// :JΞΞΞΞΞΞΞΞΞ~!ΞΞΞΞΞΞΞΞ?J^
[ PRICE ]
// .:~ΞΞΞΞΞΞΞΞΞΞ~!ΞΞΞΞΞΞΞΞΞ!!~ |

// :?~^ΞΞΞΞΞΞΞΞΞΞ~!ΞΞΞΞΞΞΞΞΞ!^Ξ! |

// ~:^^^ΞΞΞΞΞΞΞΞΞΞ~!ΞΞΞΞΞΞΞΞΞ!^^!Ξ. |

// .Ξ!^^^^ΞΞΞΞΞΞΞΞΞΞ~!ΞΞΞΞΞΞΞΞΞ!^^^~Ξ~ |

// .~Ξ~^^^^^ΞΞΞΞΞΞΞΞΞΞ~!ΞΞΞΞΞΞΞΞΞ!^^^^^!Ξ: |

// .~Ξ~^^^^^^^ΞΞΞΞΞΞΞΞΞΞ~!ΞΞΞΞΞΞΞΞΞ!^^^^^^~!!^. |

// ....::^^!~~^^^^^^^^^ΞΞΞΞΞΞΞΞΞΞ~!ΞΞΞΞΞΞΞΞΞ!^^^^^^^^^~!^^::...... |

// ..:::^^^^^^^::::::::::::::ΞΞΞΞΞΞΞΞΞΞ~!ΞΞΞΞΞΞΞΞΞ!::::::::::::^^^^^^^^:::.. |

//
// -------------------------------- [ TIME ] -------------------------------|
// How to use this indicator:
// - The basic usage of WT3D is similar to how one would use the traditional WT
indicator.
// - Divergences can be spotted by finding "trigger waves", which are small waves
that immediately follow a larger wave. These can also be thought of as Lower-Highs
and Higher-Lows in the oscillator.
// - Instead of the SMA-cross in the original WT, the primary mechanism for
identifying potential pivots are the crossovers of the fast/normal speed
oscillators, denoted by the small red/green circles.
// - The larger red/green circles represent points where there could be a potential
trigger wave for a Divergence. Settings related to Divergence detection can be
configured in the "Divergence" section.
// - For overbought/oversold conditions, the 0.5 and -0.5 levels are convenient
since the normal-speed oscillator will only exceed this level ~25% of the time.
// - For less experienced users, focusing on the three oscillators is recommended
since they give critical information from multiple timeframes that can help to
identify trends and spot potential divergences.
// - For more experienced users, this indicator also has many other valuable
features, such as Center of Gravity (CoG) smoothing, Kernel Estimate Crossovers, a
mirrored mode for cycle analysis, and more.
// - Note: Additional resources for learning/using the more advanced features of
this indicator are a work in progress, but in the meantime, I am happy to answer
any questions.

// ================
// ==== Inputs ====
// ================

// Signal Settings
src = close
useMirror = false
useEma = false
emaLength = 3
useCog = false
cogLength = 6
oscillatorLookback =20
quadraticMeanLength = 50
src := useEma ? ta.ema(src, emaLength) : src
src := useCog ? ta.cog(src, cogLength) : src
speedToEmphasize = 'Normal'
emphasisWidth = 2
useKernelMA = false
useKernelEmphasis = false

// Oscillator Settings
offset := 0
showOsc = true
showOsc := showOsc
float f_length = 0.75
float f_smoothing = 0.45
float n_length = 1.0
float n_smoothing = 1.0
float s_length = 1.75
float s_smoothing = 2.5

// Divergence Detection
divThreshold = 30
sizePercent = 40
// Overbought/Oversold Zones (Reversal Zones)
showObOs = false
invertObOsColors = false

// Transparencies and Gradients

areaBackgroundTrans = 128.
areaForegroundTrans = 64.
lineBackgroundTrans = 2.6
lineForegroundTrans = 2.
customTransparency = 30
maxStepsForGradient = 8

// The defaults are colors that Google uses for its Data Science libraries (e.g.
TensorFlow). They are considered to be colorblind-safe.
var color fastBullishColor = color.black
var color normalBullishColor = color.black
var color slowBullishColor = color.black
var color fastBearishColor = color.black
var color normalBearishColor = color.black
var color slowBearishColor =color.black
var color c_bullish = color.black
var color c_bearish = color.black

lineBackgroundTrans := lineBackgroundTrans * customTransparency

areaBackgroundTrans := areaBackgroundTrans * customTransparency
lineForegroundTrans := lineForegroundTrans * customTransparency
areaForegroundTrans := areaForegroundTrans * customTransparency

areaFastTrans = areaBackgroundTrans
lineFastTrans = lineBackgroundTrans
areaNormalTrans = areaBackgroundTrans
lineNormalTrans = lineBackgroundTrans
areaSlowTrans = areaForegroundTrans
lineSlowTrans = lineForegroundTrans

switch speedToEmphasize
"Slow" =>
areaFastTrans := areaBackgroundTrans
lineFastTrans := lineBackgroundTrans
areaNormalTrans := areaBackgroundTrans
lineNormalTrans := lineBackgroundTrans
areaSlowTrans := areaForegroundTrans
lineSlowTrans := lineForegroundTrans
"Normal" =>
areaFastTrans := areaBackgroundTrans
lineFastTrans := lineBackgroundTrans
areaNormalTrans := areaForegroundTrans
lineNormalTrans := lineForegroundTrans
areaSlowTrans := areaBackgroundTrans
lineSlowTrans := lineBackgroundTrans
"Fast" =>
areaFastTrans := areaForegroundTrans
lineFastTrans := lineForegroundTrans
areaNormalTrans := areaBackgroundTrans
lineNormalTrans := lineBackgroundTrans
areaSlowTrans := areaBackgroundTrans
lineSlowTrans := lineBackgroundTrans
"None" =>
 areaFastTrans := areaBackgroundTrans
lineFastTrans := lineBackgroundTrans
areaNormalTrans := areaBackgroundTrans
lineNormalTrans := lineBackgroundTrans
areaSlowTrans := areaBackgroundTrans
lineSlowTrans := lineBackgroundTrans

// =================================
// ==== Color Helper Functions =====
// =================================

getPlotColor(signal, bullColor, bearColor) =>

signal >= 0.0 ? bullColor : bearColor

getAreaColor(signal, useMomentum, bullColor, bearColor) =>

if useMomentum
ta.rising(signal, 1) ? bullColor : bearColor
else
signal >= 0.0 ? bullColor : bearColor

getColorGradientFromSteps(_source, _center, _steps, weakColor, strongColor) =>

var float _qtyAdvDec = 0.
var float _maxSteps = math.max(1, _steps)
bool _xUp = ta.crossover(_source, _center)
bool _xDn = ta.crossunder(_source, _center)
float _chg = ta.change(_source)
bool _up = _chg > 0
bool _dn = _chg < 0
bool _srcBull = _source > _center
bool _srcBear = _source < _center
_qtyAdvDec := _srcBull ? _xUp ? 1 : _up ? math.min(_maxSteps, _qtyAdvDec + 1) :
_dn ? math.max(1, _qtyAdvDec - 1) : _qtyAdvDec : _srcBear ? _xDn ? 1 : _dn ?
math.min(_maxSteps, _qtyAdvDec + 1) : _up ? math.max(1, _qtyAdvDec - 1) :
_qtyAdvDec : _qtyAdvDec
color colorGradient = color.from_gradient(_qtyAdvDec, 1, _maxSteps, weakColor,
strongColor)
colorGradient

getColorGradientFromSource(series, _min, _max, weakColor, strongColor) =>

var float baseLineSeries = _min + (_max - _min) / 2
color colorGradient = series >= baseLineSeries ?
color.from_gradient(value=series, bottom_value=baseLineSeries, top_value=_max,
bottom_color=weakColor, top_color=strongColor) : color.from_gradient(series, _min,
baseLineSeries, strongColor, weakColor)
colorGradient

// ================================
// ==== Main Helper Functions =====
// ================================

normalizeDeriv(_src, _quadraticMeanLength) =>

float derivative = _src - _src[2]
quadraticMean = math.sqrt(nz(math.sum(math.pow(derivative, 2),
_quadraticMeanLength) / _quadraticMeanLength))
derivative/quadraticMean

tanh(series float _src) =>

-1 + 2/(1 + math.exp(-2*_src))
dualPoleFilter(float _src, float _lookback) =>
float _omega = -99 * math.pi / (70 * _lookback)
float _alpha = math.exp(_omega)
float _beta = -math.pow(_alpha, 2)
float _gamma = math.cos(_omega) * 2 * _alpha
float _delta = 1 - _gamma - _beta
float _slidingAvg = 0.5 * (_src + nz(_src[1], _src))
float _filter = na
_filter := (_delta*_slidingAvg) + _gamma*nz(_filter[1]) + _beta*nz(_filter[2])
_filter

getOscillator(float src, float smoothingFrequency, int quadraticMeanLength) =>

nDeriv = normalizeDeriv(src, quadraticMeanLength)
hyperbolicTangent = tanh(nDeriv)
result = dualPoleFilter(hyperbolicTangent, smoothingFrequency)

// =================================
// ==== Oscillator Calculations ====
// =================================

// Fast Oscillator + Mirror

offsetFast = offset
f_lookback = f_smoothing * oscillatorLookback
signalFast = getOscillator(src, f_lookback, quadraticMeanLength)
seriesFast = f_length*signalFast+offsetFast
seriesFastMirror = useMirror ? -seriesFast + 2*offsetFast : na

// Normal Oscillator + Mirror

offsetNormal = 0
n_lookback = n_smoothing * oscillatorLookback
signalNormal = getOscillator(src, n_lookback, quadraticMeanLength)
seriesNormal = n_length*signalNormal+offsetNormal
seriesNormalMirror = useMirror ? -seriesNormal + 2*offsetNormal : na

// Slow Oscillator + Mirror

offsetSlow = -offset
s_lookback = s_smoothing * oscillatorLookback
signalSlow = getOscillator(src, s_lookback, quadraticMeanLength)
seriesSlow = s_length*signalSlow+offsetSlow
seriesSlowMirror = useMirror ? -seriesSlow + 2*offsetSlow : na

// =====================================
// ==== Color Gradient Calculations ====
// =====================================

// Fast Color Gradients (Areas and Lines)

fastBaseColor = getPlotColor(signalFast, fastBullishColor, fastBearishColor)
fastBaseColorInverse = getPlotColor(signalFast, fastBearishColor, fastBullishColor)
fastAreaGradientFromSource = getColorGradientFromSource(seriesFast, -1.+offsetFast,
1+offsetFast, color.new(fastBaseColor, areaFastTrans), fastBaseColor)
fastAreaGradientFromSteps = getColorGradientFromSteps(seriesFast, offsetFast,
maxStepsForGradient, color.new(fastBaseColor, areaFastTrans), fastBaseColor)
fastLineGradientFromSource = getColorGradientFromSource(seriesFast, -1+offsetFast,
1+offsetFast, color.new(fastBaseColor, lineFastTrans), fastBaseColor)
fastLineGradientFromSteps = getColorGradientFromSteps(seriesFast, offsetFast,
maxStepsForGradient, color.new(fastBaseColor, lineFastTrans), fastBaseColor)
fastAreaGradientFromSourceInverse = getColorGradientFromSource(seriesFast, -
1.+offsetFast, 1+offsetFast, color.new(fastBaseColorInverse, areaFastTrans),
fastBaseColorInverse)
fastAreaGradientFromStepsInverse = getColorGradientFromSteps(seriesFast,
offsetFast, maxStepsForGradient, color.new(fastBaseColorInverse, areaFastTrans),
fastBaseColorInverse)

// Normal Color Gradients (Areas and Lines)

normalBaseColor = getPlotColor(signalNormal, normalBullishColor,
normalBearishColor)
normalBaseColorInverse = getPlotColor(signalNormal, normalBearishColor,
normalBullishColor)
normalAreaGradientFromSource = getColorGradientFromSource(seriesNormal, -
1.+offsetNormal, 1.+offsetNormal, color.new(normalBaseColor, areaNormalTrans),
normalBaseColor)
normalAreaGradientFromSteps = getColorGradientFromSteps(seriesNormal, offsetNormal,
maxStepsForGradient, color.new(normalBaseColor, areaNormalTrans), normalBaseColor)
normalLineGradientFromSource = getColorGradientFromSource(seriesNormal, -
1+offsetNormal, 1+offsetNormal, color.new(normalBaseColor, lineNormalTrans),
normalBaseColor)
normalLineGradientFromSteps = getColorGradientFromSteps(seriesNormal, offsetNormal,
maxStepsForGradient, color.new(normalBaseColor, lineNormalTrans), normalBaseColor)
normalAreaGradientFromSourceInverse = getColorGradientFromSource(seriesNormal, -
1.+offsetNormal, 1.+offsetNormal, color.new(normalBaseColorInverse,
areaNormalTrans), normalBaseColorInverse)
normalAreaGradientFromStepsInverse = getColorGradientFromSteps(seriesNormal,
offsetNormal, maxStepsForGradient, color.new(normalBaseColorInverse,
areaNormalTrans), normalBaseColorInverse)

// Slow Color Gradients (Areas and Lines)

slowBaseColor = getPlotColor(signalSlow, slowBullishColor, slowBearishColor)
slowBaseColorInverse = getPlotColor(signalSlow, slowBearishColor, slowBullishColor)
slowAreaGradientFromSource = getColorGradientFromSource(seriesSlow, -
1.75+offsetSlow, 1.75+offsetSlow, color.new(slowBaseColor, areaSlowTrans),
slowBaseColor)
slowAreaGradientFromSteps = getColorGradientFromSteps(seriesSlow, offsetSlow,
maxStepsForGradient, color.new(slowBaseColor, areaSlowTrans), slowBaseColor)
slowLineGradientFromSource = getColorGradientFromSource(seriesSlow, -
1.75+offsetSlow, 1.75+offsetSlow, color.new(slowBaseColor, lineSlowTrans),
slowBaseColor)
slowLineGradientFromSteps = getColorGradientFromSteps(seriesSlow, offsetSlow,
maxStepsForGradient, color.new(slowBaseColor, lineSlowTrans), slowBaseColor)
slowAreaGradientFromSourceInverse = getColorGradientFromSource(seriesSlow, -
1.75+offsetSlow, 1.75+offsetSlow, color.new(slowBaseColorInverse, areaSlowTrans),
slowBaseColorInverse)
slowAreaGradientFromStepsInverse = getColorGradientFromSteps(seriesSlow,
offsetSlow, maxStepsForGradient, color.new(slowBaseColorInverse, areaSlowTrans),
slowBaseColorInverse)

// =========================================
// ==== Plot Parameters and Logic Gates ====
// =========================================

// Speed Booleans
isSlow = speedToEmphasize == "Slow"
isNormal = speedToEmphasize == "Normal"
isFast = speedToEmphasize == "Fast"

// Series Colors
seriesSlowColor = showOsc or isSlow ? color.new(slowLineGradientFromSource,
lineSlowTrans) : na
seriesNormalColor = showOsc or isNormal ? color.new(normalLineGradientFromSource,
lineNormalTrans) : na
seriesFastColor = showOsc or isFast ? color.new(fastLineGradientFromSource,
lineFastTrans) : na
seriesSlowMirrorColor = useMirror ? seriesSlowColor : na
seriesNormalMirrorColor = useMirror ? seriesNormalColor : na
seriesFastMirrorColor = useMirror ? seriesFastColor : na

// Series Line Widths

seriesSlowWidth = isSlow ? emphasisWidth : 1
seriesNormalWidth = isNormal ? emphasisWidth : 1
seriesFastWidth = isFast ? emphasisWidth : 1
seriesSlowMirrorWidth = useMirror ? seriesSlowWidth : na
seriesNormalMirrorWidth = useMirror ? seriesNormalWidth : na
seriesFastMirrorWidth = useMirror ? seriesFastWidth : na

// Speed Related Switches

seriesEmphasis = switch
isFast => seriesFast
isNormal => seriesNormal
isSlow => seriesSlow
=> na
//
colorLineEmphasis = switch
isFast => fastLineGradientFromSource
isNormal => normalLineGradientFromSource
isSlow => slowLineGradientFromSource
=> na

colorAreaEmphasis = switch
isFast => fastAreaGradientFromSource
isNormal => normalAreaGradientFromSource
isSlow => slowAreaGradientFromSource
=> na

// Crossover Signals
bearishCross = ta.crossunder(seriesFast, seriesNormal) and seriesNormal > 0
bullishCross = ta.crossover(seriesFast, seriesNormal) and seriesNormal < 0
slowBearishMedianCross = ta.crossunder(seriesSlow, 0)
slowBullishMedianCross = ta.crossover(seriesSlow, 0)
normalBearishMedianCross = ta.crossunder(seriesNormal, 0)
normalBullishMedianCross = ta.crossover(seriesNormal, 0)
fastBearishMedianCross = ta.crossunder(seriesFast, 0)
fastBullishMedianCross = ta.crossover(seriesFast, 0)

// Last Crossover Values

lastBearishCrossValue = ta.valuewhen(condition=bearishCross, source=seriesNormal,
occurrence=1)
lastBullishCrossValue = ta.valuewhen(condition=bullishCross , source=seriesNormal,
occurrence=1)

// Trigger Wave Size Comparison

triggerWaveFactor = sizePercent/100
isSmallerBearishCross = bearishCross and seriesNormal < lastBearishCrossValue *
triggerWaveFactor
isSmallerBullishCross = bullishCross and seriesNormal > lastBullishCrossValue *
triggerWaveFactor

// ===========================
// ==== Kernel Estimators ====
// ===========================

// The following kernel estimators are based on the Gaussian Kernel.

// They are used for:

// (1) Confirming directional changes in the slow oscillator (i.e. a type of
trend filter)
// (2) Visualizing directional changes as a dynamic ribbon (i.e. an additional
oscillator that can crossover with the user specified oscillator of interest)
// (3) Visualizing transient directional changes while in the midst of a larger
uptrend or downtrend (i.e. via color changes on the ribbon)

// Gaussian Kernel with a lookback of 6 bars, starting on bar 6 of the chart

(medium fit)
yhat0 = kernels.gaussian(seriesEmphasis, 6, 6)

// Gaussian Kernel with a lookback of 3 bars, starting on bar 2 of the chart (tight
fit)
yhat1 = kernels.gaussian(seriesEmphasis, 3, 2)

// Trend Assessment based on the relative position of the medium fit kernel to the
slow oscillator
isBearishKernelTrend = yhat0 < seriesSlow
isBullishKernelTrend = yhat0 > seriesSlow

// Divergence Signals
isBearishDivZone = ta.barssince(bearishCross[1]) < divThreshold
isBullishDivZone = ta.barssince(bullishCross[1]) < divThreshold

// Crossover Detection
isBearishTriggerWave = isSmallerBearishCross and isBearishDivZone and
isBearishKernelTrend
isBullishTriggerWave = isSmallerBullishCross and isBullishDivZone and
isBullishKernelTrend

// =======================
// ==== Plots & Fills ====

var position = 0
length := atrLength

minMult = math.max(sensitivity-4, 1)
maxMult = math.min(sensitivity, 26)

if (autopilotMode == "Short Term")

minMult:=1
maxMult := 4
if (autopilotMode == 'Mid Term')
minMult := 5
maxMult := 10
if (autopilotMode == 'Long-Term')
minMult :=8
maxMult :=13

float step = .5
//Trigger error
if minMult > maxMult
runtime.error('Minimum factor is greater than maximum factor in the range')

float perfAlpha = 10
fromCluster = 'Best'

//Optimization
maxIter = 250
maxData = 2500

//Style
bearCss = color.red
bullCss = color.teal

amaBearCss = color.new(color.red, 50)

amaBullCss = color.new(color.teal, 50)

showGradient = true

//Dashboard
showDash = true
//dashboardLocation = input.string('Top Right', 'Location', options = ['Top
Right', 'Bottom Right', 'Bottom Left'], group = 'Dashboard')
textSize = 'Small'

//-----------------------------------------------------------------------------}
//UDT's
//-----------------------------------------------------------------------------{
type supertrend
float upper = hl2
float lower = hl2
float output
float perf = 0
float factor
int trend = 0

type vector
array<float> out

//-----------------------------------------------------------------------------}
//Supertrend
//-----------------------------------------------------------------------------{
var holder = array.new<supertrend>(0)
var factors = array.new<float>(0)

//Populate supertrend type array

if barstate.isfirst
for i = 0 to int((maxMult - minMult) / step)
factors.push(minMult + i * step)
holder.push(supertrend.new())

atr = ta.atr(length)

//Compute Supertrend for multiple factors

k = 0
for factor in factors
 get_spt = holder.get(k)

up = hl2 + atr * factor

dn = hl2 - atr * factor

get_spt.trend := close > get_spt.upper ? 1 : close < get_spt.lower ? 0 :

get_spt.trend
get_spt.upper := close[1] < get_spt.upper ? math.min(up, get_spt.upper) : up
get_spt.lower := close[1] > get_spt.lower ? math.max(dn, get_spt.lower) : dn

diff = nz(math.sign(close[1] - get_spt.output))

get_spt.perf += 2/(perfAlpha+1) * (nz(close - close[1]) * diff - get_spt.perf)
get_spt.output := get_spt.trend == 1 ? get_spt.lower : get_spt.upper
get_spt.factor := factor
k += 1

//-----------------------------------------------------------------------------}
//K-means clustering
//-----------------------------------------------------------------------------{
factor_array = array.new<float>(0)
data = array.new<float>(0)

//Populate data arrays

if last_bar_index - bar_index <= maxData
for element in holder
data.push(element.perf)
factor_array.push(element.factor)

//Intitalize centroids using quartiles

centroids = array.new<float>(0)
centroids.push(data.percentile_linear_interpolation(25))
centroids.push(data.percentile_linear_interpolation(50))
centroids.push(data.percentile_linear_interpolation(75))

//Intialize clusters
var array<vector> factors_clusters = na
var array<vector> perfclusters = na

if last_bar_index - bar_index <= maxData

for _ = 0 to maxIter
factors_clusters := array.from(vector.new(array.new<float>(0)),
vector.new(array.new<float>(0)), vector.new(array.new<float>(0)))
perfclusters := array.from(vector.new(array.new<float>(0)),
vector.new(array.new<float>(0)), vector.new(array.new<float>(0)))

//Assign value to cluster

i = 0
for value in data
dist = array.new<float>(0)
for centroid in centroids
dist.push(math.abs(value - centroid))

idx = dist.indexof(dist.min())
perfclusters.get(idx).out.push(value)
factors_clusters.get(idx).out.push(factor_array.get(i))
i += 1

//Update centroids
new_centroids = array.new<float>(0)
 for cluster_ in perfclusters
new_centroids.push(cluster_.out.avg())

//Test if centroid changed

if new_centroids.get(0) == centroids.get(0) and new_centroids.get(1) ==
centroids.get(1) and new_centroids.get(2) == centroids.get(2)
break

centroids := new_centroids

//-----------------------------------------------------------------------------}
//Signals and trailing stop
//-----------------------------------------------------------------------------{
//Get associated supertrend
var float target_factor = na
var float perf_idx = na
var float perf_ama = na

var from = switch fromCluster

'Best' => 2
'Average' => 1
'Worst' => 0

//Performance index denominator

den = ta.ema(math.abs(close - close[1]), int(perfAlpha))

if not na(perfclusters)
//Get average factors within target cluster
target_factor := nz(factors_clusters.get(from).out.avg(), target_factor)

//Get performance index of target cluster

perf_idx := math.max(nz(perfclusters.get(from).out.avg()), 0) / den

//Get new supertrend

var upper = hl2
var lower = hl2
var os = 0

up = hl2 + atr * target_factor

dn = hl2 - atr * target_factor
upper := close[1] < upper ? math.min(up, upper) : up
lower := close[1] > lower ? math.max(dn, lower) : dn
os := close > upper ? 1 : close < lower ? 0 : os
ts = os ? lower : upper

//Get trailing stop adaptive MA

if na(ts[1]) and not na(ts)
perf_ama := ts
else
perf_ama += perf_idx * (ts - perf_ama)

//-----------------------------------------------------------------------------}
//Dashboard
//-----------------------------------------------------------------------------{

//-----------------------------------------------------------------------------{
css = os ? bullCss : bearCss

plot(showTrailingStoploss ? ts : na, 'Trailing Stop', os != os[1] ? na : css,

editable = false)

plot(showMovingAverage? perf_ama:na, 'Trailing Stop AMA',

ta.cross(close, perf_ama) ? na
: close > perf_ama ? amaBullCss : amaBearCss, editable = false)

//Candle coloring
//barcolor(showGradient ? color.from_gradient(perf_idx, 0, 1, color.new(css, 80),
css) : na)

//Signals

if showSignals
if os > os[1] and (signalPresets != "Smart Trail [Filter]" or
smartTrailDirection == 'long') and (signalPresets != "Trend Tracer [Filter]" or
trendTracerDirection==#02ff65) and (signalPresets != "Trend Strength [Filter]" or
trendStrengthMetric >= 25) and (signalPresets != "Trend Catcher [Filter]" or
newTrendCatcherColor == #02ff65) and (signalPresets != "Neo Cloud [Filter]" or
int(lastNeo) >= last5Neo)
int signalStrength = int(perf_idx*10) < 2 ? 1 : int(perf_idx*10) < 4 ? 2 :
int(perf_idx*10) < 5 ? 3 : 4
label.new(n, low-ta.atr(30)/2, signalClassifier ?
str.tostring(signalStrength) : ema50 > ema200 ? "▲+" : "▲"
, color = bullCss
, style = label.style_label_up
, textcolor = color.white
, yloc=yloc.belowbar
, size = size.small)
position := 1

if os < os[1] and (signalPresets != "Smart Trail [Filter]" or

smartTrailDirection == 'short') and (signalPresets != "Trend Tracer [Filter]" or
trendTracerDirection!=#02ff65) and (signalPresets != "Trend Strength [Filter]" or
trendStrengthMetric >= 25)and (signalPresets != "Trend Catcher [Filter]" or
newTrendCatcherColor != #02ff65) and (signalPresets != "Neo Cloud [Filter]" or
int(lastNeo) <=last5Neo)
int signalStrength = int(perf_idx*10) < 2 ? 1 : int(perf_idx*10) < 4 ? 2 :
int(perf_idx*10) < 5 ? 3 : 4
label.new(n, high+ta.atr(30)/2, signalClassifier ?
str.tostring(signalStrength) : ema50 < ema200 ? "▼+" : "▼"
, color = bearCss
, style = label.style_label_down
, textcolor = color.white
, yloc=yloc.abovebar
, size = size.small)
position := -1

// =======================

// Signal Plots
//plot(position == 1 and bearishCross ? high+5 : na, title="Bearish Cross",
style=plot.style_cross, linewidth=2, color=c_bearish, offset=-1)
//plot(position == -1 and bearishCross ? high+5 : na, title="Bearish Cross",
style=plot.style_circles, linewidth=2, color=c_bearish, offset=-1)
//plot(position == 1 and isBearishTriggerWave ? high+5 : na, title="Bearish Trigger
Cross", style=plot.style_cross, linewidth=3, color=c_bearish, offset=-1)
//plot(position == -1 and isBearishTriggerWave ? high+5 : na, title="Bearish
Trigger Cross", style=plot.style_circles, linewidth=3, color=c_bearish, offset=-1)
//plotchar(bearishCross and position == 1, "Long", "✖", location.abovebar, color =
#4774f5, size = size.tiny, editable = false)
//plotchar(bearishCross and position == -1, "Long", "▼", location.abovebar, color =
c_bearish, size = size.tiny)
plotchar(isBearishTriggerWave and position == 1, "Long", "✖", location.abovebar,
color=#4774f5, size = size.tiny, editable = false)
//plotchar(isBearishTriggerWave and position == -1, "Long", "▼", location.abovebar,
color=c_bearish, size = size.small)

//plot(position == 1 and bullishCross ? low -5: na, title="Bullish Cross", style=

plot.style_circles, linewidth=2, color=c_bullish, offset=-1)
//plot(position == -1 and bullishCross ? low -5: na, title="Bullish Cross", style=
plot.style_cross, linewidth=2, color=c_bullish, offset=-1)
//plot(position == 1 and isBullishTriggerWave ? low -5 : na, title="Bullish Trigger
Cross", style=plot.style_circles, linewidth=3, color=c_bullish, offset=-1)
//plot(position == -1 and isBullishTriggerWave ? low -5 : na, title="Bullish
Trigger Cross", style=plot.style_cross, linewidth=3, color=c_bullish, offset=-1)

//plotchar(bullishCross and position == 1, "Long", "▲", location.belowbar, color =

c_bullish, size = size.tiny)
//plotchar(bullishCross and position == -1, "Long", "✖", location.belowbar, color =
#ff7322, size = size.tiny, editable = false)
//plotchar(isBullishTriggerWave and position == 1, "Long", "▲", location.belowbar,
color=c_bullish, size = size.small)
plotchar(isBullishTriggerWave and position == -1, "Long", "✖", location.belowbar,
color=#ff7322, size = size.tiny, editable = false)

// Shit
atrMultiplier = input(2, title="ATR Multiplier")
boxHeightInAtr = atrMultiplier * ta.atr(10)

// Box TP 1

[lowb, midb, highb] = LAF.getTPSLBoxes(6.0)

if (takeProfitBoxes == 'On')
tp1box = box.new(left=bar_index + 1, top=close + midb, right=bar_index + 18,
bottom=close + lowb, border_color=color.new(#3666f5, 0), border_width=2,
border_style=line.style_solid, bgcolor=color.new(#3666f5, 55), text="TP/SL 1 : "
+ str.tostring(close), text_size=size.normal, text_color=color.new(#3666f5, 0))
bottom_tp1 = box.get_bottom(tp1box)
box.delete(tp1box[1])

// Box TP 2
tp2box = box.new(left=bar_index + 1, top=close+highb, right=bar_index + 18,
bottom=close+midb, border_color=color.new(#3666f5, 0), border_width=2,
border_style=line.style_solid, bgcolor=color.new(#3666f5, 65), text="TP/SL 2 : "
+ str.tostring(close), text_size=size.normal, text_color=color.new(#3666f5, 0))
top_tp2 = box.get_top(tp2box)
box.delete(tp2box[1])
// Empty Box
newBox = box.new(left=bar_index + 18, top=top_tp2, right=bar_index + 200,
bottom=bottom_tp1, border_color=color.new(#3666f5, 0), border_width=2,
border_style=line.style_solid, bgcolor=color.new(#3666f5, 50), text=" ",
text_size=size.normal, text_color=color.new(#3666f5, 0))
box.delete(newBox[1])
 // SL Box
slBox = box.new(left=bar_index + 3, top=close-lowb, right=bar_index + 18,
bottom=close-midb, border_color=color.new(color.red, 0), border_width=2,
border_style=line.style_solid, bgcolor=color.new(color.red, 66), text="TP/SL 2 :
" + str.tostring(close), text_size=size.normal, text_color=color.new(color.red, 0))
bottom_sl = box.get_top(slBox)
box.delete(slBox[1])

// SL2 Box
sl2Box = box.new(left=bar_index + 3, top=close-midb, right=bar_index + 18,
bottom=close-highb, border_color=color.new(color.red, 0), border_width=2,
border_style=line.style_solid, bgcolor=color.new(color.red, 65), text="TP/SL 1 :
" + str.tostring(close), text_size=size.normal, text_color=color.new(color.red, 0))
bottom_sl2 = box.get_bottom(sl2Box)
box.delete(sl2Box[1])

// Empty Box SL
Slboxem = box.new(left=bar_index + 18, top=bottom_sl, right=bar_index + 200,
bottom=bottom_sl2, border_color=color.new(color.red, 0), border_width=2,
border_style=line.style_solid, bgcolor=color.new(color.red, 50), text=" ",
text_size=size.normal, text_color=color.new(color.red, 0))
box.delete(Slboxem[1])
//
// Line tp Bottom
var line tpb = na
isLastBar = barstate.islast

if (isLastBar)
tpb := line.new(na, bottom_tp1, na, bottom_tp1, color=color.new(#3666f5,
0), width=2, style=line.style_dashed)

line.set_xy1(tpb, bar_index[50], bottom_tp1)

line.set_xy2(tpb, bar_index + 200, bottom_tp1)
line.delete(tpb[1])
// Line tp top
var line tp2Line = na

if (isLastBar)
tp2Line := line.new(na, top_tp2, na, top_tp2, color=color.new(#3666f5, 0),
width=2, style=line.style_dashed)

line.set_xy1(tp2Line, bar_index[50], top_tp2)

line.set_xy2(tp2Line, bar_index + 200, top_tp2)
line.delete(tp2Line[1])

// Line SL
var line slLine = na

if (isLastBar)
slLine := line.new(na, bottom_sl, na, bottom_sl, color=color.new(color.red,
0), width=2, style=line.style_dashed)

line.set_xy1(slLine, bar_index[50], bottom_sl)

line.set_xy2(slLine, bar_index + 400, bottom_sl)
line.delete(slLine[1])
// Line SL2
var line sl2Line = na

if (isLastBar)
 sl2Line := line.new(na, bottom_sl2, na, bottom_sl2,
color=color.new(color.red, 0), width=2, style=line.style_dashed)

line.set_xy1(sl2Line, bar_index[50], bottom_sl2)

line.set_xy2(sl2Line, bar_index + 200, bottom_sl2)
line.delete(sl2Line[1])

###################################################################################
###################################################################################
##################################################

//TELEGRAM ==> https://t.me/+UAk3hqvoD89jZTlk

//@version=5

//text inputs
textVPosition = 'middle'
textHPosition = 'center'
symVPosition = 'top'
symHPosition = 'left'
width = 0
height = 0
c_title = #b2b5be80
s_title = 'large'
a_title = 'center'
c_subtitle = #b2b5be80
s_subtitle = 'normal'
a_subtitle = 'center'
c_bg = color.new(color.blue, 100)

indicator("LUXALGO | Signals & Overlays", "[LUXALGO] Signals & Overlays™ [2.2]",

overlay = true, max_labels_count = 500)

//Import libraries
//Import libraries
import ayvaliktrading/EyopsTelegram/1 as LAF
import ayvaliktrading/JoinUsEyopsTelegram/1 as kernels

// # ============================[GET USERS INPUT]============================ #

groupBasic = "BASIC SETTINGS"
showSignals = input(true, "Show Signals", inline = "1", group = groupBasic, tooltip
= "Enables or disables the signals")
signalPresets = input.string("None", "Presets / Filters", ["None", "Trend Trader
[Preset]","Scalper [Preset]", "Swing Trader [Preset]", "Contrarian Trader
[Preset]", "Smart Trail [Filter]", "Trend Tracer [Filter]", "Trend Strength
[Filter]", "Trend Catcher [Filter]", "Neo Cloud [Filter]"],tooltip = "Automatically
sets settings or filters for a given category", group= groupBasic)
signalMode = input.string("Confirmation + Exits", "Signal Mode", ["Confirmation +
Exits", "Contrarian + Exits", "None"],tooltip = "Changes the Mode of the
signals" ,group = groupBasic)
signalClassifier = input(true,"AI Signal Classifer",tooltip = "Shows signal quality
from 1-4 on signals" ,group = groupBasic)
sensitivity = input.float(5, "Signal Sensitivity ", minval = 1, maxval =
26,step=1, tooltip = "Changes the sensetivity of the signals, the lower this
setting the more short term signals you will get, while a higher number will result
in longer term signals.",group = groupBasic)
atrLength = input.int(10, "Signal Tuner ", minval = 1, maxval = 25,step=1,tooltip
= "Alows you to tune your signals, the higher the number the more refined but
laggier the signal" ,group = groupBasic)
candleColorType = input.string("Confirmation Simple", "Candle Coloring",
["Confirmation Simple","Confirmation Gradient","Contrarian
Gradient","None"],tooltip = "Changes the type of signal coloring", group =
groupBasic)

// Indicator Overlay Settings

groupOverlay = "INDICATOR OVERLAY"
smartTrail = input(true, "Smart Trail", inline = "1", group = groupOverlay)
trendCatcher = input(false, "Trend Catcher", inline = "2", group = groupOverlay)
neoCloud = input(false, "Neo Cloud", inline = "3", group = groupOverlay)
reversalZone = input(true, "Reversal Zones", inline = "1", group = groupOverlay)
trendTracer = input(false, "Trend Tracer", inline = "2", group = groupOverlay)
showDashboard = input(true, "Dashboard", inline = "3", group = groupOverlay)
showTrailingStoploss = input(false, "Trailing Stoploss", inline = "4", group =
groupOverlay)
showMovingAverage = input(false, "AI Moving Average", inline = "4", group =
groupOverlay)
showSessions = input(false, "Sessions", inline = "5", group = groupOverlay)

// Advanced Settings
groupAdvanced = "ADVANCED SETTINGS"
takeProfitBoxes = input.string("Off", "TP/SL Points", options=["Off","On"], inline
= "2", tooltip = "Shows Take Profit and Stop Loss areas",group = groupAdvanced)
takeProfitStopLossDistance = input.int(5,"", minval = 1, maxval = 10, inline = "2",
group=groupAdvanced)
autopilotMode = input.string("Off", "Autopilot Sensivity",["Off","Short-Term",
"Mid-Term", "Long-Term"],tooltip = "Sets automatic settings for signals and
improves their quality" ,inline = "3", group = groupAdvanced)
dashboardLocation = input.string("Bottom Right","Dashboard Location", ["Top
Right","Bottom Right","Bottom Left"], inline = "4",tooltip = "Changes dashboard
positions" ,group = groupAdvanced)
dashboardSize = input.string("Normal","Dashboard Size",
["Tiny","Small","Normal","Large"], inline = "5",tooltip = "Changes the size of the
dashboard" ,group = groupAdvanced)

if (signalPresets == "Trend Trader [Preset]")

smartTrail := true
trendCatcher := true
neoCloud := true
trendTracer := true
smartTrail := true
if (signalPresets == "Scalper [Preset]")
sensitivity := 4
smartTrail := true
trendTracer := true
candleColorType := "Confirmation Gradient"
if (signalPresets == "Swing Trader [Preset]")
sensitivity := 18
neoCloud := true
candleColorType := "Confirmation Simple"
if (signalPresets == "Contrarian Trader [Preset]")
reversalZone := true
smartTrail := true
candleColorType := "Contrarian Gradient"
n = bar_index

// # ============================[BUY/SELL SIGNALS]============================ #
//------------------------------------------------------------------------------
//Settings
//-----------------------------------------------------------------------------{
//-----------------------------------------------------------------------------}

// # ============================[SESSIONS]============================ #
show_sesa = true
sesa_txt = 'New York'
sesa_ses = '1300-2200'
sesa_css = #ff5d00

sesa_range = true
sesa_tl = false
sesa_avg = false
sesa_vwap = false
sesa_maxmin = false

//Session B
show_sesb = true
sesb_txt = 'London'
sesb_ses = '0700-1600'
sesb_css = #2157f3

sesb_range = true
sesb_tl = false
sesb_avg = false
sesb_vwap = false
sesb_maxmin = false

//Timezones
tz_incr = 0
use_exchange = false

//Ranges Options
bg_transp = 90
show_outline = true
show_txt = true

//Dashboard
show_ses_div = false
show_day_div = false

//-----------------------------------------------------------------------------}
//Functions
//-----------------------------------------------------------------------------{

//Get session average

get_avg(session)=>
var len = 1
var float csma = na
 var float sma = na

if session > session[1]

len := 1
csma := close

if session and session == session[1] and textVPosition == 'middle' and

textHPosition == 'center' and c_title == #b2b5be80 and s_title == 'large' and
a_title == 'center' and c_subtitle == #b2b5be80 and s_subtitle == 'normal' and
a_subtitle == 'center'
len += 1
csma += close
sma := csma / len

sma

//Get trendline coordinates

get_linreg(session)=>
var len = 1
var float cwma = na
var float csma = na
var float csma2 = na

var float y1 = na
var float y2 = na
var float stdev = na
var float r2 = na

if session > session[1]

len := 1
cwma := close
csma := close
csma2 := close * close

if session and session == session[1] and textVPosition == 'middle' and

textHPosition == 'center' and c_title == #b2b5be80 and s_title == 'large' and
a_title == 'center' and c_subtitle == #b2b5be80 and s_subtitle == 'normal' and
a_subtitle == 'center'
len += 1
csma += close
csma2 += close * close
cwma += close * len

sma = csma / len

wma = cwma / (len * (len + 1) / 2)

cov = (wma - sma) * (len+1)/2

stdev := math.sqrt(csma2 / len - sma * sma)
r2 := cov / (stdev * (math.sqrt(len*len - 1) / (2 * math.sqrt(3))))

y1 := 4 * sma - 3 * wma
y2 := 3 * wma - 2 * sma

[y1 , y2, stdev, r2]

//Session Vwap
get_vwap(session) =>
var float num = na
var float den = na
 if session > session[1] and textVPosition == 'middle' and textHPosition ==
'center' and c_title == #b2b5be80 and s_title == 'large' and a_title == 'center'
and c_subtitle == #b2b5be80 and s_subtitle == 'normal' and a_subtitle == 'center'
num := close * volume
den := volume

else if session and session == session[1] and textVPosition == 'middle' and

textHPosition == 'center' and c_title == #b2b5be80 and s_title == 'large' and
a_title == 'center' and c_subtitle == #b2b5be80 and s_subtitle == 'normal' and
a_subtitle == 'center'
num += close * volume
den += volume
else
num := na

[num, den]

//Set line
set_line(session, y1, y2, session_css)=>
var line tl = na

if session > session[1] and textVPosition == 'middle' and textHPosition ==

'center' and c_title == #b2b5be80 and s_title == 'large' and a_title == 'center'
and c_subtitle == #b2b5be80 and s_subtitle == 'normal' and a_subtitle == 'center'
tl := line.new(n, close, n, close, color = session_css)

if session and session == session[1] and textVPosition == 'middle' and

textHPosition == 'center' and c_title == #b2b5be80 and s_title == 'large' and
a_title == 'center' and c_subtitle == #b2b5be80 and s_subtitle == 'normal' and
a_subtitle == 'center'
line.set_y1(tl, y1)
line.set_xy2(tl, n, y2)

//Set session range

get_range(session, session_name, session_css)=>
var t = 0
var max = high
var min = low
var box bx = na
var label lbl = na

if session > session[1] and showSessions and textVPosition == 'middle' and

textHPosition == 'center' and c_title == #b2b5be80 and s_title == 'large' and
a_title == 'center' and c_subtitle == #b2b5be80 and s_subtitle == 'normal' and
a_subtitle == 'center'
t := time
max := high
min := low

bx := box.new(n, max, n, min

, bgcolor = color.new(session_css, bg_transp)
, border_color = show_outline ? session_css : na
, border_style = line.style_dotted)

if show_txt and showSessions and textVPosition == 'middle' and

textHPosition == 'center' and c_title == #b2b5be80 and s_title == 'large' and
a_title == 'center' and c_subtitle == #b2b5be80 and s_subtitle == 'normal' and
a_subtitle == 'center'
 lbl := label.new(t, max, session_name
, xloc = xloc.bar_time
, textcolor = session_css
, style = label.style_label_down
, color = color.new(color.white, 100)
, size = size.tiny)

if session and session == session[1] and showSessions and textVPosition ==

'middle' and textHPosition == 'center' and c_title == #b2b5be80 and s_title ==
'large' and a_title == 'center' and c_subtitle == #b2b5be80 and s_subtitle ==
'normal' and a_subtitle == 'center'
max := math.max(high, max)
min := math.min(low, min)

box.set_top(bx, max)
box.set_rightbottom(bx, n, min)

if show_txt
label.set_xy(lbl, int(math.avg(t, time)), max)

[session ? na : max, session ? na : min]

//-----------------------------------------------------------------------------}
//Sessions
//-----------------------------------------------------------------------------{
tf = timeframe.period

var tz = use_exchange ? syminfo.timezone :

str.format('UTC{0}{1}', tz_incr >= 0 ? '+' : '-', math.abs(tz_incr))

is_sesa = math.sign(nz(time(tf, sesa_ses, tz)))

is_sesb = math.sign(nz(time(tf, sesb_ses, tz)))

//-----------------------------------------------------------------------------}
//Dashboard
//-----------------------------------------------------------------------------{

var float max_sesa = na

var float min_sesa = na
var float max_sesb = na
var float min_sesb = na
var float max_sesc = na
var float min_sesc = na
var float max_sesd = na
var float min_sesd = na

//Ranges
if show_sesa and sesa_range and textVPosition == 'middle' and textHPosition ==
'center' and c_title == #b2b5be80 and s_title == 'large' and a_title == 'center'
and c_subtitle == #b2b5be80 and s_subtitle == 'normal' and a_subtitle == 'center'
[max, min] = get_range(is_sesa, sesa_txt, sesa_css)
max_sesa := max
min_sesa := min

if show_sesb and sesb_range and textVPosition == 'middle' and textHPosition ==

'center' and c_title == #b2b5be80 and s_title == 'large' and a_title == 'center'
and c_subtitle == #b2b5be80 and s_subtitle == 'normal' and a_subtitle == 'center'
[max, min] = get_range(is_sesb, sesb_txt, sesb_css)
max_sesb := max
 min_sesb := min

//Trendlines
//Mean
if show_sesa and sesa_avg and textVPosition == 'middle' and textHPosition ==
'center' and c_title == #b2b5be80 and s_title == 'large' and a_title == 'center'
and c_subtitle == #b2b5be80 and s_subtitle == 'normal' and a_subtitle == 'center'
avg = get_avg(is_sesa)
set_line(is_sesa, avg, avg, sesa_css)

if show_sesb and sesb_avg and textVPosition == 'middle' and textHPosition ==

'center' and c_title == #b2b5be80 and s_title == 'large' and a_title == 'center'
and c_subtitle == #b2b5be80 and s_subtitle == 'normal' and a_subtitle == 'center'
avg = get_avg(is_sesb)
set_line(is_sesb, avg, avg, sesb_css)

//VWAP
//-----------------------------------------------------------------------------}
//Plots
//-----------------------------------------------------------------------------{
//Plot max/min
plot(showSessions and sesa_maxmin and textVPosition == 'middle' and textHPosition
== 'center' and c_title == #b2b5be80 and s_title == 'large' and a_title == 'center'
and c_subtitle == #b2b5be80 and s_subtitle == 'normal' and a_subtitle == 'center' ?
max_sesa : na, 'Session A Maximum', sesa_css, 1, plot.style_linebr, editable =
false)
plot(showSessions and sesa_maxmin and textVPosition == 'middle' and textHPosition
== 'center' and c_title == #b2b5be80 and s_title == 'large' and a_title == 'center'
and c_subtitle == #b2b5be80 and s_subtitle == 'normal' and a_subtitle == 'center' ?
min_sesa : na, 'Session A Minimum', sesa_css, 1, plot.style_linebr, editable =
false)

plot(showSessions and sesb_maxmin and textVPosition == 'middle' and textHPosition

== 'center' and c_title == #b2b5be80 and s_title == 'large' and a_title == 'center'
and c_subtitle == #b2b5be80 and s_subtitle == 'normal' and a_subtitle == 'center' ?
max_sesb : na, 'Session B Maximum', sesb_css, 1, plot.style_linebr, editable =
false)
plot(showSessions and sesb_maxmin and textVPosition == 'middle' and textHPosition
== 'center' and c_title == #b2b5be80 and s_title == 'large' and a_title == 'center'
and c_subtitle == #b2b5be80 and s_subtitle == 'normal' and a_subtitle == 'center' ?
min_sesb : na, 'Session B Minimum', sesb_css, 1, plot.style_linebr, editable =
false)

//Plot Divider A
plotshape(is_sesa and show_ses_div and show_sesa and showSessions, "·"
, shape.square
, location.bottom
, na
, text = "."
, textcolor = sesa_css
, size = size.tiny
, display = display.all - display.status_line
, editable = false)

plotshape(is_sesa != is_sesa[1] and show_ses_div and show_sesa and showSessions,

"NYE"
, shape.labelup
, location.bottom
, na
 , text = "❚"
, textcolor = sesa_css
, size = size.tiny
, display = display.all - display.status_line
, editable = false)

//Plot Divider B
plotshape(is_sesb and show_ses_div and show_sesb and showSessions, "·"
, shape.labelup
, location.bottom
, na
, text = "."
, textcolor = sesb_css
, size = size.tiny
, display = display.all - display.status_line
, editable = false)

plotshape(is_sesb != is_sesb[1] and show_ses_div and show_sesb and showSessions,

"LDN"
, shape.labelup
, location.bottom
, na
, text = "❚"
, textcolor = sesb_css
, size = size.tiny
, display = display.all - display.status_line
, editable = false)

// # ============================[FUNCTIONS]============================ #

type bar
float o = open
float h = high
float l = low
float c = close
float v = volume
int i = bar_index

bar b = bar.new()
nzV = nz(b.v)

f_calcV() =>
uV = 0.0
dV = 0.0

switch
(b.c - b.l) > (b.h - b.c) => uV := nzV
(b.c - b.l) < (b.h - b.c) => dV := -nzV
b.c > b.o => uV := nzV
b.c < b.o => dV := -nzV
b.c > nz(b.c[1]) => uV := nzV
b.c < nz(b.c[1]) => dV := -nzV
nz(uV[1]) > 0 => uV := uV + nzV
nz(dV[1]) < 0 => dV := dV - nzV

[uV, dV]
// # ============================[CONSTANT VARIABLES]============================ #
sma4 = ta.sma(close, 4)
sma5 = ta.sma(close, 5)
sma9 = ta.sma(close, 9)
ema50 = ta.ema(close, 50)
ema200 = ta.ema(close, 200)

bullishSignalColor = #59e08a
bearishSignalColor = #ff5959

dashboardRedText = #ee787d
dashboardGreenText = #42bda8
dashboardGreenBackground = #284444
dashboardRedBackground = #49343e

// # ============================[CANDLE COLORING]============================ #
macdFastLength = 12
macdSlowLength = 26
macdSignalLength = 9

if (candleColorType != 'Confirmation Simple')

macdFastLength := 10
macdSlowLength := 25
macdSignalLength:=8

[MacdX, signalX, histX] = ta.macd(close, macdFastLength, macdSlowLength,

macdSignalLength)

//candle color scheme

greenHigh = #4ce653
greenMidHigh =#4ce653
greenMidLow =#4ce653
greenLow = #56328f

// Yellow
yellowLow = #56328f

// 4 level of red
redHigh = #ff0000
redMidHigh = #ff0000
redMidLow = #ff0000
redLow = #56328f

if (candleColorType == 'Confirmation Gradient')

greenHigh := #01d70c
greenMidHigh := #269444
greenMidLow :=#4f966c
greenLow := #425970

// Yellow
yellowLow := #513a88

// 4 level of red
redHigh := #ff0000
redMidHigh := #c21637
redMidLow := #c33252
 redLow := #8e215f
if (candleColorType == 'Contrarian Gradient')
redHigh := #01d70c
redMidHigh := #269444
redMidLow :=#4f966c
redLow := #425970

// Yellow
yellowLow := #513a88

// 4 level of red
greenHigh := #ff0000
greenMidHigh := #c21637
greenMidLow := #c33252
greenLow := #8e215f

// Default color
candleBody = yellowLow

if histX > 0
if histX > histX[1] and histX[1] > 0 and textVPosition == 'middle' and
textHPosition == 'center' and c_title == #b2b5be80 and s_title == 'large' and
a_title == 'center' and c_subtitle == #b2b5be80 and s_subtitle == 'normal' and
a_subtitle == 'center'
candleBody := greenLow

if histX < 0
if histX < histX[1] and histX[1] < 0 and textVPosition == 'middle' and
textHPosition == 'center' and c_title == #b2b5be80 and s_title == 'large' and
a_title == 'center' and c_subtitle == #b2b5be80 and s_subtitle == 'normal' and
a_subtitle == 'center'
candleBody := redLow

// Bullish trend
if MacdX > 0 and histX > 0
candleBody := greenMidLow

if histX > histX[1] and MacdX[1] > 0 and histX[1] > 0 and textVPosition ==
'middle' and textHPosition == 'center' and c_title == #b2b5be80 and s_title ==
'large' and a_title == 'center' and c_subtitle == #b2b5be80 and s_subtitle ==
'normal' and a_subtitle == 'center'
candleBody := greenMidHigh

if histX > histX[2] and MacdX[2] > 0 and histX[2] > 0 and textVPosition ==
'middle' and textHPosition == 'center' and c_title == #b2b5be80 and s_title ==
'large' and a_title == 'center' and c_subtitle == #b2b5be80 and s_subtitle ==
'normal' and a_subtitle == 'center'
candleBody := greenHigh

// Bearish trend
if MacdX < 0 and histX < 0
candleBody := redMidLow

if histX < histX[1] and MacdX[1] < 0 and histX[1] < 0 and textVPosition ==
'middle' and textHPosition == 'center' and c_title == #b2b5be80 and s_title ==
'large' and a_title == 'center' and c_subtitle == #b2b5be80 and s_subtitle ==
'normal' and a_subtitle == 'center'
candleBody := redMidHigh
 if histX < histX[2] and MacdX[2] < 0 and histX[2] < 0 and textVPosition ==
'middle' and textHPosition == 'center' and c_title == #b2b5be80 and s_title ==
'large' and a_title == 'center' and c_subtitle == #b2b5be80 and s_subtitle ==
'normal' and a_subtitle == 'center'
candleBody := redHigh

barcolor(candleColorType == 'None' ? na : candleBody, editable = false)

// # ============================[SMART TRAIL]============================ #
[smartTrailLine, fillerLine, smartTrailDirection] = LAF.getSmartTrail(10, 4, 8)
smartTrail1 = plot(smartTrail and textVPosition == 'middle' and textHPosition ==
'center' and c_title == #b2b5be80 and s_title == 'large' and a_title == 'center'
and c_subtitle == #b2b5be80 and s_subtitle == 'normal' and a_subtitle == 'center' ?
smartTrailLine : na, "Smart Trail", style = plot.style_line, color =
smartTrailDirection== 'long' ? color.new(#2157f9, 0) : smartTrailDirection ==
'short' ? color.new(#ff1100, 0) : na, editable = false)
smartTrail2 = plot(smartTrail and textVPosition == 'middle' and textHPosition ==
'center' and c_title == #b2b5be80 and s_title == 'large' and a_title == 'center'
and c_subtitle == #b2b5be80 and s_subtitle == 'normal' and a_subtitle == 'center' ?
fillerLine : na, "Fib 2", style = plot.style_line, transp = 100, editable = false)
fill(smartTrail1, smartTrail2, color = smartTrailDirection == 'long' ?
color.new(#2157f9, 80) : smartTrailDirection == 'short' ? color.new(#ff1100, 80) :
na, editable = false)

// # ============================[TREND CATCHER]============================ #
[trendCatcherLine, trendCatcherColor] = LAF.getTrendCatcher()
newTrendCatcherColor = trendCatcherColor == color.blue ? #02ff65 : #ff1100
plot(trendCatcher and textVPosition == 'middle' and textHPosition == 'center' and
c_title == #b2b5be80 and s_title == 'large' and a_title == 'center' and c_subtitle
== #b2b5be80 and s_subtitle == 'normal' and a_subtitle == 'center' ?
trendCatcherLine : na, title='Trend Catcher', linewidth=2,
color=newTrendCatcherColor, editable = false)

// # ============================[NEO CLOUD]============================ #

// # ============================[REVERSAL ZONES]============================ #

// # ============================[TREND TRACER]============================ #
[trendTracerLine, trendTracerDirection] = LAF.getTrendTracer()
plot(trendTracer and textVPosition == 'middle' and textHPosition == 'center' and
c_title == #b2b5be80 and s_title == 'large' and a_title == 'center' and c_subtitle
== #b2b5be80 and s_subtitle == 'normal' and a_subtitle == 'center' ?
trendTracerLine : na, title='Trend Tracer', linewidth=2, style=plot.style_cross,
color = trendTracerDirection, editable = false)

// # ============================[DASHBOARD
COMPONENTS|]============================ #

trendStrengthMetric = math.abs(LAF.getTrendStrengthMetric(14, 'RMA', 21, 'EMA'))

trendStrengthMetric := trendStrengthMetric*2.5
trendIndication = trendStrengthMetric > 30 and textVPosition == 'middle' and
textHPosition == 'center' and c_title == #b2b5be80 and s_title == 'large' and
a_title == 'center' and c_subtitle == #b2b5be80 and s_subtitle == 'normal' and
❄️
a_subtitle == 'center' ? "" : " "
trendStrengthCellColor = newTrendCatcherColor == #02ff65 ? dashboardGreenBackground
: dashboardRedBackground
trendStrengthTextColor = trendStrengthCellColor == dashboardGreenBackground ?
dashboardGreenText : dashboardRedText
volatilityMetric = LAF.getVolatilityMetric()
volatilityMetric2 = ta.sma(LAF.getVolatilityMetric(), 8)
volatilityText = volatilityMetric < 30 ? 'Stable' : volatilityMetric < 80 ?
'Moderate' : 'Volatile'
volatilityEmoji = volatilityMetric2 > volatilityMetric ? '📉' : '📈'
volatilityCellColor = newTrendCatcherColor == #02ff65 ? dashboardGreenBackground :
dashboardRedBackground
VolatilityTextColor = trendStrengthCellColor == dashboardGreenBackground ?
dashboardGreenText : dashboardRedText

squeezeMetric = LAF.getSqueezeMetric(45, 20)

squeezeIsHigh = squeezeMetric >= 80 ? true : false
squeezeCellColor = trendTracerDirection == #02ff65 ? #1a3a3e : #482632
squeezeTextColor = trendTracerDirection != #02ff65 ? #ed3544 : #0a907a
// and textVPosition == 'middle' and textHPosition == 'center' and c_title ==
#b2b5be80 and s_title == 'large' and a_title == 'center' and c_subtitle ==
#b2b5be80 and s_subtitle == 'normal' and a_subtitle == 'center'
//
[uV, dV] = f_calcV()

totalVolume = uV + math.abs(dV)
//volumecolor = totalVolume >= 50 ? bullish : bearish
volumeCellColor = dashboardRedBackground
volumeTextColor = totalVolume >= 50 ? dashboardGreenText : dashboardRedText
if (totalVolume >= 50)
totalVolume := totalVolume*2
volumeCellColor := dashboardGreenBackground
else
totalVolume := totalVolume*-2

volumeSentiment = totalVolume

table_position = dashboardLocation == 'Bottom Left' ? position.bottom_left

: dashboardLocation == 'Top Right' ? position.top_right
: position.bottom_right

table_size = dashboardSize == 'Tiny' ? size.tiny

: dashboardSize == 'Small' ? size.small
: size.normal

tb = table.new(table_position, 7, 7
, bgcolor = #1e222d
, border_color = #373a46
, border_width = 1
, frame_color = #373a46
, frame_width = 1)

if showDashboard
if barstate.islast
tb.cell(0, 2, autopilotMode == 'Off' ? "✈️
Optimal Sensivity" : " Autopilot
Enabled", text_color = color.white, text_size = table_size, text_halign =
text.align_left)
tb.cell(0, 3, str.tostring(trendIndication) + "Trend Strength", text_color
= color.white, text_size = table_size, text_halign = text.align_left)
tb.cell(0, 4, volatilityEmoji+ " Lux Volatility", text_color = color.white,
text_size = table_size, text_halign = text.align_left)
tb.cell(0, 5, "🔃 Squeeze", text_color = color.white, text_size =
table_size, text_halign = text.align_left)
 tb.cell(0, 6, "💧 Volume Sentiment", text_color = color.white, text_size =
table_size, text_halign = text.align_left)

tb.cell(1, 2, autopilotMode, text_color = color.white, text_size =

table_size)
tb.cell(1, 3, str.tostring(trendStrengthMetric, format.percent),
text_color=trendStrengthTextColor, text_size=table_size, bgcolor =
trendStrengthCellColor)
tb.cell(1, 4, volatilityText, text_color = VolatilityTextColor, text_size =
table_size, bgcolor = volatilityCellColor)
tb.cell(1, 5, str.tostring(squeezeMetric, format.percent), text_color=
squeezeTextColor, text_size=table_size, bgcolor = squeezeCellColor)
tb.cell(1, 6, str.tostring(math.min(volumeSentiment, 100.),
format.percent), text_color = volumeTextColor, text_size = table_size, bgcolor =
volumeCellColor)

//
***********************************************************************************
*************************
// REV ZONES
//
***********************************************************************************
*************************

indiSet = false
source = hlc3
type = 'SuperSmoother'
length = 100
innermult = 1.0
outermult = 2.415

ChartSet = false
drawchannel = true
displayzone = true
zonetransp = 60
displayline = true

MTFSet = false
enable_mtf = true
mtf_disp_typ = 'On Hover'
mtf_typ = 'Auto'
mtf_lvl1 = 'D'
mtf_lvl2 = 'W'

//
***********************************************************************************
*************************
// Functions Start {
//
***********************************************************************************
*************************
var pi = 2 * math.asin(1)
var mult = pi * innermult
var mult2 = pi * outermult
var gradsize = 0.5
var gradtransp = zonetransp

//-----------------------
// Ehler SwissArmyKnife Function
//-----------------------
SAK_smoothing(_type, _src, _length) =>
c0 = 1.0
c1 = 0.0
b0 = 1.0
b1 = 0.0
b2 = 0.0
a1 = 0.0
a2 = 0.0
alpha = 0.0
beta = 0.0
gamma = 0.0
cycle = 2 * pi / _length

if _type == 'Ehlers EMA'

alpha := (math.cos(cycle) + math.sin(cycle) - 1) / math.cos(cycle)
b0 := alpha
a1 := 1 - alpha
a1
if _type == 'Gaussian'
beta := 2.415 * (1 - math.cos(cycle))
alpha := -beta + math.sqrt(beta * beta + 2 * beta)
c0 := alpha * alpha
a1 := 2 * (1 - alpha)
a2 := -(1 - alpha) * (1 - alpha)
a2
if _type == 'Butterworth'
beta := 2.415 * (1 - math.cos(cycle))
alpha := -beta + math.sqrt(beta * beta + 2 * beta)
c0 := alpha * alpha / 4
b1 := 2
b2 := 1
a1 := 2 * (1 - alpha)
a2 := -(1 - alpha) * (1 - alpha)
a2
if _type == 'BandStop'
beta := math.cos(cycle)
gamma := 1 / math.cos(cycle * 2 * 0.1) // delta default to 0.1. Acceptable
delta -- 0.05<d<0.5
alpha := gamma - math.sqrt(gamma * gamma - 1)
c0 := (1 + alpha) / 2
b1 := -2 * beta
b2 := 1
a1 := beta * (1 + alpha)
a2 := -alpha
a2
if _type == 'SMA'
c1 := 1 / _length
b0 := 1 / _length
a1 := 1
a1
if _type == 'EMA'
alpha := 2 / (_length + 1)
b0 := alpha
a1 := 1 - alpha
 a1
if _type == 'RMA'
alpha := 1 / _length
b0 := alpha
a1 := 1 - alpha
a1

_Input = _src
_Output = 0.0
_Output := c0 * (b0 * _Input + b1 * nz(_Input[1]) + b2 * nz(_Input[2])) + a1 *
nz(_Output[1]) + a2 * nz(_Output[2]) - c1 * nz(_Input[_length])
_Output

//-----------------------
// SuperSmoother Function
//-----------------------
supersmoother(_src, _length) =>
s_a1 = math.exp(-math.sqrt(2) * pi / _length)
s_b1 = 2 * s_a1 * math.cos(math.sqrt(2) * pi / _length)
s_c3 = -math.pow(s_a1, 2)
s_c2 = s_b1
s_c1 = 1 - s_c2 - s_c3
ss = 0.0
ss := s_c1 * _src + s_c2 * nz(ss[1], _src[1]) + s_c3 * nz(ss[2], _src[2])
ss

//-----------------------
// Auto TimeFrame Function
//-----------------------
// ————— Converts current chart resolution into a float minutes value.
f_resInMinutes() =>
_resInMinutes = timeframe.multiplier * (timeframe.isseconds ? 1. / 60 :
timeframe.isminutes ? 1. : timeframe.isdaily ? 60. * 24 : timeframe.isweekly ? 60.
* 24 * 7 : timeframe.ismonthly ? 60. * 24 * 30.4375 : na)
_resInMinutes

get_tf(_lvl) =>
y = f_resInMinutes()
z = timeframe.period
if mtf_typ == 'Auto'
if y < 1
z := _lvl == 1 ? '1' : _lvl == 2 ? '5' : z
z
else if y <= 3
z := _lvl == 1 ? '5' : _lvl == 2 ? '15' : z
z
else if y <= 10
z := _lvl == 1 ? '15' : _lvl == 2 ? '60' : z
z
else if y <= 30
z := _lvl == 1 ? '60' : _lvl == 2 ? '240' : z
z
else if y <= 120
z := _lvl == 1 ? '240' : _lvl == 2 ? 'D' : z
z
else if y <= 240
z := _lvl == 1 ? 'D' : _lvl == 2 ? 'W' : z
z
else if y <= 1440
 z := _lvl == 1 ? 'W' : _lvl == 2 ? 'M' : z
z
else if y <= 10080
z := _lvl == 1 ? 'M' : z
z
else
z := z
z
else
z := _lvl == 1 ? mtf_lvl1 : _lvl == 2 ? mtf_lvl2 : z
z

//-----------------------
// Mean Reversion Channel Function
//-----------------------
get_mrc() =>
v_condition = 0
v_meanline = source
v_meanrange = supersmoother(ta.tr, length)

//-- Get Line value

if type == 'SuperSmoother'
v_meanline := supersmoother(source, length)
v_meanline

if type != 'SuperSmoother'
v_meanline := SAK_smoothing(type, source, length)
v_meanline

v_upband1 = v_meanline + v_meanrange * mult

v_loband1 = v_meanline - v_meanrange * mult
v_upband2 = v_meanline + v_meanrange * mult2
v_loband2 = v_meanline - v_meanrange * mult2

//-- Check Condition

if close > v_meanline
v_upband2_1 = v_upband2 + v_meanrange * gradsize * 4
v_upband2_9 = v_upband2 + v_meanrange * gradsize * -4
if high >= v_upband2_9 and high < v_upband2
v_condition := 1
v_condition
else if high >= v_upband2 and high < v_upband2_1
v_condition := 2
v_condition
else if high >= v_upband2_1
v_condition := 3
v_condition
else if close <= v_meanline + v_meanrange
v_condition := 4
v_condition
else
v_condition := 5
v_condition

if close < v_meanline

v_loband2_1 = v_loband2 - v_meanrange * gradsize * 4
v_loband2_9 = v_loband2 - v_meanrange * gradsize * -4
 if low <= v_loband2_9 and low > v_loband2
v_condition := -1
v_condition
else if low <= v_loband2 and low > v_loband2_1
v_condition := -2
v_condition
else if low <= v_loband2_1
v_condition := -3
v_condition
else if close >= v_meanline + v_meanrange
v_condition := -4
v_condition
else
v_condition := -5
v_condition

[v_meanline, v_meanrange, v_upband1, v_loband1, v_upband2, v_loband2,

v_condition]

//-----------------------
// MTF Analysis
//-----------------------

get_stat(_cond) =>
ret = 'Price at Mean Line\n'
if _cond == 1
ret := 'Overbought (Weak)\n'
ret
else if _cond == 2
ret := 'Overbought\n'
ret
else if _cond == 3
ret := 'Overbought (Strong)\n'
ret
else if _cond == 4
ret := 'Price Near Mean\n'
ret
else if _cond == 5
ret := 'Price Above Mean\n'
ret
else if _cond == -1
ret := 'Oversold (Weak)\n'
ret
else if _cond == -2
ret := 'Oversold\n'
ret
else if _cond == -3
ret := 'Oversold (Strong)\n'
ret
else if _cond == -4
ret := 'Price Near Mean\n'
ret
else if _cond == -5
ret := 'Price Below Mean\n'
ret
ret

//-----------------------
// Chart Drawing Function
//-----------------------
format_price(x) =>
y = str.tostring(x, '0.00000')
if x > 10
y := str.tostring(x, '0.000')
y
if x > 1000
y := str.tostring(x, '0.00')
y
y

f_PriceLine(_ref, linecol) =>

line.new(x1=bar_index, x2=bar_index - 1, y1=_ref, y2=_ref, extend=extend.left,
color=linecol)

f_MTFLabel(_txt, _yloc) =>

label.new(x=time + math.round(ta.change(time) * 20), y=_yloc,
xloc=xloc.bar_time, text=mtf_disp_typ == 'Always Display' ? _txt : 'Check MTF',
tooltip=mtf_disp_typ == 'Always Display' ? '' : _txt, color=color.black,
textcolor=color.white, size=size.normal, style=mtf_disp_typ == 'On Hover' and
displayline ? label.style_label_lower_left : label.style_label_left,
textalign=text.align_left)

//} Function End

//
***********************************************************************************
*************************
// Calculate Channel
//
***********************************************************************************
*************************
var tf_0 = timeframe.period
var tf_1 = get_tf(1)
var tf_2 = get_tf(2)
textstylist = table.new(textVPosition + '_' + textHPosition, 1, 3)
[meanline, meanrange, upband1, loband1, upband2, loband2, condition] = get_mrc()
[mtf1_meanline, mtf1_meanrange, mtf1_upband1, mtf1_loband1, mtf1_upband2,
mtf1_loband2, mtf1_condition] = request.security(syminfo.tickerid, tf_1, get_mrc())
[mtf2_meanline, mtf2_meanrange, mtf2_upband1, mtf2_loband1, mtf2_upband2,
mtf2_loband2, mtf2_condition] = request.security(syminfo.tickerid, tf_2, get_mrc())

//
***********************************************************************************
*************************
// Drawing Start {
//
***********************************************************************************
*************************
float p_meanline = drawchannel ? meanline : na
float p_upband1 = drawchannel ? upband1 : na
float p_loband1 = drawchannel ? loband1 : na
float p_upband2 = drawchannel ? upband2 : na
float p_loband2 = drawchannel ? loband2 : na

//z = plot(p_meanline, color=color.new(#FFCD00, 0), style=plot.style_line, title='

Mean', linewidth=2)
//x1 = plot(p_upband1, color=color.new(color.green, 50), style=plot.style_circles,
title=' R1', linewidth=1)
//x2 = plot(p_loband1, color=color.new(color.green, 50), style=plot.style_circles,
title=' S1', linewidth=1)
//y1 = plot(p_upband2, color=color.new(color.red, 50), style=plot.style_line,
title=' R2', linewidth=1)
//y2 = plot(p_loband2, color=color.new(color.red, 50), style=plot.style_line,
title=' S2', linewidth=1)

//-----------------------
// Draw zone
//-----------------------
//---
var color1 = #FF0000
var color2 = #FF4200
var color3 = #FF5D00
var color4 = #FF7400
var color5 = #FF9700
var color6 = #FFAE00
var color7 = #FFC500
var color8 = #FFCD00
//---
float upband2_1 = drawchannel and displayzone ? upband2 + meanrange * gradsize *
4 : na
float loband2_1 = drawchannel and displayzone ? loband2 - meanrange * gradsize *
4 : na
float upband2_2 = drawchannel and displayzone ? upband2 + meanrange * gradsize *
3 : na
float loband2_2 = drawchannel and displayzone ? loband2 - meanrange * gradsize *
3 : na
float upband2_3 = drawchannel and displayzone ? upband2 + meanrange * gradsize *
2 : na
float loband2_3 = drawchannel and displayzone ? loband2 - meanrange * gradsize *
2 : na
float upband2_4 = drawchannel and displayzone ? upband2 + meanrange * gradsize *
1 : na
float loband2_4 = drawchannel and displayzone ? loband2 - meanrange * gradsize *
1 : na
float upband2_5 = drawchannel and displayzone ? upband2 + meanrange * gradsize *
0 : na
float loband2_5 = drawchannel and displayzone ? loband2 - meanrange * gradsize *
0 : na
float upband2_6 = drawchannel and displayzone ? upband2 + meanrange * gradsize * -1
: na
float loband2_6 = drawchannel and displayzone ? loband2 - meanrange * gradsize * -1
: na
float upband2_7 = drawchannel and displayzone ? upband2 + meanrange * gradsize * -2
: na
float loband2_7 = drawchannel and displayzone ? loband2 - meanrange * gradsize * -2
: na
float upband2_8 = drawchannel and displayzone ? upband2 + meanrange * gradsize * -3
: na
float loband2_8 = drawchannel and displayzone ? loband2 - meanrange * gradsize * -3
: na
float upband2_9 = drawchannel and displayzone ? upband2 + meanrange * gradsize * -4
: na
float loband2_9 = drawchannel and displayzone ? loband2 - meanrange * gradsize * -4
: na

up1 = plot(reversalZone ? upband2_1 : na, color = color.black, transp = 100,

editable = false)
up2 = plot(reversalZone ?upband2_5:na, color = color.black, transp = 100, editable
= false)
up3 = plot(reversalZone ?upband2_9:na, color = color.black, transp = 100, editable
= false)
dp1 = plot(reversalZone ?loband2_1:na, color = color.black, transp = 100, editable
= false)
dp2 = plot(reversalZone ?loband2_5:na, color = color.black, transp = 100, editable
= false)
dp3 = plot(reversalZone ?loband2_9:na, color = color.black, transp = 100, editable
= false)

fill(up1, up2, color = #56202d, transp = 20, editable = false)

fill(up2, up3, color = #3f1d29, transp = 60, editable = false)
fill(dp1, dp2, color = #0f3e3f, transp = 20, editable = false)
fill(dp2, dp3, color = #113135, transp = 60, editable = false)

//[upband2_1, upband2_5, upband2_9, loband2_1, loband2_5, loband2_9]

tenkan_len = 365
tenkan_mult = 3

kijun_len = 365
kijun_mult = 7

spanB_len = 365
spanB_mult = 15

offset = 2
//------------------------------------------------------------------------------
avg(src,length,mult)=>
atr = ta.atr(length)*mult
up = hl2 + atr
dn = hl2 - atr
upper = 0.,lower = 0.
upper := src[1] < upper[1] ? math.min(up,upper[1]) : up
lower := src[1] > lower[1] ? math.max(dn,lower[1]) : dn

os = 0,max = 0.,min = 0.
os := src > upper ? 1 : src < lower ? 0 : os[1]
spt = os == 1 ? lower : upper
max := ta.cross(src,spt) ? math.max(src,max[1]) : os == 1 ?
math.max(src,max[1]) : spt
min := ta.cross(src,spt) ? math.min(src,min[1]) : os == 0 ?
math.min(src,min[1]) : spt
math.avg(max,min)
//------------------------------------------------------------------------------
tenkan = avg(close,tenkan_len,tenkan_mult)
kijun = avg(close,kijun_len,kijun_mult)

senkouA = math.avg(kijun,tenkan)
senkouB = avg(close,spanB_len,spanB_mult)
//------------------------------------------------------------------------------
tenkan_css = #2156f300
kijun_css = #ff5e0000
cloud_a = color.new(#006989, 47)
cloud_b = color.new(#ff5252, 66)

chikou_css = #7b1fa2

plot(neoCloud ? tenkan : na,'Tenkan-Sen',tenkan_css, editable = false)

plot(neoCloud ? kijun : na,'Kijun-Sen',kijun_css, editable = false)

plot(neoCloud and ta.crossover(tenkan,kijun) ? kijun :

na,'Crossover',#2156f300,3,plot.style_circles, editable = false)
plot(neoCloud and ta.crossunder(tenkan,kijun) ? kijun :
na,'Crossunder',#ff5e0000,3,plot.style_circles, editable = false)

A = plot(neoCloud ? senkouA: na,'Senkou Span A',na,offset=offset-1, editable =

false)
B = plot(neoCloud ? senkouB : na,'Senkou Span B',na,offset=offset-1, editable =
false)
fill(A,B,senkouA > senkouB ? cloud_a : cloud_b)

lastNeo = int(senkouA + senkouB)

last5Neo = ta.sma(lastNeo, 2)

plot(close,'Chikou',chikou_css,offset=-offset+1,display=display.none, editable =
false)

// Wylicz pozycję kwadratu

ltp1 = bar_index
rtp1 = bar_index + 40

[lowBound, midBound, highBound] = LAF.getTPSLBoxes(6.0)

// Stwórz rzeczywisty kwadrat

//tp1box = box.new(left=ltp1, top=ttp1, right=rtp1, bottom=btp1,
border_color=#3666f5, border_width=2, border_style=line.style_solid,
bgcolor=color.new(#3666f5, 53), text="TP1 : " + str.tostring(close),
text_size=size.large, text_color=color.new(#3666f5, 0), text_wrap=text.wrap_auto)
//var boxes = array.new<box>()
//boxes.push(box.new(left = ltp1, top = close+highBound, right = rtp1, bottom =
close + midBound, border_color=#3666f5, border_width=2,
border_style=line.style_solid, bgcolor=color.new(#3666f5, 70), text="TP/SL 2 : "
+ str.tostring(close), text_size=size.large, text_color=color.new(#3666f5, 0),
text_wrap=text.wrap_auto))
//boxes.push(box.new(left = ltp1, top = close+midBound, right = rtp1, bottom =
close + lowBound, border_color=#3666f5, border_width=2,
border_style=line.style_solid, bgcolor=color.new(#3666f5, 40), text="TP/SL 1 : "
+ str.tostring(close), text_size=size.large, text_color=color.new(#3666f5, 0),
text_wrap=text.wrap_auto))
//SL1 = box.new(left = ltp1, top = close-highBound, right = rtp1, bottom = close -
midBound, border_color=#3666f5, border_width=2, border_style=line.style_solid,
bgcolor=color.new(#3666f5, 70), text="TP/SL 2 : " + str.tostring(close),
text_size=size.large, text_color=color.new(#3666f5, 0), text_wrap=text.wrap_auto)
//SL2 = box.new(left = ltp1, top = close-midBound, right = rtp1, bottom = close -
lowBound, border_color=#3666f5, border_width=2, border_style=line.style_solid,
bgcolor=color.new(#3666f5, 40), text="TP/SL 1 : " + str.tostring(close),
text_size=size.large, text_color=color.new(#3666f5, 0), text_wrap=text.wrap_auto)

// Usuń poprzednie ramki

//box.delete(boxes.shift())
//box.delete(SL1[1])
//box.delete(SL2[1])

//box.delete(boxes.shift())

// ==== Overview ====

// ==================

// WaveTrend 3D (WT3D) is a novel implementation of the famous WaveTrend (WT)

indicator and has been completely redesigned from the ground up to address some
// of the inherent shortcomings associated with the traditional WT algorithm,
including:
// (1) unbounded extremes
// (2) susceptibility to whipsaw
// (3) lack of insight into other timeframes

// Furthermore, WT3D expands upon the original functionality of WT by providing:

// (1) first-class support for multi-timeframe (MTF) analysis
// (2) kernel-based regression for trend reversal confirmation
// (3) various options for signal smoothing and transformation
// (4) a unique mode for visualizing an input series as a symmetrical, three-
dimensional waveform useful for pattern identification and cycle-related analysis

// Fundamental Assumptions:
// (1) There exists a probability density function that describes the relative
likelihood for a price to visit a given value.
// (2) The probability density function for price is a function of time.
// (3) The probability density function can approximate a Gaussian distribution
(shown below).

// ___
// .::~!:.. |

// :ΞΞΞΞ~!ΞΞΞ!. |

// .ΞJΞΞΞΞ~!ΞΞΞ?J^ |

// :J?ΞΞΞΞΞ~!ΞΞΞΞΞJ^ |

// :J?ΞΞΞΞΞΞ~!ΞΞΞΞΞΞ??. |

// :JΞΞΞΞΞΞΞΞ~!ΞΞΞΞΞΞΞ?J^ |

// :JΞΞΞΞΞΞΞΞΞ~!ΞΞΞΞΞΞΞΞ?J^
[ PRICE ]
// .:~ΞΞΞΞΞΞΞΞΞΞ~!ΞΞΞΞΞΞΞΞΞ!!~ |
// :?~^ΞΞΞΞΞΞΞΞΞΞ~!ΞΞΞΞΞΞΞΞΞ!^Ξ! |

// ~:^^^ΞΞΞΞΞΞΞΞΞΞ~!ΞΞΞΞΞΞΞΞΞ!^^!Ξ. |

// .Ξ!^^^^ΞΞΞΞΞΞΞΞΞΞ~!ΞΞΞΞΞΞΞΞΞ!^^^~Ξ~ |

// .~Ξ~^^^^^ΞΞΞΞΞΞΞΞΞΞ~!ΞΞΞΞΞΞΞΞΞ!^^^^^!Ξ: |

// .~Ξ~^^^^^^^ΞΞΞΞΞΞΞΞΞΞ~!ΞΞΞΞΞΞΞΞΞ!^^^^^^~!!^. |

// ....::^^!~~^^^^^^^^^ΞΞΞΞΞΞΞΞΞΞ~!ΞΞΞΞΞΞΞΞΞ!^^^^^^^^^~!^^::...... |

// ..:::^^^^^^^::::::::::::::ΞΞΞΞΞΞΞΞΞΞ~!ΞΞΞΞΞΞΞΞΞ!::::::::::::^^^^^^^^:::.. |

//
// -------------------------------- [ TIME ] -------------------------------|

// How to use this indicator:

// - The basic usage of WT3D is similar to how one would use the traditional WT
indicator.
// - Divergences can be spotted by finding "trigger waves", which are small waves
that immediately follow a larger wave. These can also be thought of as Lower-Highs
and Higher-Lows in the oscillator.
// - Instead of the SMA-cross in the original WT, the primary mechanism for
identifying potential pivots are the crossovers of the fast/normal speed
oscillators, denoted by the small red/green circles.
// - The larger red/green circles represent points where there could be a potential
trigger wave for a Divergence. Settings related to Divergence detection can be
configured in the "Divergence" section.
// - For overbought/oversold conditions, the 0.5 and -0.5 levels are convenient
since the normal-speed oscillator will only exceed this level ~25% of the time.
// - For less experienced users, focusing on the three oscillators is recommended
since they give critical information from multiple timeframes that can help to
identify trends and spot potential divergences.
// - For more experienced users, this indicator also has many other valuable
features, such as Center of Gravity (CoG) smoothing, Kernel Estimate Crossovers, a
mirrored mode for cycle analysis, and more.
// - Note: Additional resources for learning/using the more advanced features of
this indicator are a work in progress, but in the meantime, I am happy to answer
any questions.

// ================
// ==== Inputs ====
// ================

// Signal Settings
src = close
useMirror = false
useEma = false
emaLength = 3
useCog = false
cogLength = 6
oscillatorLookback =20
quadraticMeanLength = 50
src := useEma ? ta.ema(src, emaLength) : src
src := useCog ? ta.cog(src, cogLength) : src
speedToEmphasize = 'Normal'
emphasisWidth = 2
useKernelMA = false
useKernelEmphasis = false

// Oscillator Settings
offset := 0
showOsc = true
showOsc := showOsc
float f_length = 0.75
float f_smoothing = 0.45
float n_length = 1.0
float n_smoothing = 1.0
float s_length = 1.75
float s_smoothing = 2.5

// Divergence Detection
divThreshold = 30
sizePercent = 40

// Overbought/Oversold Zones (Reversal Zones)

showObOs = false
invertObOsColors = false

// Transparencies and Gradients

areaBackgroundTrans = 128.
areaForegroundTrans = 64.
lineBackgroundTrans = 2.6
lineForegroundTrans = 2.
customTransparency = 30
maxStepsForGradient = 8

// The defaults are colors that Google uses for its Data Science libraries (e.g.
TensorFlow). They are considered to be colorblind-safe.
var color fastBullishColor = color.black
var color normalBullishColor = color.black
var color slowBullishColor = color.black
var color fastBearishColor = color.black
var color normalBearishColor = color.black
var color slowBearishColor =color.black
var color c_bullish = color.black
var color c_bearish = color.black

lineBackgroundTrans := lineBackgroundTrans * customTransparency

areaBackgroundTrans := areaBackgroundTrans * customTransparency
lineForegroundTrans := lineForegroundTrans * customTransparency
areaForegroundTrans := areaForegroundTrans * customTransparency

areaFastTrans = areaBackgroundTrans
lineFastTrans = lineBackgroundTrans
areaNormalTrans = areaBackgroundTrans
lineNormalTrans = lineBackgroundTrans
areaSlowTrans = areaForegroundTrans
lineSlowTrans = lineForegroundTrans

switch speedToEmphasize
"Slow" =>
areaFastTrans := areaBackgroundTrans
lineFastTrans := lineBackgroundTrans
areaNormalTrans := areaBackgroundTrans
lineNormalTrans := lineBackgroundTrans
 areaSlowTrans := areaForegroundTrans
lineSlowTrans := lineForegroundTrans
"Normal" =>
areaFastTrans := areaBackgroundTrans
lineFastTrans := lineBackgroundTrans
areaNormalTrans := areaForegroundTrans
lineNormalTrans := lineForegroundTrans
areaSlowTrans := areaBackgroundTrans
lineSlowTrans := lineBackgroundTrans
"Fast" =>
areaFastTrans := areaForegroundTrans
lineFastTrans := lineForegroundTrans
areaNormalTrans := areaBackgroundTrans
lineNormalTrans := lineBackgroundTrans
areaSlowTrans := areaBackgroundTrans
lineSlowTrans := lineBackgroundTrans
"None" =>
areaFastTrans := areaBackgroundTrans
lineFastTrans := lineBackgroundTrans
areaNormalTrans := areaBackgroundTrans
lineNormalTrans := lineBackgroundTrans
areaSlowTrans := areaBackgroundTrans
lineSlowTrans := lineBackgroundTrans

// =================================
// ==== Color Helper Functions =====
// =================================

getPlotColor(signal, bullColor, bearColor) =>

signal >= 0.0 ? bullColor : bearColor

getAreaColor(signal, useMomentum, bullColor, bearColor) =>

if useMomentum
ta.rising(signal, 1) ? bullColor : bearColor
else
signal >= 0.0 ? bullColor : bearColor

getColorGradientFromSteps(_source, _center, _steps, weakColor, strongColor) =>

var float _qtyAdvDec = 0.
var float _maxSteps = math.max(1, _steps)
bool _xUp = ta.crossover(_source, _center)
bool _xDn = ta.crossunder(_source, _center)
float _chg = ta.change(_source)
bool _up = _chg > 0
bool _dn = _chg < 0
bool _srcBull = _source > _center
bool _srcBear = _source < _center
_qtyAdvDec := _srcBull ? _xUp ? 1 : _up ? math.min(_maxSteps, _qtyAdvDec + 1) :
_dn ? math.max(1, _qtyAdvDec - 1) : _qtyAdvDec : _srcBear ? _xDn ? 1 : _dn ?
math.min(_maxSteps, _qtyAdvDec + 1) : _up ? math.max(1, _qtyAdvDec - 1) :
_qtyAdvDec : _qtyAdvDec
color colorGradient = color.from_gradient(_qtyAdvDec, 1, _maxSteps, weakColor,
strongColor)
colorGradient

getColorGradientFromSource(series, _min, _max, weakColor, strongColor) =>

var float baseLineSeries = _min + (_max - _min) / 2
color colorGradient = series >= baseLineSeries ?
color.from_gradient(value=series, bottom_value=baseLineSeries, top_value=_max,
bottom_color=weakColor, top_color=strongColor) : color.from_gradient(series, _min,
baseLineSeries, strongColor, weakColor)
colorGradient

// ================================
// ==== Main Helper Functions =====
// ================================

normalizeDeriv(_src, _quadraticMeanLength) =>

float derivative = _src - _src[2]
quadraticMean = math.sqrt(nz(math.sum(math.pow(derivative, 2),
_quadraticMeanLength) / _quadraticMeanLength))
derivative/quadraticMean

tanh(series float _src) =>

-1 + 2/(1 + math.exp(-2*_src))

dualPoleFilter(float _src, float _lookback) =>

float _omega = -99 * math.pi / (70 * _lookback)
float _alpha = math.exp(_omega)
float _beta = -math.pow(_alpha, 2)
float _gamma = math.cos(_omega) * 2 * _alpha
float _delta = 1 - _gamma - _beta
float _slidingAvg = 0.5 * (_src + nz(_src[1], _src))
float _filter = na
_filter := (_delta*_slidingAvg) + _gamma*nz(_filter[1]) + _beta*nz(_filter[2])
_filter

getOscillator(float src, float smoothingFrequency, int quadraticMeanLength) =>

nDeriv = normalizeDeriv(src, quadraticMeanLength)
hyperbolicTangent = tanh(nDeriv)
result = dualPoleFilter(hyperbolicTangent, smoothingFrequency)

// =================================
// ==== Oscillator Calculations ====
// =================================

// Fast Oscillator + Mirror

offsetFast = offset
f_lookback = f_smoothing * oscillatorLookback
signalFast = getOscillator(src, f_lookback, quadraticMeanLength)
seriesFast = f_length*signalFast+offsetFast
seriesFastMirror = useMirror ? -seriesFast + 2*offsetFast : na

// Normal Oscillator + Mirror

offsetNormal = 0
n_lookback = n_smoothing * oscillatorLookback
signalNormal = getOscillator(src, n_lookback, quadraticMeanLength)
seriesNormal = n_length*signalNormal+offsetNormal
seriesNormalMirror = useMirror ? -seriesNormal + 2*offsetNormal : na

// Slow Oscillator + Mirror

offsetSlow = -offset
s_lookback = s_smoothing * oscillatorLookback
signalSlow = getOscillator(src, s_lookback, quadraticMeanLength)
seriesSlow = s_length*signalSlow+offsetSlow
seriesSlowMirror = useMirror ? -seriesSlow + 2*offsetSlow : na

// =====================================
// ==== Color Gradient Calculations ====
// =====================================

// Fast Color Gradients (Areas and Lines)

fastBaseColor = getPlotColor(signalFast, fastBullishColor, fastBearishColor)
fastBaseColorInverse = getPlotColor(signalFast, fastBearishColor, fastBullishColor)
fastAreaGradientFromSource = getColorGradientFromSource(seriesFast, -1.+offsetFast,
1+offsetFast, color.new(fastBaseColor, areaFastTrans), fastBaseColor)
fastAreaGradientFromSteps = getColorGradientFromSteps(seriesFast, offsetFast,
maxStepsForGradient, color.new(fastBaseColor, areaFastTrans), fastBaseColor)
fastLineGradientFromSource = getColorGradientFromSource(seriesFast, -1+offsetFast,
1+offsetFast, color.new(fastBaseColor, lineFastTrans), fastBaseColor)
fastLineGradientFromSteps = getColorGradientFromSteps(seriesFast, offsetFast,
maxStepsForGradient, color.new(fastBaseColor, lineFastTrans), fastBaseColor)
fastAreaGradientFromSourceInverse = getColorGradientFromSource(seriesFast, -
1.+offsetFast, 1+offsetFast, color.new(fastBaseColorInverse, areaFastTrans),
fastBaseColorInverse)
fastAreaGradientFromStepsInverse = getColorGradientFromSteps(seriesFast,
offsetFast, maxStepsForGradient, color.new(fastBaseColorInverse, areaFastTrans),
fastBaseColorInverse)

// Normal Color Gradients (Areas and Lines)

normalBaseColor = getPlotColor(signalNormal, normalBullishColor,
normalBearishColor)
normalBaseColorInverse = getPlotColor(signalNormal, normalBearishColor,
normalBullishColor)
normalAreaGradientFromSource = getColorGradientFromSource(seriesNormal, -
1.+offsetNormal, 1.+offsetNormal, color.new(normalBaseColor, areaNormalTrans),
normalBaseColor)
normalAreaGradientFromSteps = getColorGradientFromSteps(seriesNormal, offsetNormal,
maxStepsForGradient, color.new(normalBaseColor, areaNormalTrans), normalBaseColor)
normalLineGradientFromSource = getColorGradientFromSource(seriesNormal, -
1+offsetNormal, 1+offsetNormal, color.new(normalBaseColor, lineNormalTrans),
normalBaseColor)
normalLineGradientFromSteps = getColorGradientFromSteps(seriesNormal, offsetNormal,
maxStepsForGradient, color.new(normalBaseColor, lineNormalTrans), normalBaseColor)
normalAreaGradientFromSourceInverse = getColorGradientFromSource(seriesNormal, -
1.+offsetNormal, 1.+offsetNormal, color.new(normalBaseColorInverse,
areaNormalTrans), normalBaseColorInverse)
normalAreaGradientFromStepsInverse = getColorGradientFromSteps(seriesNormal,
offsetNormal, maxStepsForGradient, color.new(normalBaseColorInverse,
areaNormalTrans), normalBaseColorInverse)

// Slow Color Gradients (Areas and Lines)

slowBaseColor = getPlotColor(signalSlow, slowBullishColor, slowBearishColor)
slowBaseColorInverse = getPlotColor(signalSlow, slowBearishColor, slowBullishColor)
slowAreaGradientFromSource = getColorGradientFromSource(seriesSlow, -
1.75+offsetSlow, 1.75+offsetSlow, color.new(slowBaseColor, areaSlowTrans),
slowBaseColor)
slowAreaGradientFromSteps = getColorGradientFromSteps(seriesSlow, offsetSlow,
maxStepsForGradient, color.new(slowBaseColor, areaSlowTrans), slowBaseColor)
slowLineGradientFromSource = getColorGradientFromSource(seriesSlow, -
1.75+offsetSlow, 1.75+offsetSlow, color.new(slowBaseColor, lineSlowTrans),
slowBaseColor)
slowLineGradientFromSteps = getColorGradientFromSteps(seriesSlow, offsetSlow,
maxStepsForGradient, color.new(slowBaseColor, lineSlowTrans), slowBaseColor)
slowAreaGradientFromSourceInverse = getColorGradientFromSource(seriesSlow, -
1.75+offsetSlow, 1.75+offsetSlow, color.new(slowBaseColorInverse, areaSlowTrans),
slowBaseColorInverse)
slowAreaGradientFromStepsInverse = getColorGradientFromSteps(seriesSlow,
offsetSlow, maxStepsForGradient, color.new(slowBaseColorInverse, areaSlowTrans),
slowBaseColorInverse)

// =========================================
// ==== Plot Parameters and Logic Gates ====
// =========================================

// Speed Booleans
isSlow = speedToEmphasize == "Slow"
isNormal = speedToEmphasize == "Normal"
isFast = speedToEmphasize == "Fast"

// Series Colors
seriesSlowColor = showOsc or isSlow ? color.new(slowLineGradientFromSource,
lineSlowTrans) : na
seriesNormalColor = showOsc or isNormal ? color.new(normalLineGradientFromSource,
lineNormalTrans) : na
seriesFastColor = showOsc or isFast ? color.new(fastLineGradientFromSource,
lineFastTrans) : na
seriesSlowMirrorColor = useMirror ? seriesSlowColor : na
seriesNormalMirrorColor = useMirror ? seriesNormalColor : na
seriesFastMirrorColor = useMirror ? seriesFastColor : na

// Series Line Widths

seriesSlowWidth = isSlow ? emphasisWidth : 1
seriesNormalWidth = isNormal ? emphasisWidth : 1
seriesFastWidth = isFast ? emphasisWidth : 1
seriesSlowMirrorWidth = useMirror ? seriesSlowWidth : na
seriesNormalMirrorWidth = useMirror ? seriesNormalWidth : na
seriesFastMirrorWidth = useMirror ? seriesFastWidth : na

// Speed Related Switches

seriesEmphasis = switch
isFast => seriesFast
isNormal => seriesNormal
isSlow => seriesSlow
=> na
//
colorLineEmphasis = switch
isFast => fastLineGradientFromSource
isNormal => normalLineGradientFromSource
isSlow => slowLineGradientFromSource
=> na

colorAreaEmphasis = switch
isFast => fastAreaGradientFromSource
isNormal => normalAreaGradientFromSource
isSlow => slowAreaGradientFromSource
=> na

// Crossover Signals
bearishCross = ta.crossunder(seriesFast, seriesNormal) and seriesNormal > 0
bullishCross = ta.crossover(seriesFast, seriesNormal) and seriesNormal < 0
slowBearishMedianCross = ta.crossunder(seriesSlow, 0)
slowBullishMedianCross = ta.crossover(seriesSlow, 0)
normalBearishMedianCross = ta.crossunder(seriesNormal, 0)
normalBullishMedianCross = ta.crossover(seriesNormal, 0)
fastBearishMedianCross = ta.crossunder(seriesFast, 0)
fastBullishMedianCross = ta.crossover(seriesFast, 0)

// Last Crossover Values

lastBearishCrossValue = ta.valuewhen(condition=bearishCross, source=seriesNormal,
occurrence=1)
lastBullishCrossValue = ta.valuewhen(condition=bullishCross , source=seriesNormal,
occurrence=1)

// Trigger Wave Size Comparison

triggerWaveFactor = sizePercent/100
isSmallerBearishCross = bearishCross and seriesNormal < lastBearishCrossValue *
triggerWaveFactor
isSmallerBullishCross = bullishCross and seriesNormal > lastBullishCrossValue *
triggerWaveFactor

// ===========================
// ==== Kernel Estimators ====
// ===========================

// The following kernel estimators are based on the Gaussian Kernel.

// They are used for:

// (1) Confirming directional changes in the slow oscillator (i.e. a type of
trend filter)
// (2) Visualizing directional changes as a dynamic ribbon (i.e. an additional
oscillator that can crossover with the user specified oscillator of interest)
// (3) Visualizing transient directional changes while in the midst of a larger
uptrend or downtrend (i.e. via color changes on the ribbon)

// Gaussian Kernel with a lookback of 6 bars, starting on bar 6 of the chart

(medium fit)
yhat0 = kernels.gaussian(seriesEmphasis, 6, 6)

// Gaussian Kernel with a lookback of 3 bars, starting on bar 2 of the chart (tight
fit)
yhat1 = kernels.gaussian(seriesEmphasis, 3, 2)

// Trend Assessment based on the relative position of the medium fit kernel to the
slow oscillator
isBearishKernelTrend = yhat0 < seriesSlow
isBullishKernelTrend = yhat0 > seriesSlow

// Divergence Signals
isBearishDivZone = ta.barssince(bearishCross[1]) < divThreshold
isBullishDivZone = ta.barssince(bullishCross[1]) < divThreshold

// Crossover Detection
isBearishTriggerWave = isSmallerBearishCross and isBearishDivZone and
isBearishKernelTrend
isBullishTriggerWave = isSmallerBullishCross and isBullishDivZone and
isBullishKernelTrend

// =======================
// ==== Plots & Fills ====

var position = 0
length := atrLength
minMult = math.max(sensitivity-4, 1)
maxMult = math.min(sensitivity, 26)

if (autopilotMode == "Short Term")

minMult:=1
maxMult := 4
if (autopilotMode == 'Mid Term')
minMult := 5
maxMult := 10
if (autopilotMode == 'Long-Term')
minMult :=8
maxMult :=13

float step = .5

//Trigger error
if minMult > maxMult
runtime.error('Minimum factor is greater than maximum factor in the range')

float perfAlpha = 10
fromCluster = 'Best'

//Optimization
maxIter = 250
maxData = 2500

//Style
bearCss = color.red
bullCss = color.teal

amaBearCss = color.new(color.red, 50)

amaBullCss = color.new(color.teal, 50)

showGradient = true

//Dashboard
showDash = true
//dashboardLocation = input.string('Top Right', 'Location', options = ['Top
Right', 'Bottom Right', 'Bottom Left'], group = 'Dashboard')
textSize = 'Small'

//-----------------------------------------------------------------------------}
//UDT's
//-----------------------------------------------------------------------------{
type supertrend
float upper = hl2
float lower = hl2
float output
float perf = 0
float factor
int trend = 0

type vector
array<float> out
//-----------------------------------------------------------------------------}
//Supertrend
//-----------------------------------------------------------------------------{
var holder = array.new<supertrend>(0)
var factors = array.new<float>(0)

//Populate supertrend type array

if barstate.isfirst
for i = 0 to int((maxMult - minMult) / step)
factors.push(minMult + i * step)
holder.push(supertrend.new())

atr = ta.atr(length)

//Compute Supertrend for multiple factors

k = 0
for factor in factors
get_spt = holder.get(k)

up = hl2 + atr * factor

dn = hl2 - atr * factor

get_spt.trend := close > get_spt.upper ? 1 : close < get_spt.lower ? 0 :

get_spt.trend
get_spt.upper := close[1] < get_spt.upper ? math.min(up, get_spt.upper) : up
get_spt.lower := close[1] > get_spt.lower ? math.max(dn, get_spt.lower) : dn

diff = nz(math.sign(close[1] - get_spt.output))

get_spt.perf += 2/(perfAlpha+1) * (nz(close - close[1]) * diff - get_spt.perf)
get_spt.output := get_spt.trend == 1 ? get_spt.lower : get_spt.upper
get_spt.factor := factor
k += 1

//-----------------------------------------------------------------------------}
//K-means clustering
//-----------------------------------------------------------------------------{
factor_array = array.new<float>(0)
data = array.new<float>(0)

//Populate data arrays

if last_bar_index - bar_index <= maxData
for element in holder
data.push(element.perf)
factor_array.push(element.factor)

//Intitalize centroids using quartiles

centroids = array.new<float>(0)
centroids.push(data.percentile_linear_interpolation(25))
centroids.push(data.percentile_linear_interpolation(50))
centroids.push(data.percentile_linear_interpolation(75))

//Intialize clusters
var array<vector> factors_clusters = na
var array<vector> perfclusters = na

if last_bar_index - bar_index <= maxData

for _ = 0 to maxIter
factors_clusters := array.from(vector.new(array.new<float>(0)),
vector.new(array.new<float>(0)), vector.new(array.new<float>(0)))
 perfclusters := array.from(vector.new(array.new<float>(0)),
vector.new(array.new<float>(0)), vector.new(array.new<float>(0)))

//Assign value to cluster

i = 0
for value in data
dist = array.new<float>(0)
for centroid in centroids
dist.push(math.abs(value - centroid))

idx = dist.indexof(dist.min())
perfclusters.get(idx).out.push(value)
factors_clusters.get(idx).out.push(factor_array.get(i))
i += 1

//Update centroids
new_centroids = array.new<float>(0)
for cluster_ in perfclusters
new_centroids.push(cluster_.out.avg())

//Test if centroid changed

if new_centroids.get(0) == centroids.get(0) and new_centroids.get(1) ==
centroids.get(1) and new_centroids.get(2) == centroids.get(2)
break

centroids := new_centroids

//-----------------------------------------------------------------------------}
//Signals and trailing stop
//-----------------------------------------------------------------------------{
//Get associated supertrend
var float target_factor = na
var float perf_idx = na
var float perf_ama = na

var from = switch fromCluster

'Best' => 2
'Average' => 1
'Worst' => 0

//Performance index denominator

den = ta.ema(math.abs(close - close[1]), int(perfAlpha))

if not na(perfclusters)
//Get average factors within target cluster
target_factor := nz(factors_clusters.get(from).out.avg(), target_factor)

//Get performance index of target cluster

perf_idx := math.max(nz(perfclusters.get(from).out.avg()), 0) / den

//Get new supertrend

var upper = hl2
var lower = hl2
var os = 0

up = hl2 + atr * target_factor

dn = hl2 - atr * target_factor
upper := close[1] < upper ? math.min(up, upper) : up
lower := close[1] > lower ? math.max(dn, lower) : dn
os := close > upper ? 1 : close < lower ? 0 : os
ts = os ? lower : upper

//Get trailing stop adaptive MA

if na(ts[1]) and not na(ts)
perf_ama := ts
else
perf_ama += perf_idx * (ts - perf_ama)

//-----------------------------------------------------------------------------}
//Dashboard
//-----------------------------------------------------------------------------{

//-----------------------------------------------------------------------------{
css = os ? bullCss : bearCss

plot(showTrailingStoploss ? ts : na, 'Trailing Stop', os != os[1] ? na : css,

editable = false)

plot(showMovingAverage? perf_ama:na, 'Trailing Stop AMA',

ta.cross(close, perf_ama) ? na
: close > perf_ama ? amaBullCss : amaBearCss, editable = false)

//Candle coloring
//barcolor(showGradient ? color.from_gradient(perf_idx, 0, 1, color.new(css, 80),
css) : na)

//Signals

if showSignals
if os > os[1] and (signalPresets != "Smart Trail [Filter]" or
smartTrailDirection == 'long') and (signalPresets != "Trend Tracer [Filter]" or
trendTracerDirection==#02ff65) and (signalPresets != "Trend Strength [Filter]" or
trendStrengthMetric >= 25) and (signalPresets != "Trend Catcher [Filter]" or
newTrendCatcherColor == #02ff65) and (signalPresets != "Neo Cloud [Filter]" or
int(lastNeo) >= last5Neo)
int signalStrength = int(perf_idx*10) < 2 ? 1 : int(perf_idx*10) < 4 ? 2 :
int(perf_idx*10) < 5 ? 3 : 4
label.new(n, low-ta.atr(30)/2, signalClassifier ?
str.tostring(signalStrength) : ema50 > ema200 ? "▲+" : "▲"
, color = bullCss
, style = label.style_label_up
, textcolor = color.white
, size = size.small)
position := 1

if os < os[1] and (signalPresets != "Smart Trail [Filter]" or

smartTrailDirection == 'short') and (signalPresets != "Trend Tracer [Filter]" or
trendTracerDirection!=#02ff65) and (signalPresets != "Trend Strength [Filter]" or
trendStrengthMetric >= 25)and (signalPresets != "Trend Catcher [Filter]" or
newTrendCatcherColor != #02ff65) and (signalPresets != "Neo Cloud [Filter]" or
int(lastNeo) <=last5Neo)
int signalStrength = int(perf_idx*10) < 2 ? 1 : int(perf_idx*10) < 4 ? 2 :
int(perf_idx*10) < 5 ? 3 : 4
label.new(n, high+ta.atr(30)/2, signalClassifier ?
str.tostring(signalStrength) : ema50 < ema200 ? "▼+" : "▼"
, color = bearCss
, style = label.style_label_down
, textcolor = color.white
 , size = size.small)
position := -1

// =======================

// Signal Plots
//plot(position == 1 and bearishCross ? high+5 : na, title="Bearish Cross",
style=plot.style_cross, linewidth=2, color=c_bearish, offset=-1)
//plot(position == -1 and bearishCross ? high+5 : na, title="Bearish Cross",
style=plot.style_circles, linewidth=2, color=c_bearish, offset=-1)
//plot(position == 1 and isBearishTriggerWave ? high+5 : na, title="Bearish Trigger
Cross", style=plot.style_cross, linewidth=3, color=c_bearish, offset=-1)
//plot(position == -1 and isBearishTriggerWave ? high+5 : na, title="Bearish
Trigger Cross", style=plot.style_circles, linewidth=3, color=c_bearish, offset=-1)
plotchar(bearishCross and position == 1, "Long", "✖", location.abovebar, color =
#4774f5, size = size.tiny, editable = false)
//plotchar(bearishCross and position == -1, "Long", "▼", location.abovebar, color =
c_bearish, size = size.tiny)
plotchar(isBearishTriggerWave and position == 1, "Long", "✖", location.abovebar,
color=#4774f5, size = size.tiny, editable = false)
//plotchar(isBearishTriggerWave and position == -1, "Long", "▼", location.abovebar,
color=c_bearish, size = size.small)

//plot(position == 1 and bullishCross ? low -5: na, title="Bullish Cross", style=

plot.style_circles, linewidth=2, color=c_bullish, offset=-1)
//plot(position == -1 and bullishCross ? low -5: na, title="Bullish Cross", style=
plot.style_cross, linewidth=2, color=c_bullish, offset=-1)
//plot(position == 1 and isBullishTriggerWave ? low -5 : na, title="Bullish Trigger
Cross", style=plot.style_circles, linewidth=3, color=c_bullish, offset=-1)
//plot(position == -1 and isBullishTriggerWave ? low -5 : na, title="Bullish
Trigger Cross", style=plot.style_cross, linewidth=3, color=c_bullish, offset=-1)

//plotchar(bullishCross and position == 1, "Long", "▲", location.belowbar, color =

c_bullish, size = size.tiny)
plotchar(bullishCross and position == -1, "Long", "✖", location.belowbar, color =
#ff7322, size = size.tiny, editable = false)
//plotchar(isBullishTriggerWave and position == 1, "Long", "▲", location.belowbar,
color=c_bullish, size = size.small)
plotchar(isBullishTriggerWave and position == -1, "Long", "✖", location.belowbar,
color=#ff7322, size = size.tiny, editable = false)

// Shit
atrMultiplier = input(2, title="ATR Multiplier")
boxHeightInAtr = atrMultiplier * ta.atr(10)

// Box TP 1

[lowb, midb, highb] = LAF.getTPSLBoxes(6.0)

if (takeProfitBoxes == 'On')
tp1box = box.new(left=bar_index + 1, top=close + midb, right=bar_index + 18,
bottom=close + lowb, border_color=color.new(#3666f5, 0), border_width=2,
border_style=line.style_solid, bgcolor=color.new(#3666f5, 55), text="TP/SL 1 : "
+ str.tostring(close), text_size=size.normal, text_color=color.new(#3666f5, 0))
bottom_tp1 = box.get_bottom(tp1box)
 box.delete(tp1box[1])

// Box TP 2
tp2box = box.new(left=bar_index + 1, top=close+highb, right=bar_index + 18,
bottom=close+midb, border_color=color.new(#3666f5, 0), border_width=2,
border_style=line.style_solid, bgcolor=color.new(#3666f5, 65), text="TP/SL 2 : "
+ str.tostring(close), text_size=size.normal, text_color=color.new(#3666f5, 0))
top_tp2 = box.get_top(tp2box)
box.delete(tp2box[1])
// Empty Box
newBox = box.new(left=bar_index + 18, top=top_tp2, right=bar_index + 200,
bottom=bottom_tp1, border_color=color.new(#3666f5, 0), border_width=2,
border_style=line.style_solid, bgcolor=color.new(#3666f5, 50), text=" ",
text_size=size.normal, text_color=color.new(#3666f5, 0))
box.delete(newBox[1])
// SL Box
slBox = box.new(left=bar_index + 3, top=close-lowb, right=bar_index + 18,
bottom=close-midb, border_color=color.new(color.red, 0), border_width=2,
border_style=line.style_solid, bgcolor=color.new(color.red, 66), text="TP/SL 2 :
" + str.tostring(close), text_size=size.normal, text_color=color.new(color.red, 0))
bottom_sl = box.get_top(slBox)
box.delete(slBox[1])

// SL2 Box
sl2Box = box.new(left=bar_index + 3, top=close-midb, right=bar_index + 18,
bottom=close-highb, border_color=color.new(color.red, 0), border_width=2,
border_style=line.style_solid, bgcolor=color.new(color.red, 65), text="TP/SL 1 :
" + str.tostring(close), text_size=size.normal, text_color=color.new(color.red, 0))
bottom_sl2 = box.get_bottom(sl2Box)
box.delete(sl2Box[1])

// Empty Box SL
Slboxem = box.new(left=bar_index + 18, top=bottom_sl, right=bar_index + 200,
bottom=bottom_sl2, border_color=color.new(color.red, 0), border_width=2,
border_style=line.style_solid, bgcolor=color.new(color.red, 50), text=" ",
text_size=size.normal, text_color=color.new(color.red, 0))
box.delete(Slboxem[1])
//
// Line tp Bottom
var line tpb = na
isLastBar = barstate.islast

if (isLastBar)
tpb := line.new(na, bottom_tp1, na, bottom_tp1, color=color.new(#3666f5,
0), width=2, style=line.style_dashed)

line.set_xy1(tpb, bar_index[50], bottom_tp1)

line.set_xy2(tpb, bar_index + 200, bottom_tp1)
line.delete(tpb[1])
// Line tp top
var line tp2Line = na

if (isLastBar)
tp2Line := line.new(na, top_tp2, na, top_tp2, color=color.new(#3666f5, 0),
width=2, style=line.style_dashed)

line.set_xy1(tp2Line, bar_index[50], top_tp2)

line.set_xy2(tp2Line, bar_index + 200, top_tp2)
line.delete(tp2Line[1])
 // Line SL
var line slLine = na

if (isLastBar)
slLine := line.new(na, bottom_sl, na, bottom_sl, color=color.new(color.red,
0), width=2, style=line.style_dashed)

line.set_xy1(slLine, bar_index[50], bottom_sl)

line.set_xy2(slLine, bar_index + 400, bottom_sl)
line.delete(slLine[1])
// Line SL2
var line sl2Line = na

if (isLastBar)
sl2Line := line.new(na, bottom_sl2, na, bottom_sl2,
color=color.new(color.red, 0), width=2, style=line.style_dashed)

line.set_xy1(sl2Line, bar_index[50], bottom_sl2)

line.set_xy2(sl2Line, bar_index + 200, bottom_sl2)
line.delete(sl2Line[1])

###################################################################################
###################################################################################
##################################################

// This Pine Script™ code is subject to the terms of the Mozilla Public License 2.0
at https://mozilla.org/MPL/2.0/
// © Pieki

//@version=5
// # ========================================================================= #
// # | Indicator |
// # ========================================================================= #
indicator(title = "[Pieki Algo] Signals And Overlays | [V.2.0]", shorttitle =
"Signals And Overlays", overlay = true, max_lines_count = 500, max_labels_count =
500, max_boxes_count = 500)

// # ============================[GET USERS INPUT]============================ #

// # ==== [BASIC SETTINGS]
gr_basic = "BASIC SETTINGS"
bullish = input.color(#51d6ff, "Bullish", inline = "0", group =
gr_basic, tooltip = "1")
bearish = input.color(#97a1a3, "Bearish", inline = "0", group =
gr_basic)
showsignals = input.bool(true, "Show Signals", inline = "1", group =
gr_basic, tooltip = "1")
sigsensiviti = input.float(4.238 , "???????????", inline = "1", step =
0.001, group = gr_basic)
candle = input.bool(true, "Coloring Candle", inline = "2", group =
gr_basic, tooltip = "1")
candlemod = input.string("Trend", "???????",["Trend"], inline = "2",
group = gr_basic)
signfilter = input.string("None", "Signal Filters??????????????????",
["None", "Trend Tracer", "Reversal Zones", "Cloud"], inline = "3", group =
gr_basic, tooltip = "1")
// # ==== [FEATURES]
gr_ft = "FEATURES"
trendtracer = input.bool(true, "Trend Tracer???????????", inline = "1",
group = gr_ft, tooltip = "1")
trendtracersens = input.int(2, "", minval = 1, inline = "1", group = gr_ft)
revzones = input.bool(true, "Reversal Zones????????", inline = "2",
group = gr_ft, tooltip = "1")
revzonessens = input.int(50, "", minval = 1, inline = "2", group =
gr_ft)
cloudshow = input.bool(false, "Cloud????????????????????", inline =
"3", group = gr_ft, tooltip = "1")
cloudsens = input.int(1, "", minval = 1, inline = "3", group = gr_ft)
trendlineshow = input.bool(false, "Trend Line??????????????", inline =
"4", group = gr_ft, tooltip = "1")
trendlinesens = input.int(14, "", minval = 2, inline = "4", group =
gr_ft)
smarttrailshow = input.bool(true, "Smart Trail?????????????", inline =
"5", group = gr_ft, tooltip = "1")
smarttrailsens = input.int(8, "", minval = 1, inline = "5", group = gr_ft)
// # ==== [SUPPORT AND RESISTANCE]
gr_sr = "SUPPORT AND RESISTANCE"
showSR = input.bool(true, "Support / Resistance", inline = "01", group
= gr_sr)
timef = input.timeframe("", "", inline = "01", group = gr_sr)
levelssr = input.int(7 , "Levels", inline = "02", group = gr_sr)
prd = input.int(10 , "Pivot Period", inline = "02", group = gr_sr)

// # ==== [DASHBOARD]
gr_dashboard = "DASHBOARD SETTINGS"
showDash = input(true, "Dashboard",group = gr_dashboard)
showDashtrend = input(true, "Trend Dashboard",group = gr_dashboard)
dashLoc = input.string("Bottom Right", "Location", options = ["Top
Right", "Bottom Right", "Bottom Left"], group = gr_dashboard)
textSize = input.string("Normal", "Size", options = ["Tiny",
"Small", "Normal"], group = gr_dashboard)
// # ==== [RISK MANAGEMENT]
gr_risk = "RISK Management"
levels = input.bool(false, "Show TP/SL Levels" , group = gr_risk ,
inline = "1")
dynamic_tp = input.bool(false, "Dynamic TP" , group = gr_risk , inline
= "1")
slrisk = input.int(1, "SL %", inline = "2", group = gr_risk)
tp1risk = input.int(1, "TP 1 %", inline = "3", group = gr_risk)
tp2risk = input.int(2, "TP 2 %", inline = "4", group = gr_risk)
tp3risk = input.int(3, "TP 3 %", inline = "5", group = gr_risk)
// # ==== [ALERTS]
gr_alert = "ALERT SETTINGS"
sigaler = input.bool(false, "Signals Alerts", inline = "1", group =
gr_alert, tooltip = "1")
trendtraceraalert = input.bool(false, "Trend Tracer", inline = "2", group =
gr_alert, tooltip = "1")
revzonesalert = input.bool(false, "Reversal Zones", inline = "3", group =
gr_alert, tooltip = "1")
cloudalert = input.bool(false, "Cloud", inline = "4", group =
gr_alert, tooltip = "1")

// # ============================[FUNCTIONS]============================ #
// # ==== [Trend Tracer]
// ATR
get_atr(i_length) =>
ta.atr(i_length)

atr = get_atr(5) * trendtracersens

// # ==== [REVERSAL ZONES]
// Kama
kama(ssrc, llen) =>
kama = 0.0
sum_1 = math.sum(math.abs(ssrc - ssrc[1]), llen)
sum_2 = math.sum(math.abs(ssrc - ssrc[1]), llen)
kama := nz(kama[1]) + math.pow((sum_1 != 0 ? math.abs(ssrc - ssrc[llen]) /
sum_2 : 0) * (0.288 - 0.0666) + 0.0666, 2) * (ssrc - nz(kama[1]))
sma_kama = ta.sma(kama, llen)
// # ==== [Cloud]
avg(src,length,mult)=>
atr = ta.atr(length)*mult
up = hl2 + atr
dn = hl2 - atr
upper = 0.,lower = 0.
upper := src[1] < upper[1] ? math.min(up,upper[1]) : up
lower := src[1] > lower[1] ? math.max(dn,lower[1]) : dn

os = 0,max = 0.,min = 0.
os := src > upper ? 1 : src < lower ? 0 : os[1]
spt = os == 1 ? lower : upper
max := ta.cross(src,spt) ? math.max(src,max[1]) : os == 1 ?
math.max(src,max[1]) : spt
min := ta.cross(src,spt) ? math.min(src,min[1]) : os == 0 ?
math.min(src,min[1]) : spt
math.avg(max,min)
// # ==== [SUPPORT RESISTANCE]
src_c = request.security(syminfo.tickerid,timef,close, gaps = barmerge.gaps_off,
lookahead = barmerge.lookahead_off)
src_o = request.security(syminfo.tickerid,timef,open, gaps = barmerge.gaps_off,
lookahead = barmerge.lookahead_off)
f_resInMinutes() =>
_resInMinutes = timeframe.multiplier * (timeframe.isseconds ? 1. / 60 :
timeframe.isminutes ? 1. : timeframe.isdaily ? 60. * 24 : timeframe.isweekly ? 60.
* 24 * 7 : timeframe.ismonthly ? 60. * 24 * 30.4375 : na)
_resInMinutes
f_timefResInMinutes(_res) =>
request.security(syminfo.tickerid, _res, f_resInMinutes())
f_timefIsIntraday(_res) =>
[intraday, daily, weekly, monthly] = request.security(syminfo.tickerid, _res,
[timeframe.isintraday, timeframe.isdaily, timeframe.isweekly, timeframe.ismonthly])
check = intraday ? "Intraday" : daily ? "Daily" : weekly ? "Weekly" : monthly ?
"Monthly" : "Error"
check
mtimef_multiplier = int (f_timefResInMinutes(timef) / f_resInMinutes())
// # ============================[GET COMPONENTS]============================ #
src = close
rsi = 14
// # ==== [SIGNALS]
rsi_smooth = 3 // RSI Smoothing for signals
wilders_Period = rsi * 2 - 1
sig_rsi = ta.rsi(src, rsi)
sig_ma_rsi = ta.ema(sig_rsi, rsi_smooth)
sig_atr_rsi = math.abs(sig_ma_rsi[1] - sig_ma_rsi)
sig_ma_atr_rsi = ta.ema(sig_atr_rsi, wilders_Period)
dar = ta.ema(sig_ma_atr_rsi, wilders_Period) * sigsensiviti
longband = 0.0
shortband = 0.0
trend1 = 0
DeltaFastAtrRsi = dar
RSIndex = sig_ma_rsi
newshortband = RSIndex + DeltaFastAtrRsi
newlongband = RSIndex - DeltaFastAtrRsi
longband := RSIndex[1] > longband[1] and RSIndex > longband[1] ?
math.max(longband[1], newlongband) : newlongband
shortband := RSIndex[1] < shortband[1] and RSIndex < shortband[1] ?
math.min(shortband[1], newshortband) : newshortband
cross_1 = ta.cross(longband[1], RSIndex)
trend1 := ta.cross(RSIndex, shortband[1]) ? 1 : cross_1 ? -1 :
nz(trend1[1], 1)
FastAtrRsiTL = trend1 == 1 ? longband : shortband
// Find all the QQE Crosses
QQExlong = 0
QQExlong := nz(QQExlong[1])
QQExshort = 0
QQExshort := nz(QQExshort[1])
QQExlong := FastAtrRsiTL < RSIndex ? QQExlong + 1 : 0
QQExshort := FastAtrRsiTL > RSIndex ? QQExshort + 1 : 0
//Conditions
qqeLong = QQExlong == 1 ? FastAtrRsiTL[1] - 50 : na
qqeShort = QQExshort == 1 ? FastAtrRsiTL[1] - 50 : na
// # ==== [TREND TRACER]
trend_length = 10 // ATR Period
lr_length = 20 // Linear Regression (LSMA)
lr_offset = 0 // Linear Regression (LSMA)
// Highest/Lowest of source
lower = ta.lowest(src, trend_length)
upper = ta.highest(src, trend_length)
if trendtracer
lower := ta.lowest(low, trend_length)
upper := ta.highest(high, trend_length)
// Trend direction
string direction = upper > upper[1] ? "up" : lower < lower[1] ? "down" : "neutral"
// Trend and signal variables
float trend = 0.0
string up_down_trend = na
bool trendtracer_buy = false
bool trendtracer_sell = false
// ATR trend logic
if direction == "up"
trend := low - atr
if trend < trend[1]
trend := trend[1]
if direction == "down"
trend := high + atr
if trend > trend[1]
trend := trend[1]
if direction == "neutral"
trend := trend[1]
// Buy/Sell signals
up_down_trend := up_down_trend[1]
if trend > trend[1]
up_down_trend := "up"
if trend < trend[1]
up_down_trend := "down"
// Buy/Sell Signals
trendtracer_buy := up_down_trend[1] == "down" and up_down_trend == "up" ? true :
false
trendtracer_sell := up_down_trend[1] == "up" and up_down_trend == "down" ? true :
false
// # ==== [REVERSAL ZONES]
rg = kama(ta.tr, revzonessens)
basis = kama(close, revzonessens)
upper1 = basis + rg * 9
upper2 = basis + rg * 11
upper3 = basis + rg * 14
lower1 = basis - rg * 9
lower2 = basis - rg * 11
lower3 = basis - rg * 14

revzonesbuy = ta.crossunder(high, lower1)

revzonessell = ta.crossover(low, upper1)
// # ==== [CLOUD]
offset = 1
tenkan = avg(close,9 + cloudsens,2)
kijun = avg(close,26 + cloudsens,4)
senkouA = math.avg(kijun,tenkan)
senkouB = avg(close,52,6)
cloud_buy = ta.crossover(senkouA,senkouB)
cloud_sell = ta.crossover(senkouB, senkouA)
// # ==== [TREND LINES]
var upper_tl = 0.
var lower_tl = 0.
var slope_ph = 0.
var slope_pl = 0.
var offset_tl = trendlineshow ? trendlinesens : 0
n = bar_index
ph = ta.pivothigh(trendlinesens, trendlinesens)
pl = ta.pivotlow(trendlinesens, trendlinesens)
slope = ta.atr(trendlinesens) / trendlinesens * 1
slope_ph := ph ? slope : slope_ph
slope_pl := pl ? slope : slope_pl
upper_tl := ph ? ph : upper_tl - slope_ph
lower_tl := pl ? pl : lower_tl + slope_pl
var upos = 0
var dnos = 0
upos := ph ? 0 : close > upper_tl - slope_ph * trendlinesens ? 1 : upos
dnos := pl ? 0 : close < lower_tl + slope_pl * trendlinesens ? 1 : dnos
// # ==== [SUPERTREND]
[supertrend, direction1] = ta.supertrend(math.round(math.avg(6, smarttrailsens)),
34 * 2)
hullup = ta.hma(high, math.round(math.avg(21, 34))) + ta.atr(100) *
math.round(smarttrailsens / 2.5)
hulldown = ta.hma(low, math.round(math.avg(21, 34))) - ta.atr(100) *
math.round(smarttrailsens / 2.5)
hline = ta.highest(close, 34) + ta.atr(100)
lline = ta.lowest(close, 34) + ta.atr(100)
supert = 0.0
supert := if close > supertrend
math.avg(supertrend, supertrend, supertrend, hulldown, lline)
else if close < supertrend
math.avg(supertrend, supertrend, supertrend, hullup, hline)
supert2 = 0.0
supert2 := if close > supert
supert + ta.atr(100) * 1
else if close < supert
supert - ta.atr(100) * 1

smoothedSupert = ta.sma(supert, 2)
smoothedSupert2 = ta.sma(supert2,2)
tool = direction1 > 0 or direction1 < 0
// # ==== [RSI]
ma(x, len) => ta.rma(x, len)
upperr = ta.highest(src, rsi)
lowerr = ta.lowest(src, rsi)
r = upperr - lowerr
d = src - src[1]
dif = upperr > upperr[1] ? r
: lowerr < lowerr[1] ? -r
: d
num = ma(dif, rsi)
den = ma(math.abs(dif), rsi)
arsi = math.min(num / den * 50 + 50,100)
// # ==== [VOLUME]
volback = 13
up_bar = close > hl2
dn_bar = close < hl2
u_vol = up_bar ? volume : 0
d_vol = dn_bar ? volume : 0
up_vol = math.sum(u_vol, volback)
dn_vol = math.sum(d_vol, volback)
vol = math.min(100 * (up_vol - dn_vol) / (up_vol + dn_vol),100)
// # ==== [SQUEEZE]
var max = 0.0
var min = 0.0
max := nz(math.max(src, max - (max - src) / 50), src)
min := nz(math.min(src, min + (src - min) / 50), src)
diff = math.log(max - min)
// # ==== [MONEY FLOW]
mf = math.min(ta.mfi(src, 14),100)
// # ==== [ADX]
up = ta.change(high)
down = -ta.change(low)
trur = ta.rma(ta.tr, 14)
plus = fixnan(100 * ta.rma(up > down and up > 0 ? up : 0, 14) / trur)
minus = fixnan(100 * ta.rma(down > up and down > 0 ? down : 0, 14) / trur)
sum = plus + minus
adx = 100 * ta.rma(math.abs(plus - minus) / (sum == 0 ? 1 : sum), 14)
// # ==== [TREND DETECTOR MTF]
ema = ta.ema(close, 144)
emaBull = close > ema
trend_5m = request.security(syminfo.tickerid, "5" , emaBull)
trend_15m = request.security(syminfo.tickerid, "15" , emaBull)
trend_30m = request.security(syminfo.tickerid, "30" , emaBull)
trend_1h = request.security(syminfo.tickerid, "60" , emaBull)
trend_4h = request.security(syminfo.tickerid, "240" , emaBull)
trend_1d = request.security(syminfo.tickerid, "1440", emaBull)
// # ==== [RISK MANAGEMENT]
trigger2 = qqeLong ? 1 : 0
countBull = ta.barssince(qqeLong)
countBear = ta.barssince(qqeShort)
trigger = nz(countBull, bar_index) < nz(countBear, bar_index) ? 1 : 0

slatr = ta.atr(14) * slrisk

slris = trigger == 1 ? low - slatr : high + slatr

tp1atr = ta.atr(14) * tp1risk

tp1ris = trigger == 1 ? low - tp1atr : high + tp1atr

tp2atr = ta.atr(14) * tp2risk

tp2ris = trigger == 1 ? low - tp2atr : high + tp2atr

tp3atr = ta.atr(14) * tp3risk

tp3ris = trigger == 1 ? low - tp3atr : high + tp3atr

lastTrade(close) => ta.valuewhen(qqeLong or qqeShort , close, 0)

// # ==== [SUPPORT AND RESISTANCE]
maxnumpp = 284
ChannelW = 10
min_strength = 2
prd := prd * mtimef_multiplier
float src1 = math.max(src_c, src_o)
float src2 = math.min(src_c, src_o)
float src3 = math.max(close, open)
float src4 = math.min(close, open)
float ph6 = ta.pivothigh(src1, prd, prd)
float pl6 = ta.pivotlow(src2, prd, prd)
Lstyle = line.style_solid
timef_res = f_timefIsIntraday(timef)
timef_text = str.tostring(timef)

// # ============================[PLOTTING]============================ #
// # ==== [SIGNALS]
// Normal
y1 = low - (ta.atr(30) * 2), y1B = low - ta.atr(30)
y2 = high + (ta.atr(30) * 2), y2B = high + ta.atr(30)
buy = qqeLong and showsignals and signfilter == "None" ? label.new(bar_index, y1,
"^", xloc.bar_index, yloc.price, bullish, label.style_label_up, color.white,
size.normal) : na
sell = qqeShort and showsignals and signfilter == "None"? label.new(bar_index, y2,
"¡", xloc.bar_index, yloc.price, bearish, label.style_label_down, color.white,
size.normal) : na
// Trend Tracer
trendtracer_b = trendtracer_buy and showsignals and signfilter == "Trend Tracer" ?
label.new(bar_index, y1, "^", xloc.bar_index, yloc.price, bullish,
label.style_label_up, color.white, size.normal) : na
trendtracer_s = trendtracer_sell and showsignals and signfilter == "Trend Tracer"?
label.new(bar_index, y2, "¡", xloc.bar_index, yloc.price, bearish,
label.style_label_down, color.white, size.normal) : na
// Reversal zones
revzones_s = revzonessell and showsignals and signfilter == "Reversal Zones" ?
label.new(bar_index, y2, "¡", xloc.bar_index, yloc.price, bearish,
label.style_label_down, color.white, size.normal) : na
revzones_b = revzonesbuy and showsignals and signfilter == "Reversal Zones" ?
label.new(bar_index, y1, "^", xloc.bar_index, yloc.price, bullish,
label.style_label_up, color.white, size.normal) : na
// Cloud
cloud_buy1 = cloud_buy and showsignals and signfilter == "Cloud" ?
label.new(bar_index, y1, "^", xloc.bar_index, yloc.price, bullish,
label.style_label_up, color.white, size.normal) : na
cloud_sell1 = cloud_sell and showsignals and signfilter == "Cloud" ?
label.new(bar_index, y2, "¡", xloc.bar_index, yloc.price, bearish,
label.style_label_down, color.white, size.normal) : na
// # ==== [TREND TRACER]
p1 = plot(trendtracer ? trend : na, "ATR Trend", color = up_down_trend == "up" ?
bullish : bearish, linewidth = 2, editable = false)
// # ==== [TREND TRACER]
pp1 = plot(revzones ? upper1 : na, transp=100, editable = false)
pp2 = plot(revzones ? upper2 : na, transp=100, editable = false)
pp3 = plot(revzones ? upper3 : na, transp=100, editable = false)
pp4 = plot(revzones ? lower1 : na, transp=100, editable = false)
pp5 = plot(revzones ? lower2 : na, transp=100, editable = false)
pp6 = plot(revzones ? lower3 : na, transp=100, editable = false)
fill(pp1, pp2, color=color.new(bearish, 70), editable = false)
fill(pp2, pp3, color=color.new(bearish, 50), editable = false)
fill(pp4, pp5, color=color.new(bullish, 70), editable = false)
fill(pp5, pp6, color=color.new(bullish, 50), editable = false)
// # ==== [CLOUD]
A = plot(cloudshow ? senkouA : na,'Senkou Span A',na,offset=offset-1, editable =
false)
B = plot(cloudshow ? senkouB : na,'Senkou Span B',na,offset=offset-1, editable =
false)
fill(A,B,senkouA > senkouB ? color.new(bullish, 80) : color.new(bearish,80))
// # ==== [TREND LINES]
var uptl = trendlineshow ? line.new(na,na,na,na, color = bullish, style =
line.style_dashed, extend = extend.right) : na
var dntl = trendlineshow ? line.new(na,na,na,na, color = bearish, style =
line.style_dashed, extend = extend.right) : na

if ph and trendlineshow
uptl.set_xy1(n-offset_tl, trendlineshow ? ph : upper_tl - slope_ph *
trendlinesens)
uptl.set_xy2(n-offset_tl+1, trendlineshow ? ph - slope : upper_tl - slope_ph *
(trendlinesens+1))

if pl and trendlineshow
dntl.set_xy1(n-offset_tl, trendlineshow ? pl : lower_tl + slope_pl *
trendlinesens)
dntl.set_xy2(n-offset_tl+1, trendlineshow ? pl + slope : lower_tl + slope_pl *
(trendlinesens+1))
// # ==== [SMART TRAIL]
tool12 = plot(smarttrailshow ? ((direction1 < 0 and direction1[1] < 0) or
(direction1 > 0 and direction1[1] > 0) ? smoothedSupert : na) : na, "Extreme line",
color=smarttrailshow ? (close > ((direction1 < 0 and direction1[1] < 0) or
(direction1 > 0 and direction1[1] > 0) ? smoothedSupert : na) ? bullish :
bearish) : na, style=plot.style_linebr, editable = false)
tool2 = plot(smarttrailshow ? (tool ? smoothedSupert2 : na) : na, "Zone line",
color=color.new(color.gray, 100), display=smarttrailshow ? display.none :
display.none, editable=false, style=plot.style_linebr, editable = false)
fill(tool12, tool2, color=close > supert ? color.new(bullish, 80) :
color.new(bearish, 80), fillgaps=false)
lineColor = close > supertrend ? bullish : close < supertrend ? bearish : na
plot(smarttrailshow ? ((direction1 < 0 and direction1[1] < 0) or (direction1 > 0
and direction1[1] > 0) ? smoothedSupert : na) : na, color=smarttrailshow ?
lineColor : na, linewidth=2, style=smarttrailshow ? plot.style_line :
plot.style_line, title="Trend Area Line", editable = false)
// # ==== [COLORING CANDLE]
barcolor(QQExlong ? bullish : bearish)
// # ==== [RISK MANAGEMENT]
entry = levels ? label.new(time, close, "ENTRY | " +
str.tostring(lastTrade(close), "#.####"), xloc.bar_time, yloc.price, #00e2ff,
label.style_none, color.white, size.normal) : na
label.set_x(entry, label.get_x(entry) + math.round(ta.change(time) * 10))
label.set_y(entry, lastTrade(close))
label.delete(entry[1])

stop_y = lastTrade(slris)
stop = levels ? label.new(time, close, "SL | " + str.tostring(stop_y, "#.####"),
xloc.bar_time, yloc.price, bearish, label.style_none, color.white, size.normal) :
na
label.set_x(stop, label.get_x(stop) + math.round(ta.change(time) * 10))
label.set_y(stop, stop_y)
label.delete(stop[1])

tp1Rl_y = (lastTrade(close)-lastTrade(tp1ris)) + lastTrade(close)

tp1Rl = levels ? label.new(time, close, "TP 1 | " + str.tostring(tp1Rl_y,
"#.####"), xloc.bar_time, yloc.price, bullish, label.style_none, color.white,
size.normal ) : na
label.set_x(tp1Rl, label.get_x(tp1Rl) + math.round(ta.change(time) * 10))
label.set_y(tp1Rl, tp1Rl_y)
label.delete(tp1Rl[1])

tp2RL_y = (lastTrade(close)-lastTrade(tp2ris)) + lastTrade(close)

tp2RL = levels ? label.new(time, close, "TP 2 | " + str.tostring(tp2RL_y,
"#.####"), xloc.bar_time, yloc.price, bullish, label.style_none, color.white,
size.normal) : na
label.set_x(tp2RL, label.get_x(tp2RL) + math.round(ta.change(time) * 10))
label.set_y(tp2RL, tp2RL_y)
label.delete(tp2RL[1])

tp3RL_y = (lastTrade(close)-lastTrade(tp3ris)) + lastTrade(close)

tp3RL = levels ? label.new(time , close , "TP 3 | " + str.tostring(tp3RL_y,
"#.####"), xloc.bar_time, yloc.price, bullish, label.style_none, color.white,
size.normal) : na
label.set_x(tp3RL, label.get_x(tp3RL) + math.round(ta.change(time) * 10))
label.set_y(tp3RL, tp3RL_y)
label.delete(tp3RL[1])

lineEntry = levels ? line.new(bar_index - (trigger == 0 ? countBull : countBear),

lastTrade(close), bar_index + 10, lastTrade(close), xloc.bar_index, extend.none,
color.yellow, line.style_solid, 2) : na, line.delete(lineEntry[1])
lineStop = levels ? line.new(bar_index - (trigger == 0 ? countBull : countBear),
stop_y, bar_index + 10, stop_y, xloc.bar_index, extend.none, bearish,
line.style_solid, 2) : na, line.delete(lineStop[1])
lineTp1Rl = levels ? line.new(bar_index - (trigger == 0 ? countBull : countBear),
tp1Rl_y, bar_index + 10, tp1Rl_y, xloc.bar_index, extend.none, bullish,
line.style_solid, 2) : na, line.delete(lineTp1Rl[1])
lineTp2RL = levels ? line.new(bar_index - (trigger == 0 ? countBull : countBear),
tp2RL_y, bar_index + 10, tp2RL_y, xloc.bar_index, extend.none, bullish,
line.style_solid, 2) : na, line.delete(lineTp2RL[1])
lineTp3RL = levels ? line.new(bar_index - (trigger == 0 ? countBull : countBear),
tp3RL_y, bar_index + 10, tp3RL_y, xloc.bar_index, extend.none, bullish,
line.style_solid, 2) : na, line.delete(lineTp3RL[1])

// Dynamic TP
rsi_tp = ta.rsi(close ,14)
tpLabels(tp) =>
tp1Bull = ta.crossover (rsi_tp, 70), tp2Bull = ta.crossover (rsi_tp, 75),
tp3Bull = ta.crossover (rsi_tp, 80)
tp1Bear = ta.crossunder(rsi_tp, 30), tp2Bear = ta.crossunder(rsi_tp, 25),
tp3Bear = ta.crossunder(rsi_tp, 20)
tp1Bull := tp1Bull and (nz(ta.barssince(tp1Bull)[1], 9999) > countBull),
tp2Bull := tp2Bull and (ta.barssince(tp1Bull)[1] <= countBull), tp2Bull := tp2Bull
and (nz(ta.barssince(tp2Bull)[1], 9999) > countBull), tp3Bull := tp3Bull and
(ta.barssince(tp2Bull)[1] <= countBull), tp3Bull := tp3Bull and
(nz(ta.barssince(tp3Bull)[1], 9999) > countBull)
tp1Bear := tp1Bear and (nz(ta.barssince(tp1Bear)[1], 9999) > countBear),
tp2Bear := tp2Bear and (ta.barssince(tp1Bear)[1] <= countBear), tp2Bear := tp2Bear
and (nz(ta.barssince(tp2Bear)[1], 9999) > countBear), tp3Bear := tp3Bear and
(ta.barssince(tp2Bear)[1] <= countBear), tp3Bear := tp3Bear and
(nz(ta.barssince(tp3Bear)[1], 9999) > countBear)

if dynamic_tp
trigger ? (tp == 1 ? tp1Bull : tp == 2 ? tp2Bull : tp3Bull) : (tp == 1 ?
tp1Bear : tp == 2 ? tp2Bear : tp3Bear)

plotshape(tpLabels(1), "", shape.xcross, location.abovebar, trigger ?

color.yellow : na , 0, "TP 1", trigger ? color.yellow : na , false)
plotshape(tpLabels(2), "", shape.xcross, location.abovebar, trigger ?
color.yellow : na , 0, "TP 2", trigger ? color.yellow : na , false)
plotshape(tpLabels(3), "", shape.xcross, location.abovebar, trigger ?
color.yellow : na , 0, "TP 3", trigger ? color.yellow : na , false)
plotshape(tpLabels(1), "", shape.xcross, location.belowbar, trigger ? na :
color.yellow, 0, "TP 1", trigger ? na : color.yellow, false)
plotshape(tpLabels(2), "", shape.xcross, location.belowbar, trigger ? na :
color.yellow, 0, "TP 2", trigger ? na : color.yellow, false)
plotshape(tpLabels(3), "", shape.xcross, location.belowbar, trigger ? na :
color.yellow, 0, "TP 3", trigger ? na : color.yellow, false)

// # ==== [SUPPORT RESISTANCE]

if str.tostring(timef) == ""
timef_text := na(timeframe.multiplier / 60) ? timeframe.period :
timeframe.multiplier < 60 ? timeframe.period + " M |" :
str.tostring(timeframe.multiplier / 60) + " H |"
else if timef_res == "Intraday"
timef_text := na(str.tonumber(timef) / 60) ? str.tostring(timef) :
str.tonumber(timef) < 60 ? str.tostring(timef) + " M |" :
str.tostring(str.tonumber(timef) / 60) + " H |"
else
timef_text := str.tostring(timef)
//calculate maximum S/R channel zone width
prdhighest = request.security(syminfo.tickerid, timef, ta.highest(300))
prdlowest = request.security(syminfo.tickerid, timef, ta.lowest(300))
cwidth = (prdhighest - prdlowest) * ChannelW / 100
var pivotvals = array.new_float(0)
if ph6 or pl6
array.unshift(pivotvals, ph6 ? ph6 : pl6)
if array.size(pivotvals) > maxnumpp // limit the array size
array.pop(pivotvals)
get_sr_vals(ind) =>
float lo = array.get(pivotvals, ind)
float hi = lo
int numpp = 0
for y = 0 to array.size(pivotvals) - 1 by 1
float cpp = array.get(pivotvals, y)
float wdth = cpp <= lo ? hi - cpp : cpp - lo
if wdth <= cwidth // fits the max channel width?
 lo := cpp <= lo ? cpp : lo
hi := cpp > lo ? cpp : hi
numpp += 1
numpp
[hi, lo, numpp]
var sr_up_level = array.new_float(0)
var sr_dn_level = array.new_float(0)
sr_strength = array.new_float(0)

find_loc(strength) =>
ret = array.size(sr_strength)
for i = ret > 0 ? array.size(sr_strength) - 1 : na to 0 by 1
if strength <= array.get(sr_strength, i)
break
ret := i
ret
ret

check_sr(hi, lo, strength) =>

ret = true
for i = 0 to array.size(sr_up_level) > 0 ? array.size(sr_up_level) - 1 : na by
1
//included?
if array.get(sr_up_level, i) >= lo and array.get(sr_up_level, i) <= hi or
array.get(sr_dn_level, i) >= lo and array.get(sr_dn_level, i) <= hi
if strength >= array.get(sr_strength, i)
array.remove(sr_strength, i)
array.remove(sr_up_level, i)
array.remove(sr_dn_level, i)
ret
else
ret := false
ret
break
ret

var sr_lines = array.new_line(11, na)

var sr_labels = array.new_label(11, na)
var timef_labels = array.new_label(11, na)

if ph6 or pl6
//because of new calculation, remove old S/R levels
array.clear(sr_up_level)
array.clear(sr_dn_level)
array.clear(sr_strength)
//find S/R zones
for x = 0 to array.size(pivotvals) - 1 by 1
[hi, lo, strength] = get_sr_vals(x)
if check_sr(hi, lo, strength)
loc = find_loc(strength)
// if strength is in first levels sr then insert it to the arrays
if loc < levelssr and strength >= min_strength
array.insert(sr_strength, loc, strength)
array.insert(sr_up_level, loc, hi)
array.insert(sr_dn_level, loc, lo)
// keep size of the arrays = 5
if array.size(sr_strength) > levelssr
array.pop(sr_strength)
array.pop(sr_up_level)
 array.pop(sr_dn_level)

for x = 1 to 10 by 1
line.delete(array.get(sr_lines, x))
label.delete(array.get(sr_labels, x))
label.delete(array.get(timef_labels, x))

for x = 0 to array.size(sr_up_level) > 0 ? array.size(sr_up_level) - 1 : na by

1
float mid = math.round_to_mintick((array.get(sr_up_level, x) +
array.get(sr_dn_level, x)) / 2)
if showSR
array.set(sr_lines, x + 1, line.new(x1=bar_index, y1=mid, x2=bar_index
- 1, y2=mid, extend=extend.both, color=mid >= close ? color.new(bearish, 75) :
color.new(bullish, 75), style=Lstyle, width=1 * 20))
if showSR
array.set(sr_labels, x + 1, label.new(x=bar_index + 40, y=mid,
text=(showSR ? timef_text : na) + (showSR ? (" " + str.tostring(mid)) : na),
color=mid >= close ? #ff525200 : #00e67700, textcolor=color.rgb(184, 184, 184),
size = size.normal, style=label.style_label_left))
// # ============================[DASHBOARD]============================ #
// # ==== [RSI]
rsiemo = arsi > 50 ? '??' : arsi < 30 ? '??' : '??'
bgrsi = arsi >= 80 ? color.new(bearish,60) : arsi >= 50 ? color.new(bearish,80) :
arsi >= 20 ? color.new(bullish,80) : color.new(bullish,60)
txtrsi = arsi >= 80 ? color.new(bearish,30) : arsi >= 50 ? color.new(bearish,10) :
arsi >= 20 ? color.new(bullish,10) : color.new(bullish,30)
// # ==== [VOLUME]
volemo = vol > 50 ? '??' : vol < 30 ? '??' : '??'
bgvol = vol >= 80 ? color.new(bullish, 60) : vol >= 50 ? color.new(bullish, 80) :
vol >= 20 ? color.new(bearish, 80) : color.new(bearish, 60)
txtvol = vol >= 80 ? color.new(bullish, 30) : vol >= 50 ? color.new(bullish, 10) :
vol >= 20 ? color.new(bearish, 10) : color.new(bearish, 30)
// # ==== [SQUEEZE]
squeeze = -50 * ta.correlation(diff, bar_index, 20) + 50
bgsqueeze = squeeze >= 80 ? color.new(bullish, 60) : squeeze >= 50 ?
color.new(bullish, 80) : squeeze >= 20 ? color.new(bearish, 80) :
color.new(bearish, 60)
txtsqueeze = squeeze >= 80 ? color.new(bullish,30) : squeeze >= 50 ?
color.new(bullish,10) : squeeze >= 20 ? color.new(bearish,10) :
color.new(bearish,30)
// # ==== [MONEY FLOW]
mfemo= mf > 50 ? "??" : "??"
bgmf = mf >= 80 ? color.new(bullish, 60) : mf >= 50 ? color.new(bullish, 80) : mf
>= 20 ? color.new(bearish, 80) : color.new(bearish, 60)
txtmf = mf >= 80 ? color.new(bullish, 30) : mf >= 50 ? color.new(bullish, 10) : mf
>= 20 ? color.new(bearish, 10) : color.new(bearish, 30)
// # ==== [ADX]
adxemo= adx > 50 ? "??" : "??"
bgadx = adx >= 80 ? color.new(bullish, 60) : adx >= 50 ? color.new(bullish, 80) :
adx >= 20 ? color.new(bearish, 80) : color.new(bearish, 60)
txtadx = adx >= 80 ? color.new(bullish, 30) : adx >= 50 ? color.new(bullish, 10) :
adx >= 20 ? color.new(bearish, 10) : color.new(bearish, 30)
// # ==== [DRAWING TREND DASHBOARD]
var table_position = dashLoc == 'Bottom Left' ? position.bottom_left
: dashLoc == 'Top Right' ? position.top_right
: position.bottom_right
var table_size = textSize == 'Tiny' ? size.tiny
: textSize == 'Small' ? size.small
 : size.normal
var tbmtf = table.new(position.top_right, 7, 7
, bgcolor = #1e222d
, border_color = #373a46
, border_width = 1
, frame_color = #373a46
, frame_width = 1)
if showDashtrend
if barstate.islast
tbmtf.cell(1, 1,"5M", text_color = trend_5m ? color.new(bullish,30) :
color.new(bearish,30), text_size = table_size, text_halign = text.align_left,
bgcolor = trend_5m ? color.new(bullish,60) : color.new(bearish,60))
tbmtf.cell(2, 1,"15M", text_color = trend_15m ? color.new(bullish,30) :
color.new(bearish,30), text_size = table_size, text_halign = text.align_left,
bgcolor = trend_15m ? color.new(bullish,60) : color.new(bearish,60))
tbmtf.cell(3, 1,"30M", text_color = trend_30m ? color.new(bullish,30) :
color.new(bearish,30), text_size = table_size, text_halign = text.align_left,
bgcolor = trend_30m ? color.new(bullish,60) : color.new(bearish,60))
tbmtf.cell(4, 1,"1H", text_color = trend_1h ? color.new(bullish,30) :
color.new(bearish,30), text_size = table_size, text_halign = text.align_left,
bgcolor = trend_1h ? color.new(bullish,60) : color.new(bearish,60))
tbmtf.cell(5, 1,"4H", text_color = trend_4h ? color.new(bullish,30) :
color.new(bearish,30), text_size = table_size, text_halign = text.align_left,
bgcolor = trend_4h ? color.new(bullish,60) : color.new(bearish,60))
tbmtf.cell(6, 1,"1D", text_color = trend_1d ? color.new(bullish,30) :
color.new(bearish,30), text_size = table_size, text_halign = text.align_left,
bgcolor = trend_1d ? color.new(bullish,60) : color.new(bearish,60))
// # ==== [DRAWING DASHBOARD]
var tb = table.new(table_position, 7, 7
, bgcolor = #1e222d
, border_color = #373a46
, border_width = 2
, frame_color = #373a46
, frame_width = 1)

if showDash
if barstate.islast
tb.cell(1, 1, str.tostring(rsiemo) + " RSI", text_color
=color.white, text_size = table_size, text_halign = text.align_left)
tb.cell(1, 2, str.tostring(volemo) + " Volume Sentiment" , text_color
=color.white, text_size = table_size, text_halign = text.align_left)
tb.cell(1, 3, "?? Squeeze" , text_color
=color.white, text_size = table_size, text_halign = text.align_left)
tb.cell(1, 4, str.tostring(mfemo) + " Money Flow" , text_color =
color.white, text_size = table_size, text_halign = text.align_left)
tb.cell(1, 5, str.tostring(adxemo) + " ADX" , text_color
=color.white, text_size = table_size, text_halign = text.align_left)
tb.cell(2, 1, str.tostring(arsi, format.percent), text_color =
txtrsi, text_size = table_size, bgcolor = bgrsi)
tb.cell(2, 2, str.tostring(vol, format.percent), text_color =
txtvol, text_size = table_size, bgcolor = bgvol)
tb.cell(2, 3, str.tostring(squeeze, format.percent), text_color =
txtsqueeze, text_size = table_size, bgcolor = bgsqueeze)
tb.cell(2, 4, str.tostring(mf, format.percent) , text_color = txtmf,
text_size = table_size, bgcolor = bgmf)
tb.cell(2, 5, str.tostring(adx, format.percent), text_color =
txtadx, text_size = table_size, bgcolor = bgadx)

// # ============================[Alerts]============================ #
// Signals Normal
alertcondition(sigaler ? qqeLong : na, "New Signal", message = "New Buy Signal |
Normal")
alertcondition(sigaler ? qqeShort : na, "New Signal", message = "New Sell Signal |
Normal")
// Signals Trend Tracer
alertcondition(trendtraceraalert ? trendtracer_buy : na, title="New Signal",
message = "New Buy Signal | Trend Tracer")
alertcondition(trendtraceraalert ? trendtracer_sell : na, title="New Signal",
message = "New Sell Signal | Trend Tracer")
// Signals Reversal Zones
alertcondition(revzonesalert ? revzonesbuy : na, title="New Signal", message = "New
Buy Signal | Reversal Zones")
alertcondition(revzonesalert ? revzonessell : na, title="New Signal", message =
"New Sell Signal | Reversal Zones")
// Signals Cloud
alertcondition(cloudalert ? cloud_buy : na, title="New Signal", message = "New Buy
Signal | Cloud")
alertcondition(cloudalert ? cloud_sell : na, title="New Signal", message = "New
Sell Signal | Cloud")

###################################################################################
###################################################################################
##################################################

//@version=5
indicator("LuxAlgo Signals & Overlays", "LuxAlgo Signals & Overlays™", overlay =
true, max_labels_count = 500)

//Import libraries
//Import libraries
import ayvaliktrading/EyopsTelegram/1 as LAF
import ayvaliktrading/JoinUsEyopsTelegram/1 as kernels

// # ============================[GET USERS INPUT]============================ #

groupBasic = "BASIC SETTINGS"
showSignals = input(true, "Show Signals", inline = "1", group = groupBasic, tooltip
= "Enables or disables the signals")
signalPresets = input.string("None", "Presets / Filters", ["None", "Trend Trader
[Preset]","Scalper [Preset]", "Swing Trader [Preset]", "Contrarian Trader
[Preset]", "Smart Trail [Filter]", "Trend Tracer [Filter]", "Trend Strength
[Filter]", "Trend Catcher [Filter]", "Neo Cloud [Filter]"],tooltip = "Automatically
sets settings or filters for a given category", group= groupBasic)
signalMode = input.string("Confirmation + Exits", "Signal Mode", ["Confirmation +
Exits", "Contrarian + Exits", "None"],tooltip = "Changes the Mode of the
signals" ,group = groupBasic)
signalClassifier = input(true,"AI Signal Classifer",tooltip = "Shows signal quality
from 1-4 on signals" ,group = groupBasic)
sensitivity = input.float(5, "Signal Sensitivity ", minval = 1, maxval =
26,step=1, tooltip = "Changes the sensetivity of the signals, the lower this
setting the more short term signals you will get, while a higher number will result
in longer term signals.",group = groupBasic)
atrLength = input.int(10, "Signal Tuner ", minval = 1, maxval = 25,step=1,tooltip
= "Alows you to tune your signals, the higher the number the more refined but
laggier the signal" ,group = groupBasic)
candleColorType = input.string("Confirmation Simple", "Candle Coloring",
["Confirmation Simple","Confirmation Gradient","Contrarian
Gradient","None"],tooltip = "Changes the type of signal coloring", group =
groupBasic)

// Indicator Overlay Settings

groupOverlay = "INDICATOR OVERLAY"
smartTrail = input(true, "Smart Trail", inline = "1", group = groupOverlay)
trendCatcher = input(false, "Trend Catcher", inline = "2", group = groupOverlay)
neoCloud = input(false, "Neo Cloud", inline = "3", group = groupOverlay)
reversalZone = input(true, "Reversal Zones", inline = "1", group = groupOverlay)
trendTracer = input(false, "Trend Tracer", inline = "2", group = groupOverlay)
showDashboard = input(true, "Dashboard", inline = "3", group = groupOverlay)
showTrailingStoploss = input(false, "Trailing Stoploss", inline = "4", group =
groupOverlay)
showMovingAverage = input(false, "AI Moving Average", inline = "4", group =
groupOverlay)
showSessions = input(false, "Sessions", inline = "5", group = groupOverlay)

// Advanced Settings
groupAdvanced = "ADVANCED SETTINGS"
takeProfitBoxes = input.string("Off", "TP/SL Points", options=["Off","On"], inline
= "2", tooltip = "Shows Take Profit and Stop Loss areas",group = groupAdvanced)
takeProfitStopLossDistance = input.int(5,"", minval = 1, maxval = 10, inline = "2",
group=groupAdvanced)
autopilotMode = input.string("Off", "Autopilot Sensivity",["Off","Short-Term",
"Mid-Term", "Long-Term"],tooltip = "Sets automatic settings for signals and
improves their quality" ,inline = "3", group = groupAdvanced)
dashboardLocation = input.string("Bottom Right","Dashboard Location", ["Top
Right","Bottom Right","Bottom Left"], inline = "4",tooltip = "Changes dashboard
positions" ,group = groupAdvanced)
dashboardSize = input.string("Normal","Dashboard Size",
["Tiny","Small","Normal","Large"], inline = "5",tooltip = "Changes the size of the
dashboard" ,group = groupAdvanced)

if (signalPresets == "Trend Trader [Preset]")

smartTrail := true
trendCatcher := true
neoCloud := true
trendTracer := true
smartTrail := true
if (signalPresets == "Scalper [Preset]")
sensitivity := 4
smartTrail := true
trendTracer := true
candleColorType := "Confirmation Gradient"
if (signalPresets == "Swing Trader [Preset]")
sensitivity := 18
neoCloud := true
candleColorType := "Confirmation Simple"
if (signalPresets == "Contrarian Trader [Preset]")
reversalZone := true
smartTrail := true
candleColorType := "Contrarian Gradient"

n = bar_index
// # ============================[BUY/SELL SIGNALS]============================ #
//------------------------------------------------------------------------------
//Settings
//-----------------------------------------------------------------------------{
//-----------------------------------------------------------------------------}

// # ============================[SESSIONS]============================ #
show_sesa = true
sesa_txt = 'New York'
sesa_ses = '1300-2200'
sesa_css = #ff5d00

sesa_range = true
sesa_tl = false
sesa_avg = false
sesa_vwap = false
sesa_maxmin = false

//Session B
show_sesb = true
sesb_txt = 'London'
sesb_ses = '0700-1600'
sesb_css = #2157f3

sesb_range = true
sesb_tl = false
sesb_avg = false
sesb_vwap = false
sesb_maxmin = false

//Timezones
tz_incr = 0
use_exchange = false

//Ranges Options
bg_transp = 90
show_outline = true
show_txt = true

//Dashboard
show_ses_div = false
show_day_div = false

//-----------------------------------------------------------------------------}
//Functions
//-----------------------------------------------------------------------------{

//Get session average

get_avg(session)=>
var len = 1
var float csma = na
var float sma = na

if session > session[1]

len := 1
 csma := close

if session and session == session[1]

len += 1
csma += close
sma := csma / len

sma

//Get trendline coordinates

get_linreg(session)=>
var len = 1
var float cwma = na
var float csma = na
var float csma2 = na

var float y1 = na
var float y2 = na
var float stdev = na
var float r2 = na

if session > session[1]

len := 1
cwma := close
csma := close
csma2 := close * close

if session and session == session[1]

len += 1
csma += close
csma2 += close * close
cwma += close * len

sma = csma / len

wma = cwma / (len * (len + 1) / 2)

cov = (wma - sma) * (len+1)/2

stdev := math.sqrt(csma2 / len - sma * sma)
r2 := cov / (stdev * (math.sqrt(len*len - 1) / (2 * math.sqrt(3))))

y1 := 4 * sma - 3 * wma
y2 := 3 * wma - 2 * sma

[y1 , y2, stdev, r2]

//Session Vwap
get_vwap(session) =>
var float num = na
var float den = na

if session > session[1]

num := close * volume
den := volume

else if session and session == session[1]

num += close * volume
den += volume
else
num := na
 [num, den]

//Set line
set_line(session, y1, y2, session_css)=>
var line tl = na

if session > session[1]

tl := line.new(n, close, n, close, color = session_css)

if session and session == session[1]

line.set_y1(tl, y1)
line.set_xy2(tl, n, y2)

//Set session range

get_range(session, session_name, session_css)=>
var t = 0
var max = high
var min = low
var box bx = na
var label lbl = na

if session > session[1] and showSessions

t := time
max := high
min := low

bx := box.new(n, max, n, min

, bgcolor = color.new(session_css, bg_transp)
, border_color = show_outline ? session_css : na
, border_style = line.style_dotted)

if show_txt and showSessions

lbl := label.new(t, max, session_name
, xloc = xloc.bar_time
, textcolor = session_css
, style = label.style_label_down
, color = color.new(color.white, 100)
, size = size.tiny)

if session and session == session[1] and showSessions

max := math.max(high, max)
min := math.min(low, min)

box.set_top(bx, max)
box.set_rightbottom(bx, n, min)

if show_txt
label.set_xy(lbl, int(math.avg(t, time)), max)

[session ? na : max, session ? na : min]

//-----------------------------------------------------------------------------}
//Sessions
//-----------------------------------------------------------------------------{
tf = timeframe.period

var tz = use_exchange ? syminfo.timezone :

str.format('UTC{0}{1}', tz_incr >= 0 ? '+' : '-', math.abs(tz_incr))
is_sesa = math.sign(nz(time(tf, sesa_ses, tz)))
is_sesb = math.sign(nz(time(tf, sesb_ses, tz)))

//-----------------------------------------------------------------------------}
//Dashboard
//-----------------------------------------------------------------------------{

var float max_sesa = na

var float min_sesa = na
var float max_sesb = na
var float min_sesb = na
var float max_sesc = na
var float min_sesc = na
var float max_sesd = na
var float min_sesd = na

//Ranges
if show_sesa and sesa_range
[max, min] = get_range(is_sesa, sesa_txt, sesa_css)
max_sesa := max
min_sesa := min

if show_sesb and sesb_range

[max, min] = get_range(is_sesb, sesb_txt, sesb_css)
max_sesb := max
min_sesb := min

//Trendlines
//Mean
if show_sesa and sesa_avg
avg = get_avg(is_sesa)
set_line(is_sesa, avg, avg, sesa_css)

if show_sesb and sesb_avg

avg = get_avg(is_sesb)
set_line(is_sesb, avg, avg, sesb_css)

//VWAP
//-----------------------------------------------------------------------------}
//Plots
//-----------------------------------------------------------------------------{
//Plot max/min
plot(showSessions and sesa_maxmin ? max_sesa : na, 'Session A Maximum', sesa_css,
1, plot.style_linebr, editable = false)
plot(showSessions and sesa_maxmin ? min_sesa : na, 'Session A Minimum', sesa_css,
1, plot.style_linebr, editable = false)

plot(showSessions and sesb_maxmin ? max_sesb : na, 'Session B Maximum', sesb_css,

1, plot.style_linebr, editable = false)
plot(showSessions and sesb_maxmin ? min_sesb : na, 'Session B Minimum', sesb_css,
1, plot.style_linebr, editable = false)

//Plot Divider A
plotshape(is_sesa and show_ses_div and show_sesa and showSessions, "·"
, shape.square
, location.bottom
, na
, text = "."
 , textcolor = sesa_css
, size = size.tiny
, display = display.all - display.status_line
, editable = false)

plotshape(is_sesa != is_sesa[1] and show_ses_div and show_sesa and showSessions,

"NYE"
, shape.labelup
, location.bottom
, na
, text = "❚"
, textcolor = sesa_css
, size = size.tiny
, display = display.all - display.status_line
, editable = false)

//Plot Divider B
plotshape(is_sesb and show_ses_div and show_sesb and showSessions, "·"
, shape.labelup
, location.bottom
, na
, text = "."
, textcolor = sesb_css
, size = size.tiny
, display = display.all - display.status_line
, editable = false)

plotshape(is_sesb != is_sesb[1] and show_ses_div and show_sesb and showSessions,

"LDN"
, shape.labelup
, location.bottom
, na
, text = "❚"
, textcolor = sesb_css
, size = size.tiny
, display = display.all - display.status_line
, editable = false)

// # ============================[FUNCTIONS]============================ #

type bar
float o = open
float h = high
float l = low
float c = close
float v = volume
int i = bar_index

bar b = bar.new()
nzV = nz(b.v)

f_calcV() =>
uV = 0.0
dV = 0.0

switch
(b.c - b.l) > (b.h - b.c) => uV := nzV
 (b.c - b.l) < (b.h - b.c) => dV := -nzV
b.c > b.o => uV := nzV
b.c < b.o => dV := -nzV
b.c > nz(b.c[1]) => uV := nzV
b.c < nz(b.c[1]) => dV := -nzV
nz(uV[1]) > 0 => uV := uV + nzV
nz(dV[1]) < 0 => dV := dV - nzV

[uV, dV]

// # ============================[CONSTANT VARIABLES]============================ #
sma4 = ta.sma(close, 4)
sma5 = ta.sma(close, 5)
sma9 = ta.sma(close, 9)
ema50 = ta.ema(close, 50)
ema200 = ta.ema(close, 200)

bullishSignalColor = #59e08a
bearishSignalColor = #ff5959

dashboardRedText = #ee787d
dashboardGreenText = #42bda8
dashboardGreenBackground = #284444
dashboardRedBackground = #49343e

// # ============================[CANDLE COLORING]============================ #
macdFastLength = 12
macdSlowLength = 26
macdSignalLength = 9

if (candleColorType != 'Confirmation Simple')

macdFastLength := 10
macdSlowLength := 25
macdSignalLength:=8

[MacdX, signalX, histX] = ta.macd(close, macdFastLength, macdSlowLength,

macdSignalLength)

//candle color scheme

greenHigh = #4ce653
greenMidHigh =#4ce653
greenMidLow =#4ce653
greenLow = #56328f

// Yellow
yellowLow = #56328f

// 4 level of red
redHigh = #ff0000
redMidHigh = #ff0000
redMidLow = #ff0000
redLow = #56328f

if (candleColorType == 'Confirmation Gradient')

greenHigh := #01d70c
greenMidHigh := #269444
 greenMidLow :=#4f966c
greenLow := #425970

// Yellow
yellowLow := #513a88

// 4 level of red
redHigh := #ff0000
redMidHigh := #c21637
redMidLow := #c33252
redLow := #8e215f
if (candleColorType == 'Contrarian Gradient')
redHigh := #01d70c
redMidHigh := #269444
redMidLow :=#4f966c
redLow := #425970

// Yellow
yellowLow := #513a88

// 4 level of red
greenHigh := #ff0000
greenMidHigh := #c21637
greenMidLow := #c33252
greenLow := #8e215f

// Default color
candleBody = yellowLow

if histX > 0
if histX > histX[1] and histX[1] > 0
candleBody := greenLow

if histX < 0
if histX < histX[1] and histX[1] < 0
candleBody := redLow

// Bullish trend
if MacdX > 0 and histX > 0
candleBody := greenMidLow

if histX > histX[1] and MacdX[1] > 0 and histX[1] > 0

candleBody := greenMidHigh

if histX > histX[2] and MacdX[2] > 0 and histX[2] > 0

candleBody := greenHigh

// Bearish trend
if MacdX < 0 and histX < 0
candleBody := redMidLow

if histX < histX[1] and MacdX[1] < 0 and histX[1] < 0

candleBody := redMidHigh

if histX < histX[2] and MacdX[2] < 0 and histX[2] < 0

candleBody := redHigh

barcolor(candleColorType == 'None' ? na : candleBody, editable = false)

// # ============================[SMART TRAIL]============================ #
[smartTrailLine, fillerLine, smartTrailDirection] = LAF.getSmartTrail(10, 4, 8)
smartTrail1 = plot(smartTrail ? smartTrailLine : na, "Smart Trail", style =
plot.style_line, color = smartTrailDirection== 'long' ? color.new(#2157f9, 0) :
smartTrailDirection == 'short' ? color.new(#ff1100, 0) : na, editable = false)
smartTrail2 = plot(smartTrail ? fillerLine : na, "Fib 2", style = plot.style_line,
transp = 100, editable = false)
fill(smartTrail1, smartTrail2, color = smartTrailDirection == 'long' ?
color.new(#2157f9, 80) : smartTrailDirection == 'short' ? color.new(#ff1100, 80) :
na, editable = false)

// # ============================[TREND CATCHER]============================ #
[trendCatcherLine, trendCatcherColor] = LAF.getTrendCatcher()
newTrendCatcherColor = trendCatcherColor == color.blue ? #02FF65 : #FF1100
plot(trendCatcher ? trendCatcherLine : na, title='Trend Catcher', linewidth=2,
color=newTrendCatcherColor, editable = false)

// # ============================[NEO CLOUD]============================ #

// # ============================[REVERSAL ZONES]============================ #

// # ============================[TREND TRACER]============================ #
[trendTracerLine, trendTracerDirection] = LAF.getTrendTracer()
trendTracerColor = trendTracerDirection == #02ff65 ? #F1FFE7 : #6C464E
plot(trendTracer ? trendTracerLine : na, title='Trend Tracer', linewidth=2,
style=plot.style_cross, color = trendTracerColor, editable = false)

// # ============================[DASHBOARD
COMPONENTS|]============================ #

trendStrengthMetric = math.abs(LAF.getTrendStrengthMetric(14, 'RMA', 21, 'EMA'))

trendStrengthMetric := trendStrengthMetric*2.5
trendIndication = trendStrengthMetric > 30 ? ""❄️
: " "
trendStrengthCellColor = newTrendCatcherColor == #02ff65 ? dashboardGreenBackground
: dashboardRedBackground
trendStrengthTextColor = trendStrengthCellColor == dashboardGreenBackground ?
dashboardGreenText : dashboardRedText

volatilityMetric = LAF.getVolatilityMetric()
volatilityMetric2 = ta.sma(LAF.getVolatilityMetric(), 8)
volatilityText = volatilityMetric < 30 ? 'Stable' : volatilityMetric < 80 ?
'Moderate' : 'Volatile'
volatilityEmoji = volatilityMetric2 > volatilityMetric ? '📉' : '📈'
volatilityCellColor = newTrendCatcherColor == #02ff65 ? dashboardGreenBackground :
dashboardRedBackground
VolatilityTextColor = trendStrengthCellColor == dashboardGreenBackground ?
dashboardGreenText : dashboardRedText

squeezeMetric = LAF.getSqueezeMetric(45, 20)

squeezeIsHigh = squeezeMetric >= 80 ? true : false
squeezeCellColor = trendTracerDirection == #02ff65 ? #1a3a3e : #482632
squeezeTextColor = trendTracerDirection != #02ff65 ? #ed3544 : #0a907a

//Telegram ==>> https://t.me/+UAk3hqvoD89jZTlk

[uV, dV] = f_calcV()

totalVolume = uV + math.abs(dV)
//volumecolor = totalVolume >= 50 ? bullish : bearish
volumeCellColor = dashboardRedBackground
volumeTextColor = totalVolume >= 50 ? dashboardGreenText : dashboardRedText
if (totalVolume >= 50)
totalVolume := totalVolume*2
volumeCellColor := dashboardGreenBackground
else
totalVolume := totalVolume*-2

volumeSentiment = totalVolume

table_position = dashboardLocation == 'Bottom Left' ? position.bottom_left

: dashboardLocation == 'Top Right' ? position.top_right
: position.bottom_right

table_size = dashboardSize == 'Tiny' ? size.tiny

: dashboardSize == 'Small' ? size.small
: size.normal

tb = table.new(table_position, 7, 7
, bgcolor = #1e222d
, border_color = #373a46
, border_width = 1
, frame_color = #373a46
, frame_width = 1)

if showDashboard
if barstate.islast
tb.cell(0, 2, autopilotMode == 'Off' ? "✈️
Optimal Sensivity" : " Autopilot
Enabled", text_color = color.white, text_size = table_size, text_halign =
text.align_left)
tb.cell(0, 3, str.tostring(trendIndication) + "Trend Strength", text_color
= color.white, text_size = table_size, text_halign = text.align_left)
tb.cell(0, 4, volatilityEmoji+ " Lux Volatility", text_color = color.white,
text_size = table_size, text_halign = text.align_left)
tb.cell(0, 5, "🔃 Squeeze", text_color = color.white, text_size =
table_size, text_halign = text.align_left)
tb.cell(0, 6, "💧 Volume Sentiment", text_color = color.white, text_size =
table_size, text_halign = text.align_left)

tb.cell(1, 2, autopilotMode, text_color = color.white, text_size =

table_size)
tb.cell(1, 3, str.tostring(trendStrengthMetric, format.percent),
text_color=trendStrengthTextColor, text_size=table_size, bgcolor =
trendStrengthCellColor)
tb.cell(1, 4, volatilityText, text_color = VolatilityTextColor, text_size =
table_size, bgcolor = volatilityCellColor)
tb.cell(1, 5, str.tostring(squeezeMetric, format.percent), text_color=
squeezeTextColor, text_size=table_size, bgcolor = squeezeCellColor)
tb.cell(1, 6, str.tostring(math.min(volumeSentiment, 100.),
format.percent), text_color = volumeTextColor, text_size = table_size, bgcolor =
volumeCellColor)

//
***********************************************************************************
*************************
// REV ZONES
//
***********************************************************************************
*************************

indiSet = false
source = hlc3
type = 'SuperSmoother'
length = 100
innermult = 1.0
outermult = 2.415

ChartSet = false
drawchannel = true
displayzone = true
zonetransp = 60
displayline = true

MTFSet = false
enable_mtf = true
mtf_disp_typ = 'On Hover'
mtf_typ = 'Auto'
mtf_lvl1 = 'D'
mtf_lvl2 = 'W'

//
***********************************************************************************
*************************
// Functions Start {
//
***********************************************************************************
*************************
var pi = 2 * math.asin(1)
var mult = pi * innermult
var mult2 = pi * outermult
var gradsize = 0.5
var gradtransp = zonetransp

//-----------------------
// Ehler SwissArmyKnife Function
//-----------------------
SAK_smoothing(_type, _src, _length) =>
c0 = 1.0
c1 = 0.0
b0 = 1.0
b1 = 0.0
b2 = 0.0
a1 = 0.0
a2 = 0.0
alpha = 0.0
beta = 0.0
gamma = 0.0
cycle = 2 * pi / _length

if _type == 'Ehlers EMA'

alpha := (math.cos(cycle) + math.sin(cycle) - 1) / math.cos(cycle)
b0 := alpha
a1 := 1 - alpha
a1
 if _type == 'Gaussian'
beta := 2.415 * (1 - math.cos(cycle))
alpha := -beta + math.sqrt(beta * beta + 2 * beta)
c0 := alpha * alpha
a1 := 2 * (1 - alpha)
a2 := -(1 - alpha) * (1 - alpha)
a2
if _type == 'Butterworth'
beta := 2.415 * (1 - math.cos(cycle))
alpha := -beta + math.sqrt(beta * beta + 2 * beta)
c0 := alpha * alpha / 4
b1 := 2
b2 := 1
a1 := 2 * (1 - alpha)
a2 := -(1 - alpha) * (1 - alpha)
a2
if _type == 'BandStop'
beta := math.cos(cycle)
gamma := 1 / math.cos(cycle * 2 * 0.1) // delta default to 0.1. Acceptable
delta -- 0.05<d<0.5
alpha := gamma - math.sqrt(gamma * gamma - 1)
c0 := (1 + alpha) / 2
b1 := -2 * beta
b2 := 1
a1 := beta * (1 + alpha)
a2 := -alpha
a2
if _type == 'SMA'
c1 := 1 / _length
b0 := 1 / _length
a1 := 1
a1
if _type == 'EMA'
alpha := 2 / (_length + 1)
b0 := alpha
a1 := 1 - alpha
a1
if _type == 'RMA'
alpha := 1 / _length
b0 := alpha
a1 := 1 - alpha
a1

_Input = _src
_Output = 0.0
_Output := c0 * (b0 * _Input + b1 * nz(_Input[1]) + b2 * nz(_Input[2])) + a1 *
nz(_Output[1]) + a2 * nz(_Output[2]) - c1 * nz(_Input[_length])
_Output

//-----------------------
// SuperSmoother Function
//-----------------------
supersmoother(_src, _length) =>
s_a1 = math.exp(-math.sqrt(2) * pi / _length)
s_b1 = 2 * s_a1 * math.cos(math.sqrt(2) * pi / _length)
s_c3 = -math.pow(s_a1, 2)
s_c2 = s_b1
s_c1 = 1 - s_c2 - s_c3
ss = 0.0
 ss := s_c1 * _src + s_c2 * nz(ss[1], _src[1]) + s_c3 * nz(ss[2], _src[2])
ss

//-----------------------
// Auto TimeFrame Function
//-----------------------
// ————— Converts current chart resolution into a float minutes value.
f_resInMinutes() =>
_resInMinutes = timeframe.multiplier * (timeframe.isseconds ? 1. / 60 :
timeframe.isminutes ? 1. : timeframe.isdaily ? 60. * 24 : timeframe.isweekly ? 60.
* 24 * 7 : timeframe.ismonthly ? 60. * 24 * 30.4375 : na)
_resInMinutes

get_tf(_lvl) =>
y = f_resInMinutes()
z = timeframe.period
if mtf_typ == 'Auto'
if y < 1
z := _lvl == 1 ? '1' : _lvl == 2 ? '5' : z
z
else if y <= 3
z := _lvl == 1 ? '5' : _lvl == 2 ? '15' : z
z
else if y <= 10
z := _lvl == 1 ? '15' : _lvl == 2 ? '60' : z
z
else if y <= 30
z := _lvl == 1 ? '60' : _lvl == 2 ? '240' : z
z
else if y <= 120
z := _lvl == 1 ? '240' : _lvl == 2 ? 'D' : z
z
else if y <= 240
z := _lvl == 1 ? 'D' : _lvl == 2 ? 'W' : z
z
else if y <= 1440
z := _lvl == 1 ? 'W' : _lvl == 2 ? 'M' : z
z
else if y <= 10080
z := _lvl == 1 ? 'M' : z
z
else
z := z
z
else
z := _lvl == 1 ? mtf_lvl1 : _lvl == 2 ? mtf_lvl2 : z
z

//-----------------------
// Mean Reversion Channel Function
//-----------------------
get_mrc() =>
v_condition = 0
v_meanline = source
v_meanrange = supersmoother(ta.tr, length)

//-- Get Line value

 if type == 'SuperSmoother'
v_meanline := supersmoother(source, length)
v_meanline

if type != 'SuperSmoother'
v_meanline := SAK_smoothing(type, source, length)
v_meanline

v_upband1 = v_meanline + v_meanrange * mult

v_loband1 = v_meanline - v_meanrange * mult
v_upband2 = v_meanline + v_meanrange * mult2
v_loband2 = v_meanline - v_meanrange * mult2

//-- Check Condition

if close > v_meanline
v_upband2_1 = v_upband2 + v_meanrange * gradsize * 4
v_upband2_9 = v_upband2 + v_meanrange * gradsize * -4
if high >= v_upband2_9 and high < v_upband2
v_condition := 1
v_condition
else if high >= v_upband2 and high < v_upband2_1
v_condition := 2
v_condition
else if high >= v_upband2_1
v_condition := 3
v_condition
else if close <= v_meanline + v_meanrange
v_condition := 4
v_condition
else
v_condition := 5
v_condition

if close < v_meanline

v_loband2_1 = v_loband2 - v_meanrange * gradsize * 4
v_loband2_9 = v_loband2 - v_meanrange * gradsize * -4
if low <= v_loband2_9 and low > v_loband2
v_condition := -1
v_condition
else if low <= v_loband2 and low > v_loband2_1
v_condition := -2
v_condition
else if low <= v_loband2_1
v_condition := -3
v_condition
else if close >= v_meanline + v_meanrange
v_condition := -4
v_condition
else
v_condition := -5
v_condition

[v_meanline, v_meanrange, v_upband1, v_loband1, v_upband2, v_loband2,

v_condition]

//-----------------------
// MTF Analysis
//-----------------------
get_stat(_cond) =>
ret = 'Price at Mean Line\n'
if _cond == 1
ret := 'Overbought (Weak)\n'
ret
else if _cond == 2
ret := 'Overbought\n'
ret
else if _cond == 3
ret := 'Overbought (Strong)\n'
ret
else if _cond == 4
ret := 'Price Near Mean\n'
ret
else if _cond == 5
ret := 'Price Above Mean\n'
ret
else if _cond == -1
ret := 'Oversold (Weak)\n'
ret
else if _cond == -2
ret := 'Oversold\n'
ret
else if _cond == -3
ret := 'Oversold (Strong)\n'
ret
else if _cond == -4
ret := 'Price Near Mean\n'
ret
else if _cond == -5
ret := 'Price Below Mean\n'
ret
ret

//-----------------------
// Chart Drawing Function
//-----------------------
format_price(x) =>
y = str.tostring(x, '0.00000')
if x > 10
y := str.tostring(x, '0.000')
y
if x > 1000
y := str.tostring(x, '0.00')
y
y

f_PriceLine(_ref, linecol) =>

line.new(x1=bar_index, x2=bar_index - 1, y1=_ref, y2=_ref, extend=extend.left,
color=linecol)

f_MTFLabel(_txt, _yloc) =>

label.new(x=time + math.round(ta.change(time) * 20), y=_yloc,
xloc=xloc.bar_time, text=mtf_disp_typ == 'Always Display' ? _txt : 'Check MTF',
tooltip=mtf_disp_typ == 'Always Display' ? '' : _txt, color=color.black,
textcolor=color.white, size=size.normal, style=mtf_disp_typ == 'On Hover' and
displayline ? label.style_label_lower_left : label.style_label_left,
textalign=text.align_left)
//} Function End

//
***********************************************************************************
*************************
// Calculate Channel
//
***********************************************************************************
*************************
var tf_0 = timeframe.period
var tf_1 = get_tf(1)
var tf_2 = get_tf(2)

[meanline, meanrange, upband1, loband1, upband2, loband2, condition] = get_mrc()

[mtf1_meanline, mtf1_meanrange, mtf1_upband1, mtf1_loband1, mtf1_upband2,
mtf1_loband2, mtf1_condition] = request.security(syminfo.tickerid, tf_1, get_mrc())
[mtf2_meanline, mtf2_meanrange, mtf2_upband1, mtf2_loband1, mtf2_upband2,
mtf2_loband2, mtf2_condition] = request.security(syminfo.tickerid, tf_2, get_mrc())

//
***********************************************************************************
*************************
// Drawing Start {
//
***********************************************************************************
*************************
float p_meanline = drawchannel ? meanline : na
float p_upband1 = drawchannel ? upband1 : na
float p_loband1 = drawchannel ? loband1 : na
float p_upband2 = drawchannel ? upband2 : na
float p_loband2 = drawchannel ? loband2 : na

//z = plot(p_meanline, color=color.new(#FFCD00, 0), style=plot.style_line, title='

Mean', linewidth=2)
//x1 = plot(p_upband1, color=color.new(color.green, 50), style=plot.style_circles,
title=' R1', linewidth=1)
//x2 = plot(p_loband1, color=color.new(color.green, 50), style=plot.style_circles,
title=' S1', linewidth=1)
//y1 = plot(p_upband2, color=color.new(color.red, 50), style=plot.style_line,
title=' R2', linewidth=1)
//y2 = plot(p_loband2, color=color.new(color.red, 50), style=plot.style_line,
title=' S2', linewidth=1)

//-----------------------
// Draw zone
//-----------------------
//---
var color1 = #FF0000
var color2 = #FF4200
var color3 = #FF5D00
var color4 = #FF7400
var color5 = #FF9700
var color6 = #FFAE00
var color7 = #FFC500
var color8 = #FFCD00
//---
float upband2_1 = drawchannel and displayzone ? upband2 + meanrange * gradsize *
4 : na
float loband2_1 = drawchannel and displayzone ? loband2 - meanrange * gradsize *
4 : na
float upband2_2 = drawchannel and displayzone ? upband2 + meanrange * gradsize *
3 : na
float loband2_2 = drawchannel and displayzone ? loband2 - meanrange * gradsize *
3 : na
float upband2_3 = drawchannel and displayzone ? upband2 + meanrange * gradsize *
2 : na
float loband2_3 = drawchannel and displayzone ? loband2 - meanrange * gradsize *
2 : na
float upband2_4 = drawchannel and displayzone ? upband2 + meanrange * gradsize *
1 : na
float loband2_4 = drawchannel and displayzone ? loband2 - meanrange * gradsize *
1 : na
float upband2_5 = drawchannel and displayzone ? upband2 + meanrange * gradsize *
0 : na
float loband2_5 = drawchannel and displayzone ? loband2 - meanrange * gradsize *
0 : na
float upband2_6 = drawchannel and displayzone ? upband2 + meanrange * gradsize * -1
: na
float loband2_6 = drawchannel and displayzone ? loband2 - meanrange * gradsize * -1
: na
float upband2_7 = drawchannel and displayzone ? upband2 + meanrange * gradsize * -2
: na
float loband2_7 = drawchannel and displayzone ? loband2 - meanrange * gradsize * -2
: na
float upband2_8 = drawchannel and displayzone ? upband2 + meanrange * gradsize * -3
: na
float loband2_8 = drawchannel and displayzone ? loband2 - meanrange * gradsize * -3
: na
float upband2_9 = drawchannel and displayzone ? upband2 + meanrange * gradsize * -4
: na
float loband2_9 = drawchannel and displayzone ? loband2 - meanrange * gradsize * -4
: na

up1 = plot(reversalZone ? upband2_1 : na, color = color.black, transp = 100,

editable = false)
up2 = plot(reversalZone ?upband2_5:na, color = color.black, transp = 100, editable
= false)
up3 = plot(reversalZone ?upband2_9:na, color = color.black, transp = 100, editable
= false)
dp1 = plot(reversalZone ?loband2_1:na, color = color.black, transp = 100, editable
= false)
dp2 = plot(reversalZone ?loband2_5:na, color = color.black, transp = 100, editable
= false)
dp3 = plot(reversalZone ?loband2_9:na, color = color.black, transp = 100, editable
= false)

fill(up1, up2, color = #56202d, transp = 20, editable = false)

fill(up2, up3, color = #3f1d29, transp = 60, editable = false)
fill(dp1, dp2, color = #0f3e3f, transp = 20, editable = false)
fill(dp2, dp3, color = #113135, transp = 60, editable = false)

//[upband2_1, upband2_5, upband2_9, loband2_1, loband2_5, loband2_9]

tenkan_len = 365
tenkan_mult = 3

kijun_len = 365
kijun_mult = 7
spanB_len = 365
spanB_mult = 15

offset = 2
//------------------------------------------------------------------------------
avg(src,length,mult)=>
atr = ta.atr(length)*mult
up = hl2 + atr
dn = hl2 - atr
upper = 0.,lower = 0.
upper := src[1] < upper[1] ? math.min(up,upper[1]) : up
lower := src[1] > lower[1] ? math.max(dn,lower[1]) : dn

os = 0,max = 0.,min = 0.
os := src > upper ? 1 : src < lower ? 0 : os[1]
spt = os == 1 ? lower : upper
max := ta.cross(src,spt) ? math.max(src,max[1]) : os == 1 ?
math.max(src,max[1]) : spt
min := ta.cross(src,spt) ? math.min(src,min[1]) : os == 0 ?
math.min(src,min[1]) : spt
math.avg(max,min)
//------------------------------------------------------------------------------
tenkan = avg(close,tenkan_len,tenkan_mult)
kijun = avg(close,kijun_len,kijun_mult)

senkouA = math.avg(kijun,tenkan)
senkouB = avg(close,spanB_len,spanB_mult)
//------------------------------------------------------------------------------
tenkan_css = #2156f300
kijun_css = #ff5e0000

cloud_a = color.new(#006989, 47)

cloud_b = color.new(#ff5252, 66)

chikou_css = #7b1fa2

plot(neoCloud ? tenkan : na,'Tenkan-Sen',tenkan_css, editable = false)

plot(neoCloud ? kijun : na,'Kijun-Sen',kijun_css, editable = false)

plot(neoCloud and ta.crossover(tenkan,kijun) ? kijun :

na,'Crossover',#2156f300,3,plot.style_circles, editable = false)
plot(neoCloud and ta.crossunder(tenkan,kijun) ? kijun :
na,'Crossunder',#ff5e0000,3,plot.style_circles, editable = false)

A = plot(neoCloud ? senkouA: na,'Senkou Span A',na,offset=offset-1, editable =

false)
B = plot(neoCloud ? senkouB : na,'Senkou Span B',na,offset=offset-1, editable =
false)
fill(A,B,senkouA > senkouB ? cloud_a : cloud_b)
lastNeo = int(senkouA + senkouB)
last5Neo = ta.sma(lastNeo, 2)

plot(close,'Chikou',chikou_css,offset=-offset+1,display=display.none, editable =
false)

// Wylicz pozycję kwadratu

ltp1 = bar_index
rtp1 = bar_index + 40

[lowBound, midBound, highBound] = LAF.getTPSLBoxes(6.0)

// Stwórz rzeczywisty kwadrat

//tp1box = box.new(left=ltp1, top=ttp1, right=rtp1, bottom=btp1,
border_color=#3666f5, border_width=2, border_style=line.style_solid,
bgcolor=color.new(#3666f5, 53), text="TP1 : " + str.tostring(close),
text_size=size.large, text_color=color.new(#3666f5, 0), text_wrap=text.wrap_auto)
//var boxes = array.new<box>()
//boxes.push(box.new(left = ltp1, top = close+highBound, right = rtp1, bottom =
close + midBound, border_color=#3666f5, border_width=2,
border_style=line.style_solid, bgcolor=color.new(#3666f5, 70), text="TP/SL 2 : "
+ str.tostring(close), text_size=size.large, text_color=color.new(#3666f5, 0),
text_wrap=text.wrap_auto))
//boxes.push(box.new(left = ltp1, top = close+midBound, right = rtp1, bottom =
close + lowBound, border_color=#3666f5, border_width=2,
border_style=line.style_solid, bgcolor=color.new(#3666f5, 40), text="TP/SL 1 : "
+ str.tostring(close), text_size=size.large, text_color=color.new(#3666f5, 0),
text_wrap=text.wrap_auto))

//SL1 = box.new(left = ltp1, top = close-highBound, right = rtp1, bottom = close -

midBound, border_color=#3666f5, border_width=2, border_style=line.style_solid,
bgcolor=color.new(#3666f5, 70), text="TP/SL 2 : " + str.tostring(close),
text_size=size.large, text_color=color.new(#3666f5, 0), text_wrap=text.wrap_auto)
//SL2 = box.new(left = ltp1, top = close-midBound, right = rtp1, bottom = close -
lowBound, border_color=#3666f5, border_width=2, border_style=line.style_solid,
bgcolor=color.new(#3666f5, 40), text="TP/SL 1 : " + str.tostring(close),
text_size=size.large, text_color=color.new(#3666f5, 0), text_wrap=text.wrap_auto)

// Usuń poprzednie ramki

//box.delete(boxes.shift())
//box.delete(SL1[1])
//box.delete(SL2[1])

//box.delete(boxes.shift())

// ==== Overview ====

// ==================

// WaveTrend 3D (WT3D) is a novel implementation of the famous WaveTrend (WT)

indicator and has been completely redesigned from the ground up to address some
// of the inherent shortcomings associated with the traditional WT algorithm,
including:
// (1) unbounded extremes
// (2) susceptibility to whipsaw
// (3) lack of insight into other timeframes

// Furthermore, WT3D expands upon the original functionality of WT by providing:

// (1) first-class support for multi-timeframe (MTF) analysis
// (2) kernel-based regression for trend reversal confirmation
// (3) various options for signal smoothing and transformation
// (4) a unique mode for visualizing an input series as a symmetrical, three-
dimensional waveform useful for pattern identification and cycle-related analysis

// Fundamental Assumptions:
// (1) There exists a probability density function that describes the relative
likelihood for a price to visit a given value.
// (2) The probability density function for price is a function of time.
// (3) The probability density function can approximate a Gaussian distribution
(shown below).

// ___
// .::~!:.. |

// :ΞΞΞΞ~!ΞΞΞ!. |

// .ΞJΞΞΞΞ~!ΞΞΞ?J^ |

// :J?ΞΞΞΞΞ~!ΞΞΞΞΞJ^ |

// :J?ΞΞΞΞΞΞ~!ΞΞΞΞΞΞ??. |

// :JΞΞΞΞΞΞΞΞ~!ΞΞΞΞΞΞΞ?J^ |

// :JΞΞΞΞΞΞΞΞΞ~!ΞΞΞΞΞΞΞΞ?J^
[ PRICE ]
// .:~ΞΞΞΞΞΞΞΞΞΞ~!ΞΞΞΞΞΞΞΞΞ!!~ |

// :?~^ΞΞΞΞΞΞΞΞΞΞ~!ΞΞΞΞΞΞΞΞΞ!^Ξ! |

// ~:^^^ΞΞΞΞΞΞΞΞΞΞ~!ΞΞΞΞΞΞΞΞΞ!^^!Ξ. |

// .Ξ!^^^^ΞΞΞΞΞΞΞΞΞΞ~!ΞΞΞΞΞΞΞΞΞ!^^^~Ξ~ |

// .~Ξ~^^^^^ΞΞΞΞΞΞΞΞΞΞ~!ΞΞΞΞΞΞΞΞΞ!^^^^^!Ξ: |

// .~Ξ~^^^^^^^ΞΞΞΞΞΞΞΞΞΞ~!ΞΞΞΞΞΞΞΞΞ!^^^^^^~!!^. |

// ....::^^!~~^^^^^^^^^ΞΞΞΞΞΞΞΞΞΞ~!ΞΞΞΞΞΞΞΞΞ!^^^^^^^^^~!^^::...... |

// ..:::^^^^^^^::::::::::::::ΞΞΞΞΞΞΞΞΞΞ~!ΞΞΞΞΞΞΞΞΞ!::::::::::::^^^^^^^^:::.. |

//
// -------------------------------- [ TIME ] -------------------------------|

// How to use this indicator:

// - The basic usage of WT3D is similar to how one would use the traditional WT
indicator.
// - Divergences can be spotted by finding "trigger waves", which are small waves
that immediately follow a larger wave. These can also be thought of as Lower-Highs
and Higher-Lows in the oscillator.
// - Instead of the SMA-cross in the original WT, the primary mechanism for
identifying potential pivots are the crossovers of the fast/normal speed
oscillators, denoted by the small red/green circles.
// - The larger red/green circles represent points where there could be a potential
trigger wave for a Divergence. Settings related to Divergence detection can be
configured in the "Divergence" section.
// - For overbought/oversold conditions, the 0.5 and -0.5 levels are convenient
since the normal-speed oscillator will only exceed this level ~25% of the time.
// - For less experienced users, focusing on the three oscillators is recommended
since they give critical information from multiple timeframes that can help to
identify trends and spot potential divergences.
// - For more experienced users, this indicator also has many other valuable
features, such as Center of Gravity (CoG) smoothing, Kernel Estimate Crossovers, a
mirrored mode for cycle analysis, and more.
// - Note: Additional resources for learning/using the more advanced features of
this indicator are a work in progress, but in the meantime, I am happy to answer
any questions.

// ================
// ==== Inputs ====
// ================

// Signal Settings
src = close
useMirror = false
useEma = false
emaLength = 3
useCog = false
cogLength = 6
oscillatorLookback =20
quadraticMeanLength = 50
src := useEma ? ta.ema(src, emaLength) : src
src := useCog ? ta.cog(src, cogLength) : src
speedToEmphasize = 'Normal'
emphasisWidth = 2
useKernelMA = false
useKernelEmphasis = false

// Oscillator Settings
offset := 0
showOsc = true
showOsc := showOsc
float f_length = 0.75
float f_smoothing = 0.45
float n_length = 1.0
float n_smoothing = 1.0
float s_length = 1.75
float s_smoothing = 2.5

// Divergence Detection
divThreshold = 30
sizePercent = 40

// Overbought/Oversold Zones (Reversal Zones)

showObOs = false
invertObOsColors = false

// Transparencies and Gradients

areaBackgroundTrans = 128.
areaForegroundTrans = 64.
lineBackgroundTrans = 2.6
lineForegroundTrans = 2.
customTransparency = 30
maxStepsForGradient = 8

// The defaults are colors that Google uses for its Data Science libraries (e.g.
TensorFlow). They are considered to be colorblind-safe.
var color fastBullishColor = color.black
var color normalBullishColor = color.black
var color slowBullishColor = color.black
var color fastBearishColor = color.black
var color normalBearishColor = color.black
var color slowBearishColor =color.black
var color c_bullish = color.black
var color c_bearish = color.black

lineBackgroundTrans := lineBackgroundTrans * customTransparency

areaBackgroundTrans := areaBackgroundTrans * customTransparency
lineForegroundTrans := lineForegroundTrans * customTransparency
areaForegroundTrans := areaForegroundTrans * customTransparency

areaFastTrans = areaBackgroundTrans
lineFastTrans = lineBackgroundTrans
areaNormalTrans = areaBackgroundTrans
lineNormalTrans = lineBackgroundTrans
areaSlowTrans = areaForegroundTrans
lineSlowTrans = lineForegroundTrans

switch speedToEmphasize
"Slow" =>
areaFastTrans := areaBackgroundTrans
lineFastTrans := lineBackgroundTrans
areaNormalTrans := areaBackgroundTrans
lineNormalTrans := lineBackgroundTrans
areaSlowTrans := areaForegroundTrans
lineSlowTrans := lineForegroundTrans
"Normal" =>
areaFastTrans := areaBackgroundTrans
lineFastTrans := lineBackgroundTrans
areaNormalTrans := areaForegroundTrans
lineNormalTrans := lineForegroundTrans
areaSlowTrans := areaBackgroundTrans
lineSlowTrans := lineBackgroundTrans
"Fast" =>
areaFastTrans := areaForegroundTrans
lineFastTrans := lineForegroundTrans
areaNormalTrans := areaBackgroundTrans
lineNormalTrans := lineBackgroundTrans
areaSlowTrans := areaBackgroundTrans
lineSlowTrans := lineBackgroundTrans
"None" =>
areaFastTrans := areaBackgroundTrans
lineFastTrans := lineBackgroundTrans
areaNormalTrans := areaBackgroundTrans
lineNormalTrans := lineBackgroundTrans
areaSlowTrans := areaBackgroundTrans
lineSlowTrans := lineBackgroundTrans
// =================================
// ==== Color Helper Functions =====
// =================================

getPlotColor(signal, bullColor, bearColor) =>

signal >= 0.0 ? bullColor : bearColor

getAreaColor(signal, useMomentum, bullColor, bearColor) =>

if useMomentum
ta.rising(signal, 1) ? bullColor : bearColor
else
signal >= 0.0 ? bullColor : bearColor

getColorGradientFromSteps(_source, _center, _steps, weakColor, strongColor) =>

var float _qtyAdvDec = 0.
var float _maxSteps = math.max(1, _steps)
bool _xUp = ta.crossover(_source, _center)
bool _xDn = ta.crossunder(_source, _center)
float _chg = ta.change(_source)
bool _up = _chg > 0
bool _dn = _chg < 0
bool _srcBull = _source > _center
bool _srcBear = _source < _center
_qtyAdvDec := _srcBull ? _xUp ? 1 : _up ? math.min(_maxSteps, _qtyAdvDec + 1) :
_dn ? math.max(1, _qtyAdvDec - 1) : _qtyAdvDec : _srcBear ? _xDn ? 1 : _dn ?
math.min(_maxSteps, _qtyAdvDec + 1) : _up ? math.max(1, _qtyAdvDec - 1) :
_qtyAdvDec : _qtyAdvDec
color colorGradient = color.from_gradient(_qtyAdvDec, 1, _maxSteps, weakColor,
strongColor)
colorGradient

getColorGradientFromSource(series, _min, _max, weakColor, strongColor) =>

var float baseLineSeries = _min + (_max - _min) / 2
color colorGradient = series >= baseLineSeries ?
color.from_gradient(value=series, bottom_value=baseLineSeries, top_value=_max,
bottom_color=weakColor, top_color=strongColor) : color.from_gradient(series, _min,
baseLineSeries, strongColor, weakColor)
colorGradient

// ================================
// ==== Main Helper Functions =====
// ================================

normalizeDeriv(_src, _quadraticMeanLength) =>

float derivative = _src - _src[2]
quadraticMean = math.sqrt(nz(math.sum(math.pow(derivative, 2),
_quadraticMeanLength) / _quadraticMeanLength))
derivative/quadraticMean

tanh(series float _src) =>

-1 + 2/(1 + math.exp(-2*_src))

dualPoleFilter(float _src, float _lookback) =>

float _omega = -99 * math.pi / (70 * _lookback)
float _alpha = math.exp(_omega)
float _beta = -math.pow(_alpha, 2)
float _gamma = math.cos(_omega) * 2 * _alpha
float _delta = 1 - _gamma - _beta
 float _slidingAvg = 0.5 * (_src + nz(_src[1], _src))
float _filter = na
_filter := (_delta*_slidingAvg) + _gamma*nz(_filter[1]) + _beta*nz(_filter[2])
_filter

getOscillator(float src, float smoothingFrequency, int quadraticMeanLength) =>

nDeriv = normalizeDeriv(src, quadraticMeanLength)
hyperbolicTangent = tanh(nDeriv)
result = dualPoleFilter(hyperbolicTangent, smoothingFrequency)

// =================================
// ==== Oscillator Calculations ====
// =================================

// Fast Oscillator + Mirror

offsetFast = offset
f_lookback = f_smoothing * oscillatorLookback
signalFast = getOscillator(src, f_lookback, quadraticMeanLength)
seriesFast = f_length*signalFast+offsetFast
seriesFastMirror = useMirror ? -seriesFast + 2*offsetFast : na

// Normal Oscillator + Mirror

offsetNormal = 0
n_lookback = n_smoothing * oscillatorLookback
signalNormal = getOscillator(src, n_lookback, quadraticMeanLength)
seriesNormal = n_length*signalNormal+offsetNormal
seriesNormalMirror = useMirror ? -seriesNormal + 2*offsetNormal : na

// Slow Oscillator + Mirror

offsetSlow = -offset
s_lookback = s_smoothing * oscillatorLookback
signalSlow = getOscillator(src, s_lookback, quadraticMeanLength)
seriesSlow = s_length*signalSlow+offsetSlow
seriesSlowMirror = useMirror ? -seriesSlow + 2*offsetSlow : na

// =====================================
// ==== Color Gradient Calculations ====
// =====================================

// Fast Color Gradients (Areas and Lines)

fastBaseColor = getPlotColor(signalFast, fastBullishColor, fastBearishColor)
fastBaseColorInverse = getPlotColor(signalFast, fastBearishColor, fastBullishColor)
fastAreaGradientFromSource = getColorGradientFromSource(seriesFast, -1.+offsetFast,
1+offsetFast, color.new(fastBaseColor, areaFastTrans), fastBaseColor)
fastAreaGradientFromSteps = getColorGradientFromSteps(seriesFast, offsetFast,
maxStepsForGradient, color.new(fastBaseColor, areaFastTrans), fastBaseColor)
fastLineGradientFromSource = getColorGradientFromSource(seriesFast, -1+offsetFast,
1+offsetFast, color.new(fastBaseColor, lineFastTrans), fastBaseColor)
fastLineGradientFromSteps = getColorGradientFromSteps(seriesFast, offsetFast,
maxStepsForGradient, color.new(fastBaseColor, lineFastTrans), fastBaseColor)
fastAreaGradientFromSourceInverse = getColorGradientFromSource(seriesFast, -
1.+offsetFast, 1+offsetFast, color.new(fastBaseColorInverse, areaFastTrans),
fastBaseColorInverse)
fastAreaGradientFromStepsInverse = getColorGradientFromSteps(seriesFast,
offsetFast, maxStepsForGradient, color.new(fastBaseColorInverse, areaFastTrans),
fastBaseColorInverse)

// Normal Color Gradients (Areas and Lines)

normalBaseColor = getPlotColor(signalNormal, normalBullishColor,
normalBearishColor)
normalBaseColorInverse = getPlotColor(signalNormal, normalBearishColor,
normalBullishColor)
normalAreaGradientFromSource = getColorGradientFromSource(seriesNormal, -
1.+offsetNormal, 1.+offsetNormal, color.new(normalBaseColor, areaNormalTrans),
normalBaseColor)
normalAreaGradientFromSteps = getColorGradientFromSteps(seriesNormal, offsetNormal,
maxStepsForGradient, color.new(normalBaseColor, areaNormalTrans), normalBaseColor)
normalLineGradientFromSource = getColorGradientFromSource(seriesNormal, -
1+offsetNormal, 1+offsetNormal, color.new(normalBaseColor, lineNormalTrans),
normalBaseColor)
normalLineGradientFromSteps = getColorGradientFromSteps(seriesNormal, offsetNormal,
maxStepsForGradient, color.new(normalBaseColor, lineNormalTrans), normalBaseColor)
normalAreaGradientFromSourceInverse = getColorGradientFromSource(seriesNormal, -
1.+offsetNormal, 1.+offsetNormal, color.new(normalBaseColorInverse,
areaNormalTrans), normalBaseColorInverse)
normalAreaGradientFromStepsInverse = getColorGradientFromSteps(seriesNormal,
offsetNormal, maxStepsForGradient, color.new(normalBaseColorInverse,
areaNormalTrans), normalBaseColorInverse)

// Slow Color Gradients (Areas and Lines)

slowBaseColor = getPlotColor(signalSlow, slowBullishColor, slowBearishColor)
slowBaseColorInverse = getPlotColor(signalSlow, slowBearishColor, slowBullishColor)
slowAreaGradientFromSource = getColorGradientFromSource(seriesSlow, -
1.75+offsetSlow, 1.75+offsetSlow, color.new(slowBaseColor, areaSlowTrans),
slowBaseColor)
slowAreaGradientFromSteps = getColorGradientFromSteps(seriesSlow, offsetSlow,
maxStepsForGradient, color.new(slowBaseColor, areaSlowTrans), slowBaseColor)
slowLineGradientFromSource = getColorGradientFromSource(seriesSlow, -
1.75+offsetSlow, 1.75+offsetSlow, color.new(slowBaseColor, lineSlowTrans),
slowBaseColor)
slowLineGradientFromSteps = getColorGradientFromSteps(seriesSlow, offsetSlow,
maxStepsForGradient, color.new(slowBaseColor, lineSlowTrans), slowBaseColor)
slowAreaGradientFromSourceInverse = getColorGradientFromSource(seriesSlow, -
1.75+offsetSlow, 1.75+offsetSlow, color.new(slowBaseColorInverse, areaSlowTrans),
slowBaseColorInverse)
slowAreaGradientFromStepsInverse = getColorGradientFromSteps(seriesSlow,
offsetSlow, maxStepsForGradient, color.new(slowBaseColorInverse, areaSlowTrans),
slowBaseColorInverse)

// =========================================
// ==== Plot Parameters and Logic Gates ====
// =========================================

// Speed Booleans
isSlow = speedToEmphasize == "Slow"
isNormal = speedToEmphasize == "Normal"
isFast = speedToEmphasize == "Fast"

// Series Colors
seriesSlowColor = showOsc or isSlow ? color.new(slowLineGradientFromSource,
lineSlowTrans) : na
seriesNormalColor = showOsc or isNormal ? color.new(normalLineGradientFromSource,
lineNormalTrans) : na
seriesFastColor = showOsc or isFast ? color.new(fastLineGradientFromSource,
lineFastTrans) : na
seriesSlowMirrorColor = useMirror ? seriesSlowColor : na
seriesNormalMirrorColor = useMirror ? seriesNormalColor : na
seriesFastMirrorColor = useMirror ? seriesFastColor : na
// Series Line Widths
seriesSlowWidth = isSlow ? emphasisWidth : 1
seriesNormalWidth = isNormal ? emphasisWidth : 1
seriesFastWidth = isFast ? emphasisWidth : 1
seriesSlowMirrorWidth = useMirror ? seriesSlowWidth : na
seriesNormalMirrorWidth = useMirror ? seriesNormalWidth : na
seriesFastMirrorWidth = useMirror ? seriesFastWidth : na

// Speed Related Switches

seriesEmphasis = switch
isFast => seriesFast
isNormal => seriesNormal
isSlow => seriesSlow
=> na
//Telegram ==>> https://t.me/+UAk3hqvoD89jZTlk
colorLineEmphasis = switch
isFast => fastLineGradientFromSource
isNormal => normalLineGradientFromSource
isSlow => slowLineGradientFromSource
=> na

colorAreaEmphasis = switch
isFast => fastAreaGradientFromSource
isNormal => normalAreaGradientFromSource
isSlow => slowAreaGradientFromSource
=> na

// Crossover Signals
bearishCross = ta.crossunder(seriesFast, seriesNormal) and seriesNormal > 0
bullishCross = ta.crossover(seriesFast, seriesNormal) and seriesNormal < 0
slowBearishMedianCross = ta.crossunder(seriesSlow, 0)
slowBullishMedianCross = ta.crossover(seriesSlow, 0)
normalBearishMedianCross = ta.crossunder(seriesNormal, 0)
normalBullishMedianCross = ta.crossover(seriesNormal, 0)
fastBearishMedianCross = ta.crossunder(seriesFast, 0)
fastBullishMedianCross = ta.crossover(seriesFast, 0)

// Last Crossover Values

lastBearishCrossValue = ta.valuewhen(condition=bearishCross, source=seriesNormal,
occurrence=1)
lastBullishCrossValue = ta.valuewhen(condition=bullishCross , source=seriesNormal,
occurrence=1)

// Trigger Wave Size Comparison

triggerWaveFactor = sizePercent/100
isSmallerBearishCross = bearishCross and seriesNormal < lastBearishCrossValue *
triggerWaveFactor
isSmallerBullishCross = bullishCross and seriesNormal > lastBullishCrossValue *
triggerWaveFactor

// ===========================
// ==== Kernel Estimators ====
// ===========================

// The following kernel estimators are based on the Gaussian Kernel.

// They are used for:

// (1) Confirming directional changes in the slow oscillator (i.e. a type of
trend filter)
// (2) Visualizing directional changes as a dynamic ribbon (i.e. an additional
oscillator that can crossover with the user specified oscillator of interest)
// (3) Visualizing transient directional changes while in the midst of a larger
uptrend or downtrend (i.e. via color changes on the ribbon)

// Gaussian Kernel with a lookback of 6 bars, starting on bar 6 of the chart

(medium fit)
yhat0 = kernels.gaussian(seriesEmphasis, 6, 6)

// Gaussian Kernel with a lookback of 3 bars, starting on bar 2 of the chart (tight
fit)
yhat1 = kernels.gaussian(seriesEmphasis, 3, 2)

// Trend Assessment based on the relative position of the medium fit kernel to the
slow oscillator
isBearishKernelTrend = yhat0 < seriesSlow
isBullishKernelTrend = yhat0 > seriesSlow

// Divergence Signals
isBearishDivZone = ta.barssince(bearishCross[1]) < divThreshold
isBullishDivZone = ta.barssince(bullishCross[1]) < divThreshold

// Crossover Detection
isBearishTriggerWave = isSmallerBearishCross and isBearishDivZone and
isBearishKernelTrend
isBullishTriggerWave = isSmallerBullishCross and isBullishDivZone and
isBullishKernelTrend

// =======================
// ==== Plots & Fills ====

var position = 0
length := atrLength

minMult = math.max(sensitivity-4, 1)
maxMult = math.min(sensitivity, 26)

if (autopilotMode == "Short Term")

minMult:=1
maxMult := 4
if (autopilotMode == 'Mid Term')
minMult := 5
maxMult := 10
if (autopilotMode == 'Long-Term')
minMult :=8
maxMult :=13

float step = .5

//Trigger error
if minMult > maxMult
runtime.error('Minimum factor is greater than maximum factor in the range')

float perfAlpha = 10
fromCluster = 'Best'

//Optimization
maxIter = 250
maxData = 2500

//Style
bearCss = color.red
bullCss = color.teal

amaBearCss = color.new(color.red, 50)

amaBullCss = color.new(color.teal, 50)

showGradient = true

//Dashboard
showDash = true
//dashboardLocation = input.string('Top Right', 'Location', options = ['Top
Right', 'Bottom Right', 'Bottom Left'], group = 'Dashboard')
textSize = 'Small'

//-----------------------------------------------------------------------------}
//UDT's
//-----------------------------------------------------------------------------{
type supertrend
float upper = hl2
float lower = hl2
float output
float perf = 0
float factor
int trend = 0

type vector
array<float> out

//-----------------------------------------------------------------------------}
//Supertrend
//-----------------------------------------------------------------------------{
var holder = array.new<supertrend>(0)
var factors = array.new<float>(0)

//Populate supertrend type array

if barstate.isfirst
for i = 0 to int((maxMult - minMult) / step)
factors.push(minMult + i * step)
holder.push(supertrend.new())

atr = ta.atr(length)

//Compute Supertrend for multiple factors

k = 0
for factor in factors
get_spt = holder.get(k)

up = hl2 + atr * factor

dn = hl2 - atr * factor

get_spt.trend := close > get_spt.upper ? 1 : close < get_spt.lower ? 0 :

get_spt.trend
get_spt.upper := close[1] < get_spt.upper ? math.min(up, get_spt.upper) : up
get_spt.lower := close[1] > get_spt.lower ? math.max(dn, get_spt.lower) : dn

diff = nz(math.sign(close[1] - get_spt.output))

get_spt.perf += 2/(perfAlpha+1) * (nz(close - close[1]) * diff - get_spt.perf)
get_spt.output := get_spt.trend == 1 ? get_spt.lower : get_spt.upper
get_spt.factor := factor
k += 1

//-----------------------------------------------------------------------------}
//K-means clustering
//-----------------------------------------------------------------------------{
factor_array = array.new<float>(0)
data = array.new<float>(0)

//Populate data arrays

if last_bar_index - bar_index <= maxData
for element in holder
data.push(element.perf)
factor_array.push(element.factor)

//Intitalize centroids using quartiles

centroids = array.new<float>(0)
centroids.push(data.percentile_linear_interpolation(25))
centroids.push(data.percentile_linear_interpolation(50))
centroids.push(data.percentile_linear_interpolation(75))

//Intialize clusters
var array<vector> factors_clusters = na
var array<vector> perfclusters = na

if last_bar_index - bar_index <= maxData

for _ = 0 to maxIter
factors_clusters := array.from(vector.new(array.new<float>(0)),
vector.new(array.new<float>(0)), vector.new(array.new<float>(0)))
perfclusters := array.from(vector.new(array.new<float>(0)),
vector.new(array.new<float>(0)), vector.new(array.new<float>(0)))

//Assign value to cluster

i = 0
for value in data
dist = array.new<float>(0)
for centroid in centroids
dist.push(math.abs(value - centroid))

idx = dist.indexof(dist.min())
perfclusters.get(idx).out.push(value)
factors_clusters.get(idx).out.push(factor_array.get(i))
i += 1

//Update centroids
new_centroids = array.new<float>(0)
for cluster_ in perfclusters
new_centroids.push(cluster_.out.avg())

//Test if centroid changed

if new_centroids.get(0) == centroids.get(0) and new_centroids.get(1) ==
centroids.get(1) and new_centroids.get(2) == centroids.get(2)
 break

centroids := new_centroids

//-----------------------------------------------------------------------------}
//Signals and trailing stop
//-----------------------------------------------------------------------------{
//Get associated supertrend
var float target_factor = na
var float perf_idx = na
var float perf_ama = na

var from = switch fromCluster

'Best' => 2
'Average' => 1
'Worst' => 0

//Performance index denominator

den = ta.ema(math.abs(close - close[1]), int(perfAlpha))

if not na(perfclusters)
//Get average factors within target cluster
target_factor := nz(factors_clusters.get(from).out.avg(), target_factor)

//Get performance index of target cluster

perf_idx := math.max(nz(perfclusters.get(from).out.avg()), 0) / den

//Get new supertrend

var upper = hl2
var lower = hl2
var os = 0

up = hl2 + atr * target_factor

dn = hl2 - atr * target_factor
upper := close[1] < upper ? math.min(up, upper) : up
lower := close[1] > lower ? math.max(dn, lower) : dn
os := close > upper ? 1 : close < lower ? 0 : os
ts = os ? lower : upper

//Get trailing stop adaptive MA

if na(ts[1]) and not na(ts)
perf_ama := ts
else
perf_ama += perf_idx * (ts - perf_ama)

//-----------------------------------------------------------------------------}
//Dashboard
//-----------------------------------------------------------------------------{

//-----------------------------------------------------------------------------{
css = os ? bullCss : bearCss

plot(showTrailingStoploss ? ts : na, 'Trailing Stop', os != os[1] ? na : css,

editable = false)

plot(showMovingAverage? perf_ama:na, 'Trailing Stop AMA',

ta.cross(close, perf_ama) ? na
: close > perf_ama ? amaBullCss : amaBearCss, editable = false)
//Candle coloring
//barcolor(showGradient ? color.from_gradient(perf_idx, 0, 1, color.new(css, 80),
css) : na)

//Signals

if showSignals
if os > os[1] and (signalPresets != "Smart Trail [Filter]" or
smartTrailDirection == 'long') and (signalPresets != "Trend Tracer [Filter]" or
trendTracerDirection==#02ff65) and (signalPresets != "Trend Strength [Filter]" or
trendStrengthMetric >= 25) and (signalPresets != "Trend Catcher [Filter]" or
newTrendCatcherColor == #02ff65) and (signalPresets != "Neo Cloud [Filter]" or
int(lastNeo) >= last5Neo)
int signalStrength = int(perf_idx*10) < 2 ? 1 : int(perf_idx*10) < 4 ? 2 :
int(perf_idx*10) < 5 ? 3 : 4
label.new(n, low-ta.atr(30)/2, signalClassifier ?
str.tostring(signalStrength) : ema50 > ema200 ? "▲+" : "▲"
, color = bullCss
, style = label.style_label_up
, textcolor = color.white
, size = size.small)
position := 1

if os < os[1] and (signalPresets != "Smart Trail [Filter]" or

smartTrailDirection == 'short') and (signalPresets != "Trend Tracer [Filter]" or
trendTracerDirection!=#02ff65) and (signalPresets != "Trend Strength [Filter]" or
trendStrengthMetric >= 25)and (signalPresets != "Trend Catcher [Filter]" or
newTrendCatcherColor != #02ff65) and (signalPresets != "Neo Cloud [Filter]" or
int(lastNeo) <=last5Neo)
int signalStrength = int(perf_idx*10) < 2 ? 1 : int(perf_idx*10) < 4 ? 2 :
int(perf_idx*10) < 5 ? 3 : 4
label.new(n, high+ta.atr(30)/2, signalClassifier ?
str.tostring(signalStrength) : ema50 < ema200 ? "▼+" : "▼"
, color = bearCss
, style = label.style_label_down
, textcolor = color.white
, size = size.small)
position := -1

// =======================

// Signal Plots
//plot(position == 1 and bearishCross ? high+5 : na, title="Bearish Cross",
style=plot.style_cross, linewidth=2, color=c_bearish, offset=-1)
//plot(position == -1 and bearishCross ? high+5 : na, title="Bearish Cross",
style=plot.style_circles, linewidth=2, color=c_bearish, offset=-1)
//plot(position == 1 and isBearishTriggerWave ? high+5 : na, title="Bearish Trigger
Cross", style=plot.style_cross, linewidth=3, color=c_bearish, offset=-1)
//plot(position == -1 and isBearishTriggerWave ? high+5 : na, title="Bearish
Trigger Cross", style=plot.style_circles, linewidth=3, color=c_bearish, offset=-1)
plotchar(bearishCross and position == 1, "Long", "✖", location.abovebar, color =
#4774f5, size = size.tiny, editable = false)
//plotchar(bearishCross and position == -1, "Long", "▼", location.abovebar, color =
c_bearish, size = size.tiny)
plotchar(isBearishTriggerWave and position == 1, "Long", "✖", location.abovebar,
color=#4774f5, size = size.tiny, editable = false)
//plotchar(isBearishTriggerWave and position == -1, "Long", "▼", location.abovebar,
color=c_bearish, size = size.small)
//plot(position == 1 and bullishCross ? low -5: na, title="Bullish Cross", style=
plot.style_circles, linewidth=2, color=c_bullish, offset=-1)
//plot(position == -1 and bullishCross ? low -5: na, title="Bullish Cross", style=
plot.style_cross, linewidth=2, color=c_bullish, offset=-1)
//plot(position == 1 and isBullishTriggerWave ? low -5 : na, title="Bullish Trigger
Cross", style=plot.style_circles, linewidth=3, color=c_bullish, offset=-1)
//plot(position == -1 and isBullishTriggerWave ? low -5 : na, title="Bullish
Trigger Cross", style=plot.style_cross, linewidth=3, color=c_bullish, offset=-1)

//plotchar(bullishCross and position == 1, "Long", "▲", location.belowbar, color =

c_bullish, size = size.tiny)
plotchar(bullishCross and position == -1, "Long", "✖", location.belowbar, color =
#ff7322, size = size.tiny, editable = false)
//plotchar(isBullishTriggerWave and position == 1, "Long", "▲", location.belowbar,
color=c_bullish, size = size.small)
plotchar(isBullishTriggerWave and position == -1, "Long", "✖", location.belowbar,
color=#ff7322, size = size.tiny, editable = false)

// Shit
atrMultiplier = input(2, title="ATR Multiplier")
boxHeightInAtr = atrMultiplier * ta.atr(10)

// Box TP 1

[lowb, midb, highb] = LAF.getTPSLBoxes(6.0)

if (takeProfitBoxes == 'On')
tp1box = box.new(left=bar_index + 1, top=close + midb, right=bar_index + 18,
bottom=close + lowb, border_color=color.new(#3666f5, 0), border_width=2,
border_style=line.style_solid, bgcolor=color.new(#3666f5, 55), text="TP/SL 1 : "
+ str.tostring(close), text_size=size.normal, text_color=color.new(#3666f5, 0))
bottom_tp1 = box.get_bottom(tp1box)
box.delete(tp1box[1])

// Box TP 2
tp2box = box.new(left=bar_index + 1, top=close+highb, right=bar_index + 18,
bottom=close+midb, border_color=color.new(#3666f5, 0), border_width=2,
border_style=line.style_solid, bgcolor=color.new(#3666f5, 65), text="TP/SL 2 : "
+ str.tostring(close), text_size=size.normal, text_color=color.new(#3666f5, 0))
top_tp2 = box.get_top(tp2box)
box.delete(tp2box[1])
// Empty Box
newBox = box.new(left=bar_index + 18, top=top_tp2, right=bar_index + 200,
bottom=bottom_tp1, border_color=color.new(#3666f5, 0), border_width=2,
border_style=line.style_solid, bgcolor=color.new(#3666f5, 50), text=" ",
text_size=size.normal, text_color=color.new(#3666f5, 0))
box.delete(newBox[1])
// SL Box
slBox = box.new(left=bar_index + 3, top=close-lowb, right=bar_index + 18,
bottom=close-midb, border_color=color.new(color.red, 0), border_width=2,
border_style=line.style_solid, bgcolor=color.new(color.red, 66), text="TP/SL 2 :
" + str.tostring(close), text_size=size.normal, text_color=color.new(color.red, 0))
bottom_sl = box.get_top(slBox)
box.delete(slBox[1])
 // SL2 Box
sl2Box = box.new(left=bar_index + 3, top=close-midb, right=bar_index + 18,
bottom=close-highb, border_color=color.new(color.red, 0), border_width=2,
border_style=line.style_solid, bgcolor=color.new(color.red, 65), text="TP/SL 1 :
" + str.tostring(close), text_size=size.normal, text_color=color.new(color.red, 0))
bottom_sl2 = box.get_bottom(sl2Box)
box.delete(sl2Box[1])

// Empty Box SL
Slboxem = box.new(left=bar_index + 18, top=bottom_sl, right=bar_index + 200,
bottom=bottom_sl2, border_color=color.new(color.red, 0), border_width=2,
border_style=line.style_solid, bgcolor=color.new(color.red, 50), text=" ",
text_size=size.normal, text_color=color.new(color.red, 0))
box.delete(Slboxem[1])
//Telegram ==>> https://t.me/+UAk3hqvoD89jZTlk
// Line tp Bottom
var line tpb = na
isLastBar = barstate.islast

if (isLastBar)
tpb := line.new(na, bottom_tp1, na, bottom_tp1, color=color.new(#3666f5,
0), width=2, style=line.style_dashed)

line.set_xy1(tpb, bar_index[50], bottom_tp1)

line.set_xy2(tpb, bar_index + 200, bottom_tp1)
line.delete(tpb[1])
// Line tp top
var line tp2Line = na

if (isLastBar)
tp2Line := line.new(na, top_tp2, na, top_tp2, color=color.new(#3666f5, 0),
width=2, style=line.style_dashed)

line.set_xy1(tp2Line, bar_index[50], top_tp2)

line.set_xy2(tp2Line, bar_index + 200, top_tp2)
line.delete(tp2Line[1])

// Line SL
var line slLine = na

if (isLastBar)
slLine := line.new(na, bottom_sl, na, bottom_sl, color=color.new(color.red,
0), width=2, style=line.style_dashed)

line.set_xy1(slLine, bar_index[50], bottom_sl)

line.set_xy2(slLine, bar_index + 400, bottom_sl)
line.delete(slLine[1])
// Line SL2
var line sl2Line = na

if (isLastBar)
sl2Line := line.new(na, bottom_sl2, na, bottom_sl2,
color=color.new(color.red, 0), width=2, style=line.style_dashed)

line.set_xy1(sl2Line, bar_index[50], bottom_sl2)

line.set_xy2(sl2Line, bar_index + 200, bottom_sl2)
line.delete(sl2Line[1])
###################################################################################
###################################################################################
##################################################

//@version=5
indicator("[X1]", overlay=true, max_lines_count=500, max_labels_count=500,
max_boxes_count=350)

// FUNCTIONS

// Close to Close Volatility

f_coc(x, period, sqrtAnnual) =>
mean = ta.sma(x, period)
s = array.new_float(0)
for i = 0 to period - 1 by 1
array.push(s, math.pow(x[i] - mean, 2))
sqrtAnnual * math.sqrt(array.sum(s) / (period - 1))

// Parkinson Volatility
f_park(period, sqrtAnnual) =>
var LOG2 = math.log(2)
powLogHighLow = math.pow(math.log(high / low), 2)
sqrtAnnual * math.sqrt(1.0 / period * math.sum(1.0 / (4.0 * LOG2) *
powLogHighLow, period))

// Garman Klass Volatility

f_gk(period, sqrtAnnual) =>
var LOG2 = math.log(2)
var SQRT_1_PERIOD = math.sqrt(1 / period)
powLogHighLow = math.pow(math.log(high / low), 2)
powLogCloseOpen = math.pow(math.log(close / open), 2)
tmp = 0.5 * powLogHighLow - (2.0 * LOG2 - 1.0) * powLogCloseOpen
sqrtAnnual * math.sqrt(math.sum(tmp, period)) * SQRT_1_PERIOD

// Rogers Satchell Volatility

f_rsv(period, sqrtAnnual) =>
tmp = math.log(high / close) * math.log(high / open) + math.log(low / close) *
math.log(low / open)
sqrtAnnual * math.sqrt(math.sum(tmp, period) / period)

// Garman Klass Yang Zhang Extension Volatility

f_gkyz(period, sqrtAnnual) =>
var LOG2 = math.log(2)
var SQRT_1_PERIOD = math.sqrt(1 / period)
powLogHighLow = math.pow(math.log(high / low), 2)
powLogCloseOpen = math.pow(math.log(close / open), 2)
lastClose = nz(close[1], close)
powLogOpenClose1 = math.pow(math.log(open / lastClose), 2)
tmp = powLogOpenClose1 + 0.5 * powLogHighLow - (2.0 * LOG2 - 1.0) *
powLogCloseOpen
sqrtAnnual * math.sqrt(math.sum(tmp, period)) * SQRT_1_PERIOD

// Yang Zhang Volatility

f_yz(a, period, sqrtAnnual) =>
o = math.log(open) - math.log(nz(close[1], close))
 u = math.log(high) - math.log(open)
d = math.log(low) - math.log(open)
c = math.log(close) - math.log(open)
nMinusOne = period - 1
avgo = ta.sma(o, period)
avgc = ta.sma(c, period)
so = array.new_float(0)
sc = array.new_float(0)
for i = 0 to period - 1 by 1
array.push(so, math.pow(o[i] - avgo, 2))
array.push(sc, math.pow(c[i] - avgc, 2))
sumo = array.sum(so)
sumc = array.sum(sc)
Vo = sumo / nMinusOne
Vc = sumc / nMinusOne
Vrs = math.sum(u * (u - c) + d * (d - c), period) / period
k = (a - 1.0) / (a + (period + 1.0) / nMinusOne)
sqrtAnnual * math.sqrt(Vo + k * Vc + (1.0 - k) * Vrs)

// Exponentially Weighted Volatility

f_ewma(source, period, sqrtAnnual) =>
var lambda = (period - 1) / (period + 1)
squared = math.pow(source, 2)
float v = na
v := lambda * nz(v[1], squared) + (1.0 - lambda) * squared
sqrtAnnual * math.sqrt(v)

// Mean Absolute Deviation (Adjusted)

f_mad(source, period, sqrtAnnual) =>
var SQRT_HALF_PI = math.sqrt(math.asin(1))
mean = ta.sma(source, period)
S = array.new_float(0)
for i = 0 to period - 1 by 1
array.push(S, math.abs(source[i] - mean))
sumS = array.sum(S)
sqrtAnnual * (sumS / period) * SQRT_HALF_PI

// Median Absolute Deviation

f_mead(source, period, sqrtAnnual) =>
median = ta.percentile_nearest_rank(source, period, 50)
E = 0.0
for i = 0 to period - 1 by 1
E += math.abs(source[i] - median)
E
sqrtAnnual * math.sqrt(2) * (E / period)

//Rescale Function
f_rescale(_src, _size) =>
math.max(0, math.min(_size, int(_src / 100 * _size)))

// label Panel Function

_label(T, color_PnL) =>
label PnL_Label = na
label.delete(PnL_Label[1])
PnL_Label := label.new(time, 0, text=T, color=color_PnL,
textcolor=color.white,size=size.normal, style=label.style_label_left,
xloc=xloc.bar_time, textalign=text.align_left)
label.set_x(PnL_Label, label.get_x(PnL_Label) + math.round(ta.change(time) *
3))
// Round Function
Round(src, digits) =>
p = math.pow(10, digits)
math.round(math.abs(src) * p) / p * math.sign(src)

//Options for Inputs

ON = 'On'
OFF = 'Off'
CTC = 'Close to Close'
PKS = 'Parkinson'
GK = 'Garman Klass'
RS = 'Rogers Satchell'
GKYZ = 'Garman Klass Yang Zhang Extension'
YZ = 'Yang Zhang'
EWMA = 'EWMA'
MAD = 'Mean Absolute Deviation'
MAAD = 'Median Absolute Deviation'
L = 'Line'
SL = 'StepLine'
Ar = 'Area'
CL = 'Columns'

// Settings
H = EWMA
period = 10
Annual = 365
a = 1.34
Plen = 365
Pco = ON
sma = ON
malen = 55
bsg = OFF
stl = CL
lT = 3
i_invert = OFF
bg = OFF
sp = OFF

// bgcolor(bg ? color.new(#000000, 20) : na, title='Dark Background', transp=90)

var sqrtAnnual = math.sqrt(Annual) * 100

logr = math.log(close / close[1])

// Historical Volatiity Models

Hv = if H == CTC
f_coc(logr, period, sqrtAnnual)
else if H == PKS
f_park(period, sqrtAnnual)
else if H == RS
f_rsv(period, sqrtAnnual)
else if H == GK
f_gk(period, sqrtAnnual)
else if H == GKYZ
f_gkyz(period, sqrtAnnual)
else if H == EWMA
f_ewma(logr, period, sqrtAnnual)
else if H == YZ
 f_yz(a, period, sqrtAnnual)
else if H == MAD
f_mad(logr, period, sqrtAnnual)
else
// H == "Median Absolute Deviation"
f_mead(logr, period, sqrtAnnual)

pstyle = stl == L ? plot.style_linebr : stl == SL ? plot.style_stepline : stl == Ar

? plot.style_area : stl == CL ? plot.style_columns : plot.style_line

//Hv Stats
avgHV = ta.sma(Hv, malen)
HVP = ta.percentrank(Hv, Plen)
NearZero = HVP < 1.5 ? 1 : 0
HV50 = ta.percentile_nearest_rank(Hv, Plen, 50)

// // Text Functions
// texthv() =>
// ' HV: ' + str.tostring(Round(Hv, 2))

// textphv() =>
// 'HV 50ᵗʰ Percentile: ' + str.tostring(Round(HV50, 2))

// texthvp() =>
// 'HV Percentile: ' + str.tostring(Round(HVP, 2)) + 'ᵗʰ'

// // Coloring
// var c_ = array.new_color(na)
// if barstate.isfirst
// array.push(c_, #0effff)
// array.push(c_, #00fdf6)
// array.push(c_, #00fbee)
// array.push(c_, #00f9e4)
// array.push(c_, #00f6db)
// array.push(c_, #00f4d1)
// array.push(c_, #13f1c6)
// array.push(c_, #24efbc)
// array.push(c_, #31ecb1)
// array.push(c_, #3ce9a6)
// array.push(c_, #47e69b)
// array.push(c_, #51e390)
// array.push(c_, #5adf85)
// array.push(c_, #62dc7a)
// array.push(c_, #6ad96e)
// array.push(c_, #72d563)
// array.push(c_, #7ad157)
// array.push(c_, #81cd4b)
// array.push(c_, #88ca3f)
// array.push(c_, #8fc532)
// array.push(c_, #96c123)
// array.push(c_, #9cbd0e)
// array.push(c_, #a3b800)
// array.push(c_, #a9b300)
// array.push(c_, #b0ae00)
// array.push(c_, #b6a900)
// array.push(c_, #bca300)
// array.push(c_, #c29e00)
// array.push(c_, #c29e00)
// array.push(c_, #c89800)
// array.push(c_, #ce9100)
// array.push(c_, #d48b00)
// array.push(c_, #da8400)
// array.push(c_, #df7c00)
// array.push(c_, #e57400)
// array.push(c_, #ea6c00)
// array.push(c_, #ef6200)
// array.push(c_, #f35800)
// array.push(c_, #f74c00)
// array.push(c_, #fb3e00)
// array.push(c_, #ff2d00)

// if i_invert
// array.reverse(c_)
// var sizeOf = array.size(c_) - 1
// colorHV = Pco ? array.get(c_, f_rescale(HVP, sizeOf)) : color.aqua

// Plots

// plot(Hv, 'HV', color=colorHV, linewidth=lT, style=plot.style_line)

// plot(sma ? avgHV : na, 'sma', color=color.new(#FFFFFF, 25), linewidth=2)

//bgcolor(Hv > avgHV ? color.lime : na)

// if sp
// _label(H + texthv() + '\n' + textphv() + '\n' + texthvp() + '\n\n',
#000000c0)

// col2 = HVP >= 1 ? color.yellow : HVP <= 1 and HVP >= 0.5 ? color.orange : HVP <=
0.5 ?
//#8D0000 : color.silver
// // bgcolor(bsg and NearZero ? col2 : na, transp=50)

//Custrom MAS
maa = avgHV / 100 * 140
mab = avgHV / 100 * 180
mac = avgHV / 100 * 240
mad = avgHV / 100 * 60
mae = avgHV / 100 * 20

// Auto Sensivity Volatility Band Settings

float volatility = 0.0

if Hv < maa and Hv > avgHV // ilk band ust

volatility := 3.15
else if Hv < mab and Hv > maa // ikinci band ust
volatility := 3.5
else if Hv < mac and Hv > mab // ucuncu band ust
volatility := 3.6
else if Hv > mac // volatilite en ust degerde
volatility := 4
else if Hv < maa and Hv > mad // altdaki ilk band
volatility := 3
else if Hv < mad and Hv > mae // altdaki ikinci band
volatility := 2.85
else if Hv < mae // volatilite butun bandlarin anltinda
volatility := 3
//plot(volatility,color = color.red)

// plot(maa, 'maa', color=color.new(color.aqua, 25))

// plot(mab, 'mab', color=color.new(color.aqua, 25))
// plot(mac, 'mac', color=color.new(color.aqua, 25))
// plot(mad, 'mad', color=color.new(color.aqua, 25))
// plot(mae, 'mae', color=color.new(color.aqua, 25))

//-------------- Elite Algo v22 | https://elitesignals.com -----------------//

// Get user input
enableDashboard = input(true, "Enable Dashboard", group="DASHBOARD SETTINGS")
locationDashboard = input.string("Middle right", "Location", ["Top right", "Top
left", "Middle right", "Middle left", "Bottom right", "Bottom left"],
group="DASHBOARD SETTINGS")
sizeDashboard = input.string("Tiny", "Size", ["Tiny", "Small", "Normal"],
group="DASHBOARD SETTINGS")
colorBackground = input(#2A2E39, "Bg color", group="DASHBOARD SETTINGS")
colorFrame = input(#2A2E39, "Frame color", group="DASHBOARD SETTINGS")
colorBorder = input(#363A45, "Border color", group="DASHBOARD SETTINGS")
showSignals = input(true, "Show signals", group="BUY AND SELL SIGNALS
SETTINGS")
strategy = input.string("Normal", "Strategy", ["Normal", "Confirmed",
"Trend scalper"], group="BUY AND SELL SIGNALS SETTINGS")
sensitivity11 = input.float(defval=1.8, title="Sensitivity", minval=1,
maxval=20, group = 'Signals')
sensitivity = sensitivity11
auto_button = input.bool(defval = true , title = "Auto Sensitivity", group =
'Signals')
consSignalsFilter = input(false, "Consolidation signals filter", group="BUY AND
SELL SIGNALS SETTINGS")
smartSignalsOnly = input(false, "Smart signals only", group="BUY AND SELL SIGNALS
SETTINGS")
candleColors = input(false, "Candle colors", group="BUY AND SELL SIGNALS
SETTINGS")
momentumCandles = input(false, "Momentum candles", group="BUY AND SELL SIGNALS
SETTINGS")
highVolSignals = input(false, "High volume signals only", group="BUY AND SELL
SIGNALS SETTINGS")
enableTrailingSL = input(false, "Enable trailing stop-loss", group="RISK
MANAGEMENT SETTINGS")
usePercSL = input(false, "% Trailing sl", inline="2", group="RISK
MANAGEMENT SETTINGS")
percTrailingSL = input.float(1, "", 0, step=0.1, inline="2", group="RISK
MANAGEMENT SETTINGS")
enableSwings = input(false, "Enable Swing High's & Swing's Low's", inline="3",
group="RISK MANAGEMENT SETTINGS")
periodSwings = input.int(10, "", 2, inline="3", group="RISK MANAGEMENT
SETTINGS")
enableTpSlAreas = input(false, "Enable take profit/stop-loss areas", group="RISK
MANAGEMENT SETTINGS")
useTP1 = input(true, "", inline="4", group="RISK MANAGEMENT SETTINGS")
multTP1 = input.float(1, "TP 1", 0, inline="4", group="RISK MANAGEMENT
SETTINGS")
useTP2 = input(true, "", inline="5", group="RISK MANAGEMENT SETTINGS")
multTP2 = input.float(2, "TP 2", 0, inline="5", group="RISK MANAGEMENT
SETTINGS")
useTP3 = input(true, "", inline="6", group="RISK MANAGEMENT SETTINGS")
multTP3 = input.float(3, "TP 3", 0, inline="6", group="RISK MANAGEMENT
SETTINGS")
tpLabels = input(true, "Take profit labels", group="RISK MANAGEMENT
SETTINGS")
showTrendCloud = input(true, "Show Trend cloud", group="TREND CLOUD SETTINGS")
periodTrendCloud = input.string("New", "Trend cloud period", ["Short term", "Long
term", "New"],group="TREND CLOUD SETTINGS")
signalsTrendCloud = input(false, "Trend only signals", group="TREND CLOUD
SETTINGS")
fastTrendCloud = input(false, "Fast trend cloud", group="TREND CLOUD SETTINGS")
fastTrendCloudLen = input.int(55, "Fast trend cloud", 2, group="TREND CLOUD
SETTINGS")
enableAutoTrend = input(false, "Enable Auto Trendlines", group="AUTO TRENDLINES
SETTINGS")
srcTrendChannel = input(close, "Trend channel source", group="AUTO TRENDLINES
SETTINGS")
lenTrendChannel = input.int(200, "Trend channel loopback", 2, group="AUTO
TRENDLINES SETTINGS")
enableSR = input(false, "Enable support and resistance", group="AUTO
SUPPORT AND RESISTANCE SETTINGS")
lineSrStyle = input.string("Dashed", "Line Style", ["Solid", "Dotted",
"Dashed"], group="AUTO SUPPORT AND RESISTANCE SETTINGS")
lineSrWidth = input.int(2, "Line Width", 1, 4, group="AUTO SUPPORT AND
RESISTANCE SETTINGS")
showCons = input(false, "Consolidation Zones", group="CONSOLIDATION
ZONES")
lbPeriod = input.int(10, "Loopback Period", 2, 50, group="CONSOLIDATION
ZONES")
lenCons = input.int(5, "Min Consolidation Length", 2, 20,
group="CONSOLIDATION ZONES")
paintCons = input(true, "Paint Consolidation Area", group="CONSOLIDATION
ZONES")
colorZone = input(color.new(color.blue, 70), "Zone Color",
group="CONSOLIDATION ZONES")
box_ob = input.bool(false, "Toggle Order Block", group="ORDER BLOCK")
box_hide_gray = input.bool(false, "Hide gray boxes", group="ORDER BLOCK")
bos_type = input.string("High and Low", "MSB trigger", ["High and Low",
"Close and Open"],group="ORDER BLOCK")
box_sv = input.bool(true, "Plot demand boxes", group="ORDER BLOCK")
box_test_delay = input.int(3, "Delay to count test of demand box", 1,
group="ORDER BLOCK")
box_fill_delay = input.int(3, "Delay to count fill of demand box", 1,
group="ORDER BLOCK")
box_test_sv = input.bool(true, "Dim tested demand boxes", group="ORDER
BLOCK")
box_stop_sv = input.bool(true, "Stop plotting filled demand boxes",
group="ORDER BLOCK")
eliteVP = input(false, "Elite volume profile", group="ELITE VOLUME
PROFILE")
colorBorderVP = input(color.new(color.black, 80), "Border color", group="ELITE
VOLUME PROFILE")
colorBuyVP = input(#7F1623, "Buy volume", group="ELITE VOLUME PROFILE")
colorSellVP = input(#00DD00, "Sell volume", group="ELITE VOLUME PROFILE")
offset = input.int(2, "Offset", 2, 20, group="ELITE VOLUME PROFILE")
lookback = input.int(100, "Lookback", 14, 10000, group="ELITE VOLUME
PROFILE")
levelNum = input.int(100, "Number of levels", 10, 1000, group="ELITE
VOLUME PROFILE")
levelWidth = input.int(50, "Level width", 2, 100, group="ELITE VOLUME
PROFILE")

if auto_button == false
sensitivity
else if auto_button == true
sensitivity := volatility

// Functions
f_chartTfInMinutes() =>
float _resInMinutes = timeframe.multiplier * (
timeframe.isseconds ? 1. / 60 :
timeframe.isminutes ? 1. :
timeframe.isdaily ? 60. * 24 :
timeframe.isweekly ? 60. * 24 * 7 :
timeframe.ismonthly ? 60. * 24 * 30.4375 : na)
atr(len) =>
tr = ta.tr
atr = 0.0
atr := nz(atr[1] + (tr - atr[1]) / len, tr)
supertrend(src, factor, len) =>
atr = ta.atr(len)
upperBand = src + factor * atr
lowerBand = src - factor * atr
prevLowerBand = nz(lowerBand[1])
prevUpperBand = nz(upperBand[1])
lowerBand := lowerBand > prevLowerBand or close[1] < prevLowerBand ?
lowerBand : prevLowerBand
upperBand := upperBand < prevUpperBand or close[1] > prevUpperBand ?
upperBand : prevUpperBand
int direction = na
float superTrend = na
prevSuperTrend = superTrend[1]
if prevSuperTrend == prevUpperBand
direction := close > upperBand ? 1 : -1
else
direction := close < lowerBand ? -1 : 1
superTrend := direction == 1 ? lowerBand : direction == -1 ? upperBand : na
dchannel(len)=>
hh = ta.highest(len)
ll = ta.lowest (len)
trend = 0
trend := close > hh[1] ? 1 : close < ll[1] ? -1 : nz(trend[1])
trendScalper(show, len1, len2, len3, colorBull, colorBear, colorBarBull,
colorBarBear) =>
avgOC = math.avg(open, close)
ha_o = 0.0, ha_o := na(ha_o[1]) ? avgOC : (ha_o[1] + ohlc4[1]) / 2
ema1 = ta.ema(ha_o, len1), ema2 = ta.ema(ha_o, len2), ema3 = ta.ema(ha_o, len3)
ris1 = ema1 > ema1[1], ris2 = ema2 > ema2[1], ris3 = ema3 > ema3[1]
fal1 = ema1 < ema1[1], fal2 = ema2 < ema2[1], fal3 = ema3 < ema3[1]
colorEma1 = ris1 ? colorBull : fal1 ? colorBear : na, colorEma2 = ris2 ?
colorBull : fal2 ? colorBear : na, colorEma3 = ris3 ? colorBull : fal3 ? colorBear
: na
fillEma1 = avgOC > ema1 ? colorBull : avgOC < ema1 ? colorBear : na, fillEma2 =
ema1 > ema2 ? colorBull : ema1 < ema2 ? colorBear : na, fillEma3 = ema2 > ema3 ?
colorBull : ema2 < ema3 ? colorBear : na
colorBar = close < ema1 and close < ema2 ? colorBarBear : colorBarBull
[avgOC, show ? ema1 : na, show ? ema2 : na, show ? ema3 : na,
color.new(colorEma1, 55), color.new(colorEma2, 45), color.new(colorEma3, 35),
color.new(fillEma1, 85), color.new (fillEma2, 80), color.new(fillEma3, 75),
colorBar]
candlesMom() =>
[_, _, macd] = ta.macd(close, 12, 26, 9)
(macd > 0 and macd > macd[1]) or (macd < 0 and macd < macd[1])
trailingSL(buy, sell, factor, len, usePerc, perc) =>
atr = atr(len)
upperBand = high + (usePerc ? high * (perc / 100) : factor * atr)
lowerBand = low - (usePerc ? low * (perc / 100) : factor * atr)
prevLowerBand = nz(lowerBand[1])
prevUpperBand = nz(upperBand[1])
lowerBand := lowerBand > prevLowerBand or buy ? lowerBand : prevLowerBand
upperBand := upperBand < prevUpperBand or sell ? upperBand : prevUpperBand
int direction = na
float stop = na
prevSuperTrend = stop[1]
if prevSuperTrend == prevUpperBand
direction := buy ? 1 : -1
else
direction := sell ? -1 : 1
stop := direction == 1 ? lowerBand : direction == -1 ? upperBand : na
add_to_zz(zz, val, bi) =>
array.unshift(zz, bi)
array.unshift(zz, val)
if array.size(zz) > 12
array.pop(zz)
update_zz(zz, val, bi, dir) =>
if array.size(zz) == 0
add_to_zz(zz, val, bi)
else
if dir == 1 and val > array.get(zz, 0) or dir == -1 and val < array.get(zz,
0)
array.set(zz, 0, val)
array.set(zz, 1, bi)
0
float ph = ta.pivothigh(high, 10, 10)
float pl = ta.pivotlow (low , 10, 10)
LSRstyle = lineSrStyle == "Dashed" ? line.style_dashed : lineSrStyle == "Solid" ?
line.style_solid : line.style_dotted
prdhighest = ta.highest(300)
prdlowest = ta.lowest (300)
cwidth = (prdhighest - prdlowest) * 10 / 100
var pivotvals = array.new_float(0)
if ph or pl
array.unshift(pivotvals, ph ? ph : pl)
if array.size(pivotvals) > 20
array.pop(pivotvals)
get_sr_vals(ind) =>
float lo = array.get(pivotvals, ind)
float hi = lo
int numpp = 0
for y = 0 to array.size(pivotvals) - 1 by 1
float cpp = array.get(pivotvals, y)
float wdth = cpp <= lo ? hi - cpp : cpp - lo
if wdth <= cwidth
lo := cpp <= lo ? cpp : lo
hi := cpp > lo ? cpp : hi
numpp += 1
numpp
 [hi, lo, numpp]
var sr_up_level = array.new_float(0)
var sr_dn_level = array.new_float(0)
sr_strength = array.new_float(0)
find_loc(strength) =>
ret = array.size(sr_strength)
for i = ret > 0 ? array.size(sr_strength) - 1 : na to 0 by 1
if strength <= array.get(sr_strength, i)
break
ret := i
ret
ret
check_sr(hi, lo, strength) =>
ret = true
for i = 0 to array.size(sr_up_level) > 0 ? array.size(sr_up_level) - 1 : na by
1
if array.get(sr_up_level, i) >= lo and array.get(sr_up_level, i) <= hi or
array.get(sr_dn_level, i) >= lo and array.get(sr_dn_level, i) <= hi
if strength >= array.get(sr_strength, i)
array.remove(sr_strength, i)
array.remove(sr_up_level, i)
array.remove(sr_dn_level, i)
ret
else
ret := false
ret
break
ret
// Get components
rsi = ta.rsi(close, 14)
vosc = ta.obv - ta.ema(ta.obv, 20)
bs = ta.ema(nz(math.abs((open - close) / (high - low) * 100)), 3)
ema = ta.ema(close, 200)
emaBull = close > ema
equal_tf(res) => str.tonumber(res) == f_chartTfInMinutes()
higher_tf(res) => str.tonumber(res) > f_chartTfInMinutes()
too_small_tf(res) => (timeframe.isweekly and res=="1") or (timeframe.ismonthly and
str.tonumber(res) < 10)
securityNoRep(sym, res, src) =>
bool bull = na
bull := equal_tf(res) ? src : bull
bull := higher_tf(res) ? request.security(sym, res, src, barmerge.gaps_off,
barmerge.lookahead_on) : bull
bull_array = request.security_lower_tf(syminfo.tickerid, higher_tf(res) ?
str.tostring (f_chartTfInMinutes()) : too_small_tf(res) ? (timeframe.isweekly ? "3"
: "10") : res, src)
if array.size(bull_array) > 1 and not equal_tf(res) and not higher_tf(res)
bull := array.pop(bull_array)
array.clear(bull_array)
bull
TF1Bull = securityNoRep(syminfo.tickerid, "1" , emaBull)
TF3Bull = securityNoRep(syminfo.tickerid, "3" , emaBull)
TF5Bull = securityNoRep(syminfo.tickerid, "5" , emaBull)
TF10Bull = securityNoRep(syminfo.tickerid, "10" , emaBull)
TF15Bull = securityNoRep(syminfo.tickerid, "15" , emaBull)
TF30Bull = securityNoRep(syminfo.tickerid, "30" , emaBull)
TF60Bull = securityNoRep(syminfo.tickerid, "60" , emaBull)
TF120Bull = securityNoRep(syminfo.tickerid, "120" , emaBull)
TF240Bull = securityNoRep(syminfo.tickerid, "240" , emaBull)
TF720Bull = securityNoRep(syminfo.tickerid, "720" , emaBull)
TFDBull = securityNoRep(syminfo.tickerid, "1440", emaBull)
ema150 = ta.ema(close, 150)
ema250 = ta.ema(close, 250)
hma55 = ta.hma(close, 55 )
[_, _, macd] = ta.macd(close, 12, 26, 9)
supertrend = supertrend(ohlc4, sensitivity, 10)
maintrend = dchannel(30)
confBull = (ta.crossover (close, supertrend) or (ta.crossover (close, supertrend)
[1] and maintrend[1] < 0)) and macd > 0 and macd > macd[1] and ema150 > ema250 and
hma55 > hma55[2] and maintrend > 0
confBear = (ta.crossunder(close, supertrend) or (ta.crossunder(close, supertrend)
[1] and maintrend[1] > 0)) and macd < 0 and macd < macd[1] and ema150 < ema250 and
hma55 < hma55[2] and maintrend < 0
trendcloud = supertrend(ohlc4, periodTrendCloud == "Long term" ? 7 : 4, 10)
hma = fastTrendCloud ? ta.hma(close, fastTrendCloudLen) : na
none = close > 0
[_, _, adx] = ta.dmi(14, 14)
consFilter = adx > 20
smartFilter = ta.ema(close, 200)
volFilter = (ta.ema(volume, 25) - ta.ema(volume, 26)) / ta.ema(volume, 26) > 0
trendFilter = trendcloud
bull = (strategy == "Normal" ? ta.crossover (close, supertrend) : confBull and not
confBull[1]) and strategy != "Trend scalper" and (smartSignalsOnly ? close >
smartFilter : none) and (consSignalsFilter ? consFilter : none) and
(highVolSignals ? volFilter : none) and (signalsTrendCloud ? (periodTrendCloud ==
"New" ? ema150 > ema250 : close > trendFilter) : none)
bear = (strategy == "Normal" ? ta.crossunder(close, supertrend) : confBear and not
confBear[1]) and strategy != "Trend scalper" and (smartSignalsOnly ? close <
smartFilter : none) and (consSignalsFilter ? consFilter : none) and
(highVolSignals ? volFilter : none) and (signalsTrendCloud ? (periodTrendCloud ==
"New" ? ema150 < ema250 : close < trendFilter) : none)
countBull = ta.barssince(bull)
countBear = ta.barssince(bear)
trigger = nz(countBull, bar_index) < nz(countBear, bar_index) ? 1 : 0
[avgOC, ema5, ema9, ema21, colorEma5, colorEma9, colorEma21, fillEma5, fillEma9,
fillEma21, colorBar] = trendScalper(strategy == "Trend scalper" ? true : false, 5,
9, 21, color.green,color.red, #00DD00, #DD0000)

trailingStop = trailingSL(bull, bear, 2.2, 14, usePercSL, percTrailingSL)

float _ph = ta.highestbars(high, periodSwings) == 0 ? high : na
float _pl = ta.lowestbars (low, periodSwings) == 0 ? low : na
var _dir = 0, dir_ = _pl and na(_ph) ? -1 : _dir, _dir := _ph and na(_pl) ? 1 :
dir_, dirChg = ta.change(_dir)
var zz = array.new_float(0), zzOld = array.copy(zz)
float zzLive = _ph or _pl ? (dirChg ? add_to_zz(zz, _dir == 1 ? _ph : _pl,
bar_index) : update_zz (zz, _dir == 1 ? _ph : _pl, bar_index, _dir)) : na
aA = ta.wma(srcTrendChannel, lenTrendChannel), b = ta.sma(srcTrendChannel,
lenTrendChannel)
A = 4 * b - 3 * aA, B = 3 * aA - 2 * b
m = (A - B) / (lenTrendChannel - 1)
d = 0., for i = 0 to lenTrendChannel - 1 by 1
l = B + m * i
d += math.pow(srcTrendChannel[i] - l, 2)
rmse = math.sqrt(d / (lenTrendChannel - 1)) * 2
float hb_ = ta.highestbars(lbPeriod) == 0 ? high : na
float lb_ = ta.lowestbars (lbPeriod) == 0 ? low : na
var int dir = 0
float zz_ = na
float pp = na
var int consCnt = 0
var float condHi = na
var float condLo = na
float H_ = ta.highest(lenCons)
float L_ = ta.lowest (lenCons)
var line lineUp = na
var line lineDn = na
bool breakUp = false
bool breakDn = false
var float[] pvh1_price = array.new_float(1000, na)
var int[] pvh1_time = array.new_int (1000, na)
var float[] pvl1_price = array.new_float(1000, na)
var int[] pvl1_time = array.new_int (1000, na)
var float[] pvh2_price = array.new_float(1000, na)
var int[] pvh2_time = array.new_int (1000, na)
var float[] pvl2_price = array.new_float(1000, na)
var int[] pvl2_time = array.new_int (1000, na)
var float htcmrll_price = na
var int htcmrll_time = na
var float ltcmrhh_price = na
var int ltcmrhh_time = na
var box[] long_boxes = array.new_box()
var box[] short_boxes = array.new_box()
var float temp_pv_0 = na
var float temp_pv_1 = na
var float temp_pv_2 = na
bool pvh = high < high[1] and high[1] > high[2]
bool pvl = low > low [1] and low [1] < low [2]
int pv1_time = bar_index[1]
float pv1_high = high[1]
float pv1_low = low [1]
float trigger_high = bos_type == "High and Low" ? high : math.max(open,
close)
float trigger_low = bos_type == "High and Low" ? low : math.min(open,
close)
rangeHigh = ta.highest(high, lookback)
rangeLow = ta.lowest(low, lookback)
rangeHeight = rangeHigh - rangeLow
histogramHeight = rangeHeight / levelNum
histogramLowList = array.new_float(levelNum, na)
histogramHighList = array.new_float(levelNum, na)
histogramBuyVolumeList = array.new_float(levelNum, 0.0)
histogramSellVolumeList = array.new_float(levelNum, 0.0)
var buyBars = array.new_box(365, na)
for i = 0 to 364
box.delete(array.get(buyBars, i))
var sellBars = array.new_box(365, na)
for i = 0 to 364
box.delete(array.get(sellBars, i))
// Colors
green = #00DD00, green50 = color.new(green, 50), green20 = color.new(green,
80)
red = #DD0000, red50 = color.new(red, 50), red20 = color.new(red, 80)
silver = #B2B5BE, silver50 = color.new(silver, 50), silver20 = color.new(silver,
80)
// Plots
atrBand = usePercSL ? (trigger ? low : high) * (percTrailingSL / 100) : ta.atr(14)
* 2.2
atrStop = trigger ? low - atrBand : high + atrBand
lastTrade(src) => ta.valuewhen(bull or bear, src, 0)
entry_y = lastTrade(close)
stop_y = lastTrade(atrStop)
tp1_y = (entry_y-lastTrade(atrStop))*multTP1 + entry_y
tp2_y = (entry_y-lastTrade(atrStop))*multTP2 + entry_y
tp3_y = (entry_y-lastTrade(atrStop))*multTP3 + entry_y
labelTpSl(cond, y, txt, color) =>
label labelTpSl = enableTpSlAreas and cond ? label.new(bar_index + 1, y, txt,
xloc.bar_index, yloc.price, color, label.style_label_left, color.white,
size.normal) : na
label.delete(labelTpSl[1])
labelTpSl(none, entry_y, "Entry : " +
str.tostring(math.round_to_mintick(entry_y)),color.orange)

labelTpSl(none, stop_y , "Stop loss : " +

str.tostring(math.round_to_mintick(atrStop)), color.red)
labelTpSl(useTP1 and multTP1 != 0, tp1_y, "TP 1 : " +
str.tostring(math.round_to_mintick (tp1_y)), color.green)
labelTpSl(useTP2 and multTP2 != 0, tp2_y, "TP 2 : " +
str.tostring(math.round_to_mintick (tp2_y)), color.green)
labelTpSl(useTP3 and multTP3 != 0, tp3_y, "TP 3 : " +
str.tostring(math.round_to_mintick (tp3_y)), color.green)
lineTpSl(cond, y, color, style) =>
line lineTpSl = enableTpSlAreas and cond ? line.new(bar_index - (trigger ?
countBull : countBear), y, bar_index + 1, y, xloc.bar_index, extend.none, color,
style) : na
line.delete(lineTpSl[1])
lineTpSl(none, entry_y, color.orange, line.style_dashed)
lineTpSl(none, stop_y , color.red , line.style_solid )
lineTpSl(useTP1 and multTP1 != 0, tp1_y, color.green, line.style_dotted)
lineTpSl(useTP2 and multTP2 != 0, tp2_y, color.green, line.style_dotted)
lineTpSl(useTP3 and multTP3 != 0, tp3_y, color.green, line.style_dotted)
var dashboard_loc = locationDashboard == "Top right" ? position.top_right :
locationDashboard == "Top left" ? position.top_left : locationDashboard == "Middle
right" ? position.middle_right : locationDashboard == "Middle left" ?
position.middle_left : locationDashboard == "Bottom right" ? position.bottom_right
: position.bottom_left
var dashboard_size = sizeDashboard == "Tiny" ? size.tiny : sizeDashboard == "Small"
? size.small : size.normal
var dashboard = table.new(dashboard_loc, 2, 20, colorBackground, colorFrame,
3, colorBorder, 3)
dashboard_cell(column, row, txt) => table.cell(dashboard, column, row, txt, 0, 0,
color.white, text_size=dashboard_size)
dashboard_cell_bg(column, row, col) => table.cell_set_bgcolor(dashboard, column,
row, col)
if barstate.islast and enableDashboard
dashboard_cell(0, 0 , "Current strategy")
dashboard_cell(0, 1 , "Current sensitivity")
dashboard_cell(0, 2 , "Current Position")
dashboard_cell(0, 3 , "Current trend")
dashboard_cell(0, 4 , "Trend strength")
dashboard_cell(0, 5 , "Volume")
dashboard_cell(0, 6 , "Volatility")
dashboard_cell(0, 7 , "Momentum")
dashboard_cell(0, 8 , "Timeframe trends??"), table.merge_cells(dashboard, 0, 8,
1, 8)
dashboard_cell(0, 9 , "1 min")
dashboard_cell(0, 10, "3 min")
 dashboard_cell(0, 11, "5 min")
dashboard_cell(0, 12, "10 min")
dashboard_cell(0, 13, "15 min")
dashboard_cell(0, 14, "30 min")
dashboard_cell(0, 15, "1 Hour")
dashboard_cell(0, 16, "2 Hour")
dashboard_cell(0, 17, "4 Hour")
dashboard_cell(0, 18, "12 Hour")
dashboard_cell(0, 19, "Daily")
dashboard_cell(1, 0 , strategy)
dashboard_cell(1, 1 , str.tostring(sensitivity))
dashboard_cell(1, 2 , strategy != "Trend scalper" ? (trigger ? "Buy" :
"Sell") : ""), dashboard_cell_bg(1, 2, strategy != "Trend scalper" ? (trigger ?
color.green : color.red) : colorBackground)
dashboard_cell(1, 3 , emaBull ? "Bullish" : "Bearish"), dashboard_cell_bg(1, 3,
emaBull ? color.green : color.red)
dashboard_cell(1, 4 , str.tostring(bs, "0.0") + " %")
dashboard_cell(1, 5 , vosc > 0 ? "Bullish" : "Bearish"), dashboard_cell_bg(1,
5, vosc > 0 ? color.green : color.red)
dashboard_cell(1, 6 , adx > 20 ? "Trending ??" : "Ranging ??"),
dashboard_cell_bg(1, 6, adx > 20 ? color.green : color.orange)
dashboard_cell(1, 7 , rsi > 50 ? "Bullish" : "Bearish"), dashboard_cell_bg(1,
7, rsi > 50 ? color.green : color.red)
dashboard_cell(1, 9 , TF1Bull ? "Bullish" : "Bearish"), dashboard_cell_bg(1,
9 , TF1Bull ? color.green : color.red)
dashboard_cell(1, 10, TF3Bull ? "Bullish" : "Bearish"), dashboard_cell_bg(1,
10, TF3Bull ? color.green : color.red)
dashboard_cell(1, 11, TF5Bull ? "Bullish" : "Bearish"), dashboard_cell_bg(1,
11, TF5Bull ? color.green : color.red)
dashboard_cell(1, 12, TF10Bull ? "Bullish" : "Bearish"), dashboard_cell_bg(1,
12, TF10Bull ? color.green : color.red)
dashboard_cell(1, 13, TF15Bull ? "Bullish" : "Bearish"), dashboard_cell_bg(1,
13, TF15Bull ? color.green : color.red)
dashboard_cell(1, 14, TF30Bull ? "Bullish" : "Bearish"), dashboard_cell_bg(1,
14, TF30Bull ? color.green : color.red)
dashboard_cell(1, 15, TF60Bull ? "Bullish" : "Bearish"), dashboard_cell_bg(1,
15, TF60Bull ? color.green : color.red)
dashboard_cell(1, 16, TF120Bull ? "Bullish" : "Bearish"), dashboard_cell_bg(1,
16, TF120Bull ? color.green : color.red)
dashboard_cell(1, 17, TF240Bull ? "Bullish" : "Bearish"), dashboard_cell_bg(1,
17, TF240Bull ? color.green : color.red)
dashboard_cell(1, 18, TF720Bull ? "Bullish" : "Bearish"), dashboard_cell_bg(1,
18, TF720Bull ? color.green : color.red)
dashboard_cell(1, 19, TFDBull ? "Bullish" : "Bearish"), dashboard_cell_bg(1,
19, TFDBull ? color.green : color.red)

l(css, k) =>
line lr = enableAutoTrend ? line.new(bar_index - lenTrendChannel + 1, A + k,
bar_index, B + k, extend=extend.right, color=css) : na
line.delete(lr[1])
l(color.blue, rmse), l(color.blue, 0), l(color.blue, -rmse)

//
//================================================================
//=============
// INDICATOR 11 - Trend Confidence
//================================================================
//============
// CCI

TM_Long = ta.cci(close, 14) > 0

TM_Short = ta.cci(close, 14) < 0

//color1 = ta.cci(close, 5) >= 0 ? #0022FC : #FC0400

//plot(MagicTrend, color=color1, linewidth=3)

// ADX
lenadx = 21
lensig = 21
limadx = 34

ADX_up = ta.change(high)
ADX_down = -ta.change(low)
trur = ta.rma(ta.tr, lenadx)
plus = fixnan(100 * ta.rma(ADX_up > ADX_down and ADX_up > 0 ? ADX_up : 0, lenadx) /
trur)
minus = fixnan(100 * ta.rma(ADX_down > ADX_up and ADX_down > 0 ? ADX_down : 0,
lenadx) / trur)
sum = plus + minus
adxxs = 100 * ta.rma(math.abs(plus - minus) / (sum == 0 ? 1 : sum), lensig)

macol = adxxs > limadx and plus > minus ? color.lime : adxxs > limadx and plus <
minus ? color.red : color.black

ADX_Long = adxxs > limadx and plus > minus

ADX_Short = adxxs > limadx and plus < minus

//Acumulation/Distribution
ACC_Dist = ta.sma(ta.accdist, 34)

ACC_Long = ta.accdist > ACC_Dist

ACC_Short = ta.accdist < ACC_Dist

// MFI

MFI = ta.mfi(close , 21)

MFI_SMA = ta.sma (MFI, 13)

MFI_Long = MFI > MFI_SMA

MFI_Short = MFI < MFI_SMA

// Momentum Linear Regression

mom = ta.mom(close, 21)

lrmom = ta.linreg(mom, 28, 0)

MOML_Long = lrmom > lrmom[1]

MOML_Short = lrmom < lrmom[1]
//
entry_long = true
entry_short = true

Long_Signal_Strength = 0
Short_Signal_Strength = 0

if entry_long
if TM_Long
Long_Signal_Strength += 1
if ADX_Long
Long_Signal_Strength += 1
if ACC_Long
Long_Signal_Strength += 1
if MFI_Long
Long_Signal_Strength += 1
if MOML_Long
Long_Signal_Strength += 1

if entry_short
if TM_Short
Short_Signal_Strength += 1
if ADX_Short
Short_Signal_Strength += 1
if ACC_Short
Short_Signal_Strength += 1
if MFI_Short
Short_Signal_Strength += 1
if MOML_Short
Short_Signal_Strength += 1
//Plot Buy/Sell Signals on chart

smartbuysigtex = "Smart Buy\n" + str.tostring(Long_Signal_Strength) + "??"

smartselsigtex = str.tostring(Short_Signal_Strength) + "??\n" + "Smart Sell"
buysigtex = "Buy\n" + str.tostring(Long_Signal_Strength) + "??"
selsigtex = str.tostring(Short_Signal_Strength) + "??\n" + "Sell"
enter_Long_Text = close > smartFilter ? smartbuysigtex : buysigtex
enter_Short_Text = close < smartFilter ? smartselsigtex : selsigtex
//
buy = showSignals and bull ? label.new(bar_index, low ,enter_Long_Text ,
xloc.bar_index, yloc.belowbar, color.green, label.style_label_up , color.white,
size.normal) : na
sell = showSignals and bear ? label.new(bar_index, high,enter_Short_Text ,
xloc.bar_index, yloc.abovebar, color.red , label.style_label_down, color.white,
size.normal) : na
//
tpLabels(tp) =>
tp1Bull = ta.crossover (rsi, 70), tp2Bull = ta.crossover (rsi, 75), tp3Bull =
ta.crossover (rsi, 80)
tp1Bear = ta.crossunder(rsi, 30), tp2Bear = ta.crossunder(rsi, 25), tp3Bear =
ta.crossunder (rsi, 20)
tp1Bull := tp1Bull and (nz(ta.barssince(tp1Bull)[1], 9999) > countBull),
tp2Bull := tp2Bull and (ta.barssince(tp1Bull)[1] <= countBull), tp2Bull := tp2Bull
and (nz(ta.barssince(tp2Bull)[1], 9999) > countBull), tp3Bull := tp3Bull and
(ta.barssince(tp2Bull)[1] <= countBull), tp3Bull := tp3Bull and
(nz(ta.barssince(tp3Bull)[1], 9999) > countBull)
tp1Bear := tp1Bear and (nz(ta.barssince(tp1Bear)[1], 9999) > countBear),
tp2Bear := tp2Bear and (ta.barssince(tp1Bear)[1] <= countBear), tp2Bear := tp2Bear
and (nz(ta.barssince(tp2Bear) [1], 9999) > countBear), tp3Bear := tp3Bear and
(ta.barssince(tp2Bear)[1] <= countBear), tp3Bear := tp3Bear and
(nz(ta.barssince(tp3Bear)[1], 9999) > countBear)
if strategy != "Trend scalper" and tpLabels
trigger ? (tp == 1 ? tp1Bull : tp == 2 ? tp2Bull : tp3Bull) : (tp == 1 ?
tp1Bear : tp == 2 ? tp2Bear : tp3Bear)
plotshape(tpLabels(1), "", shape.cross, location.abovebar, trigger ? green : na ,
0, "TP 1", trigger ? green : na , false)
plotshape(tpLabels(2), "", shape.cross, location.abovebar, trigger ? green : na ,
0, "TP 2", trigger ? green : na , false)
plotshape(tpLabels(3), "", shape.cross, location.abovebar, trigger ? green : na ,
0, "TP 3", trigger ? green : na , false)
plotshape(tpLabels(1), "", shape.cross, location.belowbar, trigger ? na : red,
0, "TP 1", trigger ? na : red, false)
plotshape(tpLabels(2), "", shape.cross, location.belowbar, trigger ? na : red,
0, "TP 2", trigger ? na : red, false)
plotshape(tpLabels(3), "", shape.cross, location.belowbar, trigger ? na : red,
0, "TP 3", trigger ? na : red, false)
var label zzLabel = na
if array.size(zz) > 12 and enableSwings
if array.get(zz, 0) != array.get(zzOld, 0) or array.get(zz, 1) !=
array.get(zzOld, 1)
if array.get(zz, 2) == array.get(zzOld, 2) and array.get(zz, 3) ==
array.get(zzOld, 3)
label.delete(zzLabel)
zzLabel := label.new(math.round(array.get(zz, 1)), array.get(zz, 0), _dir
== 1 ? array.get(zz, 0) > array.get(zz, 4) ? ((array.get(zz, 4) < array.get(zz, 8))
? "High" : "HH") : "LH" : array.get(zz, 0) < array.get(zz, 4) ? ((array.get(zz, 4)
> array.get(zz, 8)) ? "Low" : "LL") : "HL", xloc.bar_index, yloc.price,
color.new(color.white, 100), _dir == 1 ? label.style_label_down :
label.style_label_up, _dir == 1 ? color.green : color.red)
var sr_lines = array.new_line(11, na)
for x = 1 to 10 by 1
line.set_color(array.get(sr_lines, x), color=line.get_y1(array.get(sr_lines,
x)) >= close ? color.red : color.lime)

if ph or pl
array.clear(sr_up_level)
array.clear(sr_dn_level)
array.clear(sr_strength)
for x = 0 to array.size(pivotvals) - 1 by 1
[hi, lo, strength] = get_sr_vals(x)
if check_sr(hi, lo, strength)
loc = find_loc(strength)
if loc < 5 and strength >= 2
array.insert(sr_strength, loc, strength)
array.insert(sr_up_level, loc, hi)
array.insert(sr_dn_level, loc, lo)
if array.size(sr_strength) > (enableSR ? 5 : 0)
array.pop(sr_strength)
array.pop(sr_up_level)
array.pop(sr_dn_level)
for x = 1 to 10 by 1
line.delete(array.get(sr_lines, x))
for x = 0 to array.size(sr_up_level) > 0 ? array.size(sr_up_level) - 1 : na by
1
float mid = math.round_to_mintick((array.get(sr_up_level, x) +
array.get(sr_dn_level, x)) / 2)
rate = 100 * (mid - close) / close
 array.set(sr_lines, x + 1, line.new(x1=bar_index, y1=mid, x2=bar_index - 1,
y2=mid, extend=extend.both, color=mid >= close ? color.red : color.lime,
style=LSRstyle, width=lineSrWidth))
if showCons and barstate.isconfirmed
dir := hb_ and na(lb_) ? 1 : lb_ and na(hb_) ? -1 : dir
if hb_ and lb_
if dir == 1
zz_ := hb_
else
zz_ := lb_
else
zz_ := hb_ ? hb_ : lb_ ? lb_ : na
for x = 0 to 1000
if na(close) or dir != dir[x]
break
if zz_[x]
if na(pp)
pp := zz_[x]
else
if dir[x] == 1 and zz_[x] > pp
pp := zz_[x]
if dir[x] == -1 and zz_[x] < pp
pp := zz_[x]
if pp != pp[1]
if consCnt > lenCons
if pp > condHi
breakUp := true
if pp < condLo
breakDn := true
if consCnt > 0 and pp <= condHi and pp >= condLo
consCnt += 1
else
consCnt := 0
else
consCnt += 1
if consCnt >= lenCons
if consCnt == lenCons
condHi := H_
condLo := L_
else
line.delete(lineUp)
line.delete(lineDn)
condHi := math.max(condHi, high)
condLo := math.min(condLo, low )
lineUp := line.new(bar_index, condHi , bar_index - consCnt, condHi ,
color=color.red , style=line.style_dashed)
lineDn := line.new(bar_index, condLo , bar_index - consCnt, condLo ,
color=color.lime, style=line.style_dashed)
fill(plot(condHi, "", na, 1, plot.style_stepline, editable=false), plot(condLo, "",
na, 1, plot.style_stepline, editable=false), paintCons and consCnt > lenCons ?
colorZone : na, "", false)
if box_ob and barstate.isconfirmed
if pvh
array.pop(pvh1_price)
array.pop(pvh1_time)
array.unshift(pvh1_price, pv1_high)
array.unshift(pvh1_time, pv1_time)
if array.size(pvh1_price) > 2
temp_pv_0 := array.get(pvh1_price, 0)
 temp_pv_1 := array.get(pvh1_price, 1)
temp_pv_2 := array.get(pvh1_price, 2)
if temp_pv_0 > temp_pv_1
for i = 0 to array.size(pvl1_time) - 1 by 1
temp_ltcmrhh_time = array.get(pvl1_time, i)
if temp_ltcmrhh_time < array.get(pvh1_time, 0)
ltcmrhh_price := array.get(pvl1_price, i)
ltcmrhh_time := temp_ltcmrhh_time
break
if temp_pv_0 < temp_pv_1 and temp_pv_1 > temp_pv_2
array.pop(pvh2_price)
array.pop(pvh2_time)
array.unshift(pvh2_price, temp_pv_1)
array.unshift(pvh2_time, array.get(pvh1_time, 1))
if pvl
array.pop(pvl1_price)
array.pop(pvl1_time)
array.unshift(pvl1_price, pv1_low)
array.unshift(pvl1_time, pv1_time)
if array.size(pvl1_price) > 2
temp_pv_0 := array.get(pvl1_price, 0)
temp_pv_1 := array.get(pvl1_price, 1)
temp_pv_2 := array.get(pvl1_price, 2)
if temp_pv_0 < temp_pv_1
for i = 0 to array.size(pvh1_time) - 1 by 1
temp_htcmrll_time = array.get(pvh1_time, i)
if temp_htcmrll_time < array.get(pvl1_time, 0)
htcmrll_price := array.get(pvh1_price, i)
htcmrll_time := temp_htcmrll_time
break
if temp_pv_0 > temp_pv_1 and temp_pv_1 < temp_pv_2
array.pop(pvl2_price)
array.pop(pvl2_time)
array.unshift(pvl2_price, temp_pv_1)
array.unshift(pvl2_time, array.get(pvl1_time, 1))
if trigger_high > htcmrll_price
if box_sv
loBox = box.new(left=array.get(pvl1_time, 0),
top=math.min(high[bar_index - array.get (pvl1_time, 0)], high[bar_index -
array.get(pvl1_time, 0) + 1]), right=bar_index, bottom=array.get(pvl1_price, 0),
bgcolor=color.rgb(0, 255, 0, 80), border_color=color.rgb(0, 255, 0, 80),
extend=extend.right)
if array.size(long_boxes) >= 25
box.delete(array.shift(long_boxes))
array.push(long_boxes, loBox)
htcmrll_price := na
htcmrll_price
if trigger_low < ltcmrhh_price
if box_sv
hiBox = box.new(left=array.get(pvh1_time, 0), top=array.get(pvh1_price,
0), right=bar_index, bottom=math.max(low[bar_index - array.get(pvh1_time, 0)],
low[bar_index - array.get(pvh1_time, 0) + 1]), bgcolor=color.rgb(255, 0, 0, 80),
border_color=color.rgb(255, 0, 0, 80), extend=extend.right)
if array.size(short_boxes) >= 25
box.delete(array.shift(short_boxes))
array.push(short_boxes, hiBox)
ltcmrhh_price := na
ltcmrhh_price
if array.size(short_boxes) > 0
 for i = array.size(short_boxes) - 1 to 0 by 1
tbox = array.get(short_boxes, i)
top = box.get_top(tbox)
bottom = box.get_bottom(tbox)
if trigger_high > bottom and box.get_left(tbox) + box_test_delay <
bar_index and box_test_sv
if box_hide_gray
box.set_bgcolor(tbox, #00000000)
box.set_border_color(tbox, #00000000)
else
box.set_bgcolor(tbox, color.rgb(192, 192, 192, 80))
box.set_border_color(tbox, color.rgb(192, 192, 192, 80))
if trigger_high > top and box.get_left(tbox) + box_fill_delay <
bar_index
if box_stop_sv
box.set_right(tbox, bar_index)
box.set_extend(tbox, extend.none)
array.remove(short_boxes, i)
if array.size(long_boxes) > 0
for i = array.size(long_boxes) - 1 to 0 by 1
lbox = array.get(long_boxes, i)
top = box.get_top(lbox)
bottom = box.get_bottom(lbox)
if trigger_low < top and box.get_left(lbox) + box_test_delay <
bar_index and box_test_sv
if box_hide_gray
box.set_bgcolor(lbox, #00000000)
box.set_border_color(lbox, #00000000)
else
box.set_bgcolor(lbox, color.rgb(192, 192, 192, 80))
box.set_border_color(lbox, color.rgb(192, 192, 192, 80))
if trigger_low < bottom and box.get_left(lbox) + box_fill_delay <
bar_index
if box_stop_sv
box.set_right(lbox, bar_index)
box.set_extend(lbox, extend.none)
array.remove(long_boxes, i)
if barstate.islast and eliteVP
for i = 0 to levelNum - 1
histogramLow = rangeLow + histogramHeight * i
histogramHigh = rangeLow + histogramHeight * (i + 1)
array.set(histogramLowList, i, histogramLow)
array.set(histogramHighList, i, histogramHigh)
for i = 0 to lookback - 1
currentBarHeight = high[i] - low[i]
currentBuyVolume = high[i] == low[i] ? 0 : volume[i] * (close[i] - low
[i]) / currentBarHeight
currentSellVolume = high[i] == low[i] ? 0 : volume[i] * (high [i] -
close[i]) / currentBarHeight
for j = 0 to levelNum - 1
histogramLow = array.get(histogramLowList, j)
histogramHigh = array.get(histogramHighList, j)
target = math.max(histogramHigh, high[i]) - math.min(histogramLow,
low[i]) - (math.max (histogramHigh, high[i]) - math.min(histogramHigh, high[i])) -
(math.max(histogramLow, low[i]) - math.min(histogramLow, low[i]))
histogramVolumePercentage = target / currentBarHeight
histogramBuyVolume = array.get(histogramBuyVolumeList, j)
histogramSellVolume = array.get(histogramSellVolumeList, j)
if histogramVolumePercentage > 0
 array.set(histogramBuyVolumeList, j, histogramBuyVolume +
currentBuyVolume * histogramVolumePercentage)
array.set(histogramSellVolumeList, j, histogramSellVolume +
currentSellVolume * histogramVolumePercentage)
highestHistogramVolume = 0.0
for i = 0 to levelNum - 1
histogramBuyVolume = array.get(histogramBuyVolumeList, i)
histogramSellVolume = array.get(histogramSellVolumeList, i)
histogramVolume = histogramBuyVolume + histogramSellVolume
highestHistogramVolume := math.max(highestHistogramVolume, histogramVolume)
highestHistogramVolume
for i = 0 to levelNum - 1
histogramLow = array.get(histogramLowList, i)
histogramHigh = array.get(histogramHighList, i)
histogramBuyVolume = array.get(histogramBuyVolumeList, i)
histogramSellVolume = array.get(histogramSellVolumeList, i)
histogramVolume = histogramBuyVolume + histogramSellVolume
histogramWidth = levelWidth * histogramVolume / highestHistogramVolume
histogramBuyWidth = math.floor(histogramWidth * histogramBuyVolume /
histogramVolume)
histogramSellWidth = math.floor(histogramWidth * histogramSellVolume /
histogramVolume)
array.set(buyBars , i, box.new(bar_index + offset + levelWidth - 1 -
histogramBuyWidth, histogramHigh, bar_index + offset + levelWidth - 1 ,
histogramLow, colorBorderVP, bgcolor=colorBuyVP ))
array.set(sellBars, i, box.new(bar_index + offset + levelWidth - 1 -
histogramBuyWidth, histogramHigh, bar_index + offset + levelWidth - 1 -
histogramBuyWidth - histogramSellWidth, histogramLow, colorBorderVP,
bgcolor=colorSellVP))
barcolor(momentumCandles and candlesMom() ? color.purple : candleColors ? (strategy
== "Trend scalper" ? colorBar : na(countBull) and na(countBear) ? color.gray :
trigger ? green : red) : na, editable=false)
fill(plot(showTrendCloud and periodTrendCloud == "New" ? ema150 : na, "", na,
editable=false), plot(showTrendCloud and periodTrendCloud == "New" ? ema250 : na,
"", na, editable=false), ema150 > ema250 ? color.new(color.green, 70) : ema150 <
ema250 ? color.new(color.red, 70) : na)
plot(enableTrailingSL and trigger and nz(ta.barssince(low < trailingStop),
bar_index) > countBull ? trailingStop : na, "", green, 1, plot.style_linebr,
editable=false)
plot(enableTrailingSL and not trigger and nz(ta.barssince(high > trailingStop),
bar_index) > countBear ? trailingStop : na, "", red , 1, plot.style_linebr,
editable=false)
p0 = plot(avgOC, "", na , editable=false)
p1 = plot(ema5 , "", colorEma5 , editable=false)
p2 = plot(ema9 , "", colorEma9 , editable=false)
p3 = plot(ema21, "", colorEma21, editable=false)
fill(p0, p1, fillEma5 )
fill(p1, p2, fillEma9 )
fill(p2, p3, fillEma21)
fill(plot(showTrendCloud and periodTrendCloud != "New" and trendcloud != 0 and
close > trendcloud ? trendcloud : na, "", color.green, 1, plot.style_linebr,
editable=false), p0, color.new (color.green, 90))
fill(plot(showTrendCloud and periodTrendCloud != "New" and trendcloud != 0 and
close < trendcloud ? trendcloud : na, "", color.red , 1, plot.style_linebr,
editable=false), p0, color.new (color.red , 90))
fill(plot(hma, "", hma > hma[2] ? green : hma < hma[2] ? red : na, editable=false),
plot(hma[2], "", hma > hma[2] ? green : hma < hma[2] ? red : na, editable=false),
hma > hma[2] ? green : hma < hma[2] ? red : na)
// Alerts
f_crossed_over() =>
ret = false
for x = 0 to array.size(sr_up_level) > 0 ? array.size(sr_up_level) - 1 : na by
1
float mid = math.round_to_mintick((array.get(sr_up_level, x) +
array.get(sr_dn_level, x)) / 2)
if close[1] <= mid and close > mid
ret := true
ret
ret
f_crossed_under() =>
ret = false
for x = 0 to array.size(sr_up_level) > 0 ? array.size(sr_up_level) - 1 : na by
1
float mid = math.round_to_mintick((array.get(sr_up_level, x) +
array.get(sr_dn_level, x)) / 2)
if close[1] >= mid and close < mid
ret := true
ret
ret
f_sl_crossed() =>
ret = false
stop = enableTrailingSL ? trailingStop : stop_y
crossBull = low [1] >= stop[1] and low < stop[1] and ta.barssince(low [1] >=
stop[1] and low < stop[1])[1] >= countBull - 1
crossBear = high[1] <= stop[1] and high > stop[1] and ta.barssince(high[1] <=
stop[1] and high > stop[1])[1] >= countBear - 1
ret := trigger[1] ? crossBull : crossBear
f_tp_crossed(tp) =>
ret = false
profit = tp
crossBull = high[1] <= profit[1] and high > profit[1] and ta.barssince(high[1]
<= profit[1] and high > profit[1])[1] >= countBull - 1
crossBear = low [1] >= profit[1] and low < profit[1] and ta.barssince(low [1]
>= profit[1] and low < profit[1])[1] >= countBear - 1
ret := trigger[1] ? crossBull : crossBear
alert01 = (bull and close <= smartFilter) or (bear and close >= smartFilter)
alert02 = bull or bear
alert03 = (bull and close > smartFilter) or (bear and close < smartFilter)
alert04 = bull and close <= smartFilter
alert05 = f_crossed_over()
alert06 = bear and close >= smartFilter
alert07 = bull and close > smartFilter
alert08 = bear and close < smartFilter
alert09 = f_sl_crossed()
alert10 = f_crossed_under()
alert11 = f_tp_crossed(tp1_y)
alert12 = f_tp_crossed(tp2_y)
alert13 = f_tp_crossed(tp3_y)
alert14 = periodTrendCloud == "New" ? ta.crossunder(ema150, ema250) : (close <
trendcloud) and (close > trendcloud)[1]
alert15 = periodTrendCloud == "New" ? ta.crossover (ema150, ema250) : (close >
trendcloud) and (close < trendcloud)[1]
alerts(sym) =>
if alert01 or alert02 or alert03 or alert04 or alert05 or alert06 or alert07 or
alert08 or alert09 or alert10 or alert11 or alert12 or alert13 or alert14 or
alert15
alert("NEW ALERT", alert.freq_once_per_bar_close)
alerts(syminfo.tickerid)
alertcondition(alert01, "Any Signal Buy / sell", "Buy or Sell")
alertcondition(alert02, "Any signal Buy/Smart Buy or Sell/Smart Sell", "Buy/Smart
Buy or Sell/Smart Sell")
alertcondition(alert03, "Any signal Smart Buy / Smart Sell", "Smart Buy or Smart
Sell")
alertcondition(alert04, "Buy alert", "Buy")
alertcondition(alert05, "Resistance Broken", "Resistance Broken")
alertcondition(alert06, "Sell alert", "Sell")
alertcondition(alert07, "Smart Buy", "Smart Buy")
alertcondition(alert08, "Smart Sell", "Smart Sell")
alertcondition(alert09, "Stop loss", "Stop loss")
alertcondition(alert10, "Support Broken", "Support Broken")
alertcondition(alert11, "Target 1", "Target 1")
alertcondition(alert12, "Target 2", "Target 2")
alertcondition(alert13, "Target 3", "Target 3")
alertcondition(alert14, "Trend cloud Bearish Alert", "Trend cloud Bearish")
alertcondition(alert15, "Trend cloud Bullish Alert", "Trend cloud Bullish")

// Watermark

//text inputs

//symbol info
symInfoCheck = false
symInfo = syminfo.ticker + ' | ' + timeframe.period + (timeframe.isminutes ? 'M' :
na)
date = str.tostring(dayofmonth(time_close)) + '/' + str.tostring(month(time_close))
+ '/' + str.tostring(year(time_close))
//text positioning
textVPosition = 'middle'
textHPosition = 'center'
//symbol info positioning
symVPosition = 'top'
symHPosition = 'left'
//cell size
width = 0
height = 0
//title settings
c_title = color.new(color.orange, 0)
s_title = 'large'
a_title = 'center'
//subtitle settings
c_subtitle = color.new(color.orange, 50)
s_subtitle = 'normal'
a_subtitle = 'center'

//symbol settings
c_symInfo = color.new(color.orange, 50)
s_symInfo = 'normal'
a_symInfo = 'center'
c_bg = color.new(color.blue, 100)

//symbol info watermark creation

symWatermark = table.new(symVPosition + '_' + symHPosition, 5, 5)
if symInfoCheck == true
table.cell(symWatermark, 0, 1, symInfo, width, height, c_symInfo, a_symInfo,
text_size=s_symInfo, bgcolor=c_bg)
 table.cell(symWatermark, 0, 0, date, width, height, c_symInfo, a_symInfo,
text_size=s_symInfo, bgcolor=c_bg)

###################################################################################
###################################################################################
##################################################

//@version=2
study("Breakout",overlay=true)
res1 = input(title="Close Time Frame", type=resolution, defval="D")
cld=security(tickerid, res1, close[1])
opd=security(tickerid,res1, open[1])
tu=(cld +opd)/2
plot( tu, "Breakout",color=black ,style=line,linewidth=2,transp=0)

###################################################################################
###################################################################################
##################################################

//@version=5
indicator(title='ATR Trailing Stops with Kernel Functions', shorttitle='ATR +
Kernels', overlay=true, linktoseries=true, timeframe='')

import ayvaliktrading/EyopsTelegram/1 as LAF

import ayvaliktrading/JoinUsEyopsTelegram/1 as kernels

// ATR Inputs
atrLookback = input.int(defval=21, title='ATR Lookback Period')
atrMultiplier = input.float(defval=3, title='ATR Multiplier', step=0.1, minval=0.5,
maxval=4)
atrTrailMode = input.string(title='Trail Mode', defval='Trailing',
options=['Running', 'Trailing'])
atrFlipInput = input.string(title='Flip Trail on:', defval='Close',
options=['Close', 'Wick'])
atrBodyPercent = input.int(title='Percentage of Body to Include', defval=100,
minval=0, maxval=200, step=10, group="Advanced Settings")
atrWickPercent = input.int(title='Percentage of Wick to Include', defval=100,
minval=0, maxval=200, step=10)
atrSmoothingMode = input.string(title='ATR Smoothing Mode', defval='RMA',
options=['RMA', 'SMA', 'EMA', 'WMA'])

// Kernel Functions Inputs

showKernels = input.bool(defval=true, title="Show Kernel Functions")

// ATR Calculations
f_ma(_source, _length, _atrSmoothingMode) =>
if _atrSmoothingMode == 'RMA'
ta.rma(_source, _length)
else
if _atrSmoothingMode == 'SMA'
ta.sma(_source, _length)
else
if _atrSmoothingMode == 'EMA'
ta.ema(_source, _length)
else
ta.wma(_source, _length)

float atrBodyTrueRange = math.max(math.abs(open - close), math.abs(open -

close[1]), math.abs(close - close[1]))
float atrWickTrueRange = high - math.max(open, close) + math.min(open, close) - low
float atrPercentAdjustedTrueRange = atrBodyTrueRange * (atrBodyPercent / 100) +
atrWickTrueRange * (atrWickPercent / 100)

float atrValue = f_ma(atrPercentAdjustedTrueRange, atrLookback, atrSmoothingMode)

float atrMultiplied = atrValue * atrMultiplier

float atrLow = low - atrMultiplied

float atrHigh = high + atrMultiplied

// Trailing ATR Calculations

f_trail(_source, _trail, _direction) =>
_direction == 'down' and _source >= _trail ? _trail : _direction == 'up' and
_source <= _trail ? _trail : _source

var float trailAtrLong = atrLow

var float trailAtrShort = atrHigh

trailAtrLong := f_trail(atrLow, trailAtrLong, 'up')

trailAtrShort := f_trail(atrHigh, trailAtrShort, 'down')

// Flip function
f_flip(_flipInput, _longTrail, _shortTrail, _longReset, _shortReset) =>
var bool _flipLongNow = false
var bool _flipShortNow = false
var bool _isLong = true
var bool _isShort = true
float _flipLongSource = _flipInput == 'Close' ? close : _flipInput == 'Wick' ?
high : na
float _flipShortSource = _flipInput == 'Close' ? close : _flipInput == 'Wick' ?
low : na
_flipLongNow := _isShort[1] and _flipLongSource > _shortTrail ? true : false
_flipShortNow := _isLong[1] and _flipShortSource < _longTrail ? true : false
_flipLongNow := _flipShortNow and _flipLongNow and close > _longTrail ? true :
_flipShortNow and _flipLongNow and close <= _longTrail ? false : _flipLongNow
_flipShortNow := _flipLongNow and _flipShortNow and close < _shortTrail ?
true : _flipShortNow and _flipLongNow and close >= _shortTrail ? false :
_flipShortNow
_isLong := _flipLongNow ? true : _flipShortNow ? false : na(_isLong[1]) ?
true : _isLong[1]
_isShort := _flipShortNow ? true : _flipLongNow ? false : na(_isShort[1]) ?
true : _isShort[1]
 _longTrailOutput = _longTrail
_shortTrailOutput = _shortTrail
_longTrailOutput := _isLong and not _isLong[1] ? _longReset : _longTrailOutput
_shortTrailOutput := _isShort and not _isShort[1] ? _shortReset :
_shortTrailOutput
float _longTrailPlot = _isLong ? _longTrailOutput : _isLong and _isShort ?
_longTrailOutput : na
float _shortTrailPlot = _isShort ? _shortTrailOutput : _isLong and _isShort ?
_shortTrailOutput : na
[_longTrailOutput, _shortTrailOutput, _longTrailPlot, _shortTrailPlot]

[trailAtrLongTemp, trailAtrShortTemp, trailAtrLongPlot, trailAtrShortPlot] =

f_flip(atrFlipInput, trailAtrLong, trailAtrShort, atrLow, atrHigh)

trailAtrLong := trailAtrLongTemp
trailAtrShort := trailAtrShortTemp

// ATR Plots
plot(atrTrailMode == 'Running' ? atrLow : na, 'Running ATR Low',
color=color.new(color.white, 60), linewidth=1)
plot(atrTrailMode == 'Running' ? atrHigh : na, 'Running ATR High',
color=color.new(color.white, 60), linewidth=1)

plot(atrTrailMode == 'Trailing' ? trailAtrLongPlot : na, 'Trailing ATR Long Stop',

color=color.new(color.navy, 50), style=plot.style_linebr, linewidth=3)
plot(atrTrailMode == 'Trailing' ? trailAtrLongPlot : na, 'Trailing ATR Long Stop
Highlight', color=color.teal, style=plot.style_linebr, linewidth=1)

plot(atrTrailMode == 'Trailing' ? trailAtrShortPlot : na, 'Trailing ATR Short

Stop', color=color.new(color.maroon, 50), style=plot.style_linebr, linewidth=3)
plot(atrTrailMode == 'Trailing' ? trailAtrShortPlot : na, 'Trailing ATR Short Stop
Highlight', color=color.red, style=plot.style_linebr, linewidth=1)

// ... (previous code remains the same)

// Kernel Functions Calculations

yhat1 = kernels.rationalQuadratic(close, 8, 1, 25)
yhat2 = kernels.gaussian(close, 16, 25)
yhat3 = kernels.periodic(close, 8, 100, 25)
yhat4 = kernels.locallyPeriodic(close, 8, 24, 25)

// Kernel Functions Plots

plot(showKernels ? yhat1 : na, color = color.new(color.red, 50), title = "Rational
Quadratic Kernel", linewidth=1)
plot(showKernels ? yhat2 : na, color = color.new(color.yellow, 50), title =
"Gaussian Kernel", linewidth=1)
plot(showKernels ? yhat3 : na, color = color.new(color.green, 50), title =
"Periodic Kernel", linewidth=1)
plot(showKernels ? yhat4 : na, color = color.new(color.aqua, 50), title = "Locally
Periodic Kernel", linewidth=1)

// ... (rest of the code remains the same)

// Alerts
float atrFlipLongSource = atrFlipInput == 'Close' ? close : atrFlipInput ==
'Wick' ? high : na
float atrFlipShortSource = atrFlipInput == 'Close' ? close : atrFlipInput == 'Wick'
? low : na

bool alertCrossAtrShortStop = atrFlipLongSource > trailAtrShortPlot[1] and

atrFlipLongSource[1] <= trailAtrShortPlot[2] ? true : false
bool alertCrossAtrLongStop = atrFlipShortSource < trailAtrLongPlot[1] and
atrFlipShortSource[1] >= trailAtrLongPlot[2] ? true : false

bool alertCrossAtr = alertCrossAtrShortStop or alertCrossAtrLongStop

alertcondition(alertCrossAtr, title='Price crossed ATR', message='Price crossed
trailing ATR')