A Dissertation

On

A STUDY ON PRICE FORECASTING WITH TECHNICAL INDICATORS

FOR SELECTED INDIAN STOCKS.

Submitted in Partial Fulfillment of the Requirement for the

Award of Degree

Master of Commerce
(M. COM)
Batch 2024-25

Submitted by
Lokesh Chandra Pargai
Enrollment No.- ku20129653

Under the guidance of

Dr. Vijay Laxmi Sharma

MB Government Post Graduate College, Haldwani, Nainital

Uttarakhand
(Kumaun University)
 DECLARATION

I, Lokesh Chandra Pargai, Enrollment No. KU20129653, student of Master of Commerce

(M.Com), IV Semester, hereby declare that the research project titled:

“A Study on Price Forecasting with Technical Indicators for Selected Indian Stocks”

is an original work carried out by me under the valuable guidance and supervision of Dr. Vijay
Laxmi Sharma.

This project has been prepared exclusively for academic purposes and has not been submitted
earlier to any other University, Institution, or organization for the award of any degree, diploma,
or fellowship.

I further declare that all sources of information used in the preparation of this project have been
duly acknowledged.

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 ACKNOWLEDGEMENT

I would like to express my sincere gratitude to all those who supported and guided me
throughout the completion of this research project titled:

“A Study on Price Forecasting with Technical Indicators for Selected Indian Stocks.”

First and foremost, I would like to thank Dr. Vijay Laxmi Sharma, my project guide, for her
constant support, valuable guidance, and encouragement at every stage of the project. Her
expertise and constructive feedback were instrumental in shaping this work.

I also extend my heartfelt thanks to the faculty members of the Department of Commerce,
[M.B. Govt. Post Graduate College Haldwani], for creating a supportive academic
environment and providing access to necessary resources.

I am also thankful to my classmates, friends, and family members for their moral support and
understanding during the research period.

Finally, I acknowledge with gratitude all authors and researchers whose works and insights have
been referenced in this project.

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 ABSTRACT

Investment decisions in the stock market are generally influenced by two principal methods of
analysis: Fundamental Analysis and Technical Analysis. While Fundamental Analysis evaluates
a company's intrinsic value based on financial statements, earnings, and market conditions,
Technical Analysis focuses on the study of historical price patterns and trading volumes to
forecast future price movements. This research concentrates on the Technical Analysis of
selected Indian equity stocks, with the primary aim of examining and predicting stock price
trends using widely accepted technical indicators.

The study spans a six-month period from September 2023 to February 2024, during which the
daily closing prices of the selected stocks were closely monitored and analyzed. The analysis
incorporates three core technical tools: the Simple Moving Average (SMA), candlestick chart
patterns, and the Relative Strength Index (RSI). The SMA is used to smooth out short-term price
fluctuations and highlight longer-term trends, while candlestick charts are interpreted to
understand investor sentiment and identify potential reversal or continuation patterns. The RSI, a
momentum oscillator, helps measure the speed and change of price movements, providing
signals for overbought or oversold conditions.

This study is entirely based on secondary data collected from authentic sources such as company
financial reports, stock exchange websites, and financial news platforms. Through the
application of these tools, the research aims to identify price trends, analyze historical data
patterns, and make informed predictions about potential future movements in stock prices. The
primary objective is to offer a systematic approach to price forecasting that may aid investors,
analysts, and portfolio managers in making more informed and timely investment decisions.
Ultimately, this study contributes to a better understanding of the usefulness and reliability of
technical indicators in the Indian stock market context.

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 TABLE OF CONTENTS

CHAPTER 1 - INTRODUCTION
1.1 Stock………………………………………………………………………………
1.2 Stock Market……………………………………………………………………...
1.2.1 National Stock Exchange……………………………………………………….
1.2.2 Bombay Stock Exchange……………………………………………………….
1.3 Birth of the Stock Market………………………………………………………..
1.4 Current state of Indian Stock market……………………………………………..
1.5 Stock analysis through technical indicators………………………………………
1.6 Objectives of the study……………………………………………………………
1.7 Scope of the study………………………………………………………………..
1.8 Limitations of the study…………………………………………………………..

CHAPTER 2 - REVIEW OF LITERATURE

2.1 Review of Literature Related Research ………………………………………….

CHAPTER 3 - RESEARCH METHODOLOGY

3.1 Research Design…………………………………………………………………..
3.2 Time Period of the Study………………………………………………………….
3.3 Sources of data…………………………………………………………………….
3.4 Method of data collection………………………………………………… ……...
3.4.1 Secondary data…………………………………………………………………..
3.4.2 Statistical tools applied………………………………………………………….
3.5 Limitation of the study…………………………………………………….

CHAPTER 4 - DATA ANALYSIS AND INTERPRETATION

4.1 Types of analysis………………………………………………………………….
4.1.1 Fundamental analysis…………………………………………………………..
4.1.2 Technical analysis………………………………………………………………
4.1.2.1 Types of charts……………………………………………………………….

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4.2 Assumptions of Technical Analysis……………………………………………...
4.3 Technical indicators……………………………………………………………..
4.3.1 SIMPLE MOVING AVERAGE (SMA) ………………………………………
4.3.2 Relative Strength Index (RSI)............................................................................
4.4 Chart Analysis……………………………………………………………………
4.4.1 Tata Steel Ltd…………………………………………………………………..
4.4.2 STATE BANK OF INDIA …………………………………………………….
4.4.3 BHARTI AIRTEL LIMITED…………………………………………………..

CHAPTER 5 - CONCLUSION & FUTURE RESEARCH DIRECTION

REFERENCES

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 CHAPTER - 1

INTRODUCTION

“Stock market is a voting machine in the short run, and it is a weighing machine in the long run”
– Benjamin Graham

The stock market presents significant opportunities for investors, either through acquiring equity
to gain long-term benefits as shareholders or by trading stocks for short-term gains. However, the
stock market is inherently dynamic and volatile, often influenced by a wide range of factors,
including business launches and unforeseen national, global, or socio-economic events, which
can cause abrupt fluctuations in stock prices. Consequently, it is challenging to predict stock
price movements with certainty; investors and traders typically rely on forecasting major
developments based on historical and real-time data. Investment decisions are generally
informed by a company’s past and current performance, assessed through numerical indicators
and essential news content.

Stock trend prediction methods are commonly classified based on the number of data sources
into single-source and dual-source models. Single-source methods typically extract either
numerical or semantic information from available news and public sentiment, while dual-source
methods integrate both types of information. In recent years, the increasing complexity of
financial data—characterized by the "5Vs" of big data: Volume, Variety, Velocity, Veracity, and
Value—has exceeded the capacity of manual analysis, underscoring the necessity of automated
systems that leverage historical price data and stock trend indicators (STIs) for effective
forecasting.

A well-functioning stock market is considered essential for national economic development. It

serves two primary roles: enabling companies to raise capital for growth, and offering the public
avenues to earn returns through corporate profit-sharing. However, due to its nonlinear, complex,
and information-sensitive nature, forecasting stock market behavior remains a formidable
challenge. The exponential expansion of digital trading platforms has heightened investor

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interest in developing systematic approaches for predicting stock price movements and market
trends.

Stock market forecasting, aimed at optimizing buy-sell decisions for profitability, has garnered
considerable attention from both industry and academia. Historically, prediction systems were
constrained by reliance on traditional financial data. Today, advanced methodologies
incorporating diverse online information sources, such as financial news and public sentiment—
have emerged. As a result, contemporary forecasting models often combine fundamental analysis
(FA), technical analysis (TA), and hybrid approaches to support investment decisions. These
methods acknowledge the significant influence of trends, sentiments, and trading volumes on
stock price dynamics.

The two most common forms of market analysis are fundamental analysis and technical analysis.
Fundamental analysis (FA) is a method of assessing a security’s inherent value by analyzing
associated economic and financial variables. Fundamental analysts research everything that can
influence the security’s value, from macroeconomic variables such as the nature of the economy
and market developments to microeconomic aspects, like the efficacy of the company’s
management. The ultimate aim is to arrive at a number that can be compared to the market price
of a security to determine if it is underpriced or overpriced.

On the other end, Technical analysis is a technique or strategy for predicting the likely
future price action of a security based on market information. Technical analysis is not astrology
for predicting prices. Technical analysis is based on analyzing the current demand-supply of
commodities, stocks, indices, futures, or any tradable instrument. It involves putting stock
information like prices, volumes, and open interest on a chart and applying various patterns and
indicators to it in order to assess the future price movements. Technical analysts do not attempt
to measure a securities intrinsic value, but instead use charts and other tools to identify patterns
that can suggest future activity.

“Technical analysis is a security analysis technique that claims the ability to forecast the future
direction of prices through the study of past market data, primarily price and volume.

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1.1 STOCK

A stock, also known as equity, is a security that represents the ownership of a fraction of the
issuing corporation. Units of stock are called shares, which entitle the owner to a proportion of
the corporation’s assets and profits equal to how much of shares they own. Stocks are bought and
sold predominantly on stock exchanges and are the foundation of many individual investors’
portfolios. Stock trades have to conform to government regulations meant to protect investors
from fraudulent practices.

Corporations issue stock to raise funds to operate their businesses. The holder of stock, a
shareholder, may have a claim to part of the company’s assets and earnings. A shareholder is
considered an owner of the issuing company, determined by the number of shares an investor
owns relative to the number of outstanding shares.

1.2 STOCK MARKET

The stock exchange is often regarded as a barometer of the economy, reflecting the overall
economic health of a country. Stock markets play a pivotal role in the economic framework by
facilitating the trading of shares. All stock transactions—buying and selling of shares—are
conducted exclusively through the stock exchange. These transactions are governed by the
principles of supply and demand, and the stock exchange serves as the official platform for
recording and regulating such activities.

A stock market is a platform that enables the movement of capital through an efficient trading
and settlement system. Companies issue shares to you (investors) in the stock market to raise
capital for future growth. It could be in the form of equity shares or debt (debentures). These are
called securities that can be traded on a stock exchange. Investors buy such securities as a form
of financial investment.

A buyer gets shares, and the seller gets the money on the day of the trading settlement. The
stock market management's job is to ensure such settlements happen without fail.

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An efficient stock market is pivotal to a country's economic development as it enables the
movement of capital from those who have it to those who need it. India's stock market is the fifth
largest in the world by market value.

The evolution of the Indian stock market from a paper-based trading system to one of the most
efficient is a story for another day. If you want to buy or sell your shares, you have to approach a
broker who is a member of the National Stock Exchange or the Bombay Stock Exchange. You
open a Demat account first and then a trading account with a broker. The two stock exchanges
enable your seamless stock market trading experience through an efficiently managed trading
and settlement system.

1.2.1 NATIONAL STOCK EXCHANGE (NSE)

The National Stock Exchange of India (NSE) is one of the premier stock exchanges in the country
and a cornerstone of the Indian financial system. Established in 1992 and commencing operations
in 1994, the NSE revolutionized the Indian capital markets by introducing a fully automated,
electronic trading system that significantly improved transparency, efficiency, and investor
accessibility. Headquartered in Mumbai, the NSE was the first exchange in India to provide a
modern, demutualized structure where ownership, management, and trading rights are separated,
fostering greater accountability and governance.

The inception of the NSE was driven by the need for a transparent and efficient capital market
mechanism in India. Prior to its establishment, the Indian stock market was largely fragmented
and manually operated, which often led to inefficiencies and lack of investor trust. The NSE's
electronic limit order book (LOB) trading model eliminated the need for physical trading floors,
making trading faster, more reliable, and accessible nationwide through a robust communication
network. This model soon became the benchmark for modern trading systems in India.

The NSE’s key benchmark index, the Nifty 50, is composed of 50 large-cap companies from
diverse sectors of the Indian economy. It serves as an important barometer of market performance
and investor sentiment. The exchange provides a wide array of financial instruments, including

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equities, equity derivatives, currency derivatives, debt instruments, interest rate futures, and
exchange-traded funds (ETFs). Through its various segments, such as the capital market segment,
futures and options segment, and wholesale debt market, NSE facilitates comprehensive market
participation.

In addition to trading infrastructure, the NSE has made significant contributions to market
education and research. It operates the NSE Academy, which offers financial education programs,
certifications, and training to improve financial literacy among investors and professionals.
Furthermore, the NSE’s data analytics and research initiatives support informed investment
decisions and policy-making.

The NSE is regulated by the Securities and Exchange Board of India (SEBI) and adheres to a strict
regulatory and compliance framework. It employs robust risk management systems, real-time
surveillance mechanisms, and investor protection initiatives, which contribute to the credibility
and resilience of the Indian securities market.

Over the years, the NSE has consistently maintained its position as one of the top exchanges
globally in terms of trading volume, particularly in derivatives. It has also played a key role in
integrating India's financial markets with global systems, enhancing capital formation, and
attracting domestic and international investors.

The NSE has not only modernized the Indian stock trading environment but has also become a
symbol of trust, efficiency, and innovation. Its technological advancements and investor-focused
initiatives have significantly contributed to the deepening of financial markets in India, making it
a pivotal player in the country's economic growth.

1.2.2 BOMBAY STOCK EXCHANGE (BSE)

The Bombay Stock Exchange (BSE), established in 1875, is the oldest stock exchange in Asia and
one of the most significant financial institutions in India. With its headquarters in Mumbai, the
BSE has played a foundational role in the development of India’s capital markets, evolving from

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an open outcry system to one of the most advanced electronic trading platforms in the world. Over
the decades, it has supported economic expansion by enabling capital mobilization and providing
a structured platform for securities trading.

The BSE began as a group of stockbrokers trading under a banyan tree in Mumbai and gradually
developed into an organized institution. It was formally recognized under the Securities Contracts
(Regulation) Act of 1956. The BSE’s transition from manual to automated trading occurred in
1995 with the launch of the BOLT (BSE Online Trading) system, marking a significant milestone
in enhancing operational efficiency and transparency.

The flagship index of the BSE, the S&P BSE Sensex, is composed of 30 of the largest and most
actively traded stocks on the exchange. Introduced in 1986, the Sensex is widely regarded as the
barometer of the Indian stock market and reflects the overall performance of key sectors in the
Indian economy. The exchange supports trading in a wide range of instruments, including equities,
debt instruments, derivatives, mutual funds, and SME securities.

The BSE has established various platforms to facilitate inclusive growth and promote diverse
investment opportunities. The BSE SME Platform, launched in 2012, is dedicated to the listing
and trading of small and medium enterprises, thus enabling them to access capital markets for
funding and expansion. Additionally, the BSE MF platform has significantly simplified mutual
fund transactions, enhancing retail participation in asset management.

Beyond trading services, the BSE is also known for its contribution to investor education and
market research. Through its subsidiary, BSE Institute Ltd., the exchange provides a wide array of
educational and professional training programs in finance, investment, and capital markets. It also
collaborates with academic institutions and regulatory bodies to promote financial literacy and
awareness.

The BSE operates under the regulation of SEBI and adheres to stringent compliance and
governance norms. It employs sophisticated surveillance, risk management, and audit systems to
maintain market integrity and protect investor interests. These mechanisms are crucial in
maintaining investor confidence and ensuring the orderly functioning of the financial markets.

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In recent years, the BSE has also embraced sustainability and innovation. It has introduced the
BSE Greenex index to promote environmentally responsible investments and has actively explored
technologies such as blockchain to enhance operational efficiency and security.

To conclude, the Bombay Stock Exchange stands as a symbol of India’s financial heritage and
ongoing progress. It has not only contributed to the development of a robust capital market but has
also supported inclusive economic growth by extending its reach to a diverse spectrum of market
participants. As India continues to integrate with global markets, the BSE remains a vital
institution in shaping the future of the country’s financial and economic landscape.

1.3 BIRTH OF THE INDIAN STOCK MARKET

The roots of the Indian stock market can be traced back to the early 19th century when the country
was under British colonial rule. The growth of the stock market in India was closely linked to the
development of trade, commerce, and industry under British influence.

EARLY 19TH CENTURY: THE PRECURSOR TO STOCK TRADING

The beginning of organized stock trading in India can be traced to the 1830s in Mumbai, which
was rapidly emerging as a major commercial hub due to its strategic location and the presence of
the British East India Company. The need for capital to fund large-scale infrastructure projects,
such as the construction of railways and the establishment of textile mills, led to the introduction
of joint-stock companies. These companies needed to raise capital from the public, leading to the
early forms of stock trading.

1850S: FORMALIZATION OF THE STOCK MARKET

The first recorded instance of organized trading in shares can be dated to the 1850s. A group of
brokers began trading under a banyan tree in front of the Town Hall in Bombay. This informal
group of brokers would later become the foundation of India's first stock exchange.

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1875: ESTABLISHMENT OF THE BOMBAY STOCK EXCHANGE (BSE)

The year 1875 marked a significant milestone in the history of the Indian stock market with the
establishment of the Native Share and Stock Brokers' Association, which later became the Bombay
Stock Exchange. The BSE is the oldest stock exchange in Asia and was formed by a group of 22
brokers who would meet under the banyan tree to trade shares. The BSE played a crucial role in
the development of the Indian capital markets by providing a platform for the trading of securities
and formalizing the process of stock trading.

1956: FORMALIZATION OF STOCK TRADING

India passed the Securities Contracts Regulation Act in 1956, which formalized stock trading. This
act provided a legal framework for the regulation of stock exchanges, securities contracts, and the
protection of investors, further strengthening the foundation of the Indian stock market.

1964: INTRODUCTION OF MUTUAL FUNDS

The newly created Unit Trust of India (UTI) launched India’s first mutual fund scheme, the US
64, in 1964. The scheme became highly popular, raising Rs 6,400 crore by 1988, and established
UTI as a major player in the Indian financial market.

1977: THE RISE OF RELIANCE INDUSTRIES

Dhirubhai Ambani’s Reliance Industries, with interests in textiles and petrochemicals, was listed
on the stock exchange in 1977. The IPO garnered huge interest from retail investors, kickstarting
the ‘cult of equity’ in India, and marked the beginning of a new era for Indian entrepreneurship
and the stock market.

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1986: LAUNCH OF BSE SENSEX

On January 1, 1986, BSE introduced the SENSEX, a 30-share index that became the benchmark
for the Indian stock market. With a base year of 1978-79 and a base value of 100, the SENSEX
provided a barometer of market performance and became the most widely tracked index in India.

CHALLENGES AND TRANSFORMATIONS IN THE LATE 20TH

CENTURY

1988: ESTABLISHMENT OF SEBI

The late 1980s were marked by a lack of transparency and unreliable clearing and settlement
systems, which underscored the need for a financial market regulator. As a result, the Securities
and Exchange Board of India (SEBI) was established in 1988. However, it was not until 1992 that
SEBI was granted statutory power, enabling it to regulate the securities market effectively.

1992: FORMATION OF THE NATIONAL STOCK EXCHANGE (NSE)

In 1992, the National Stock Exchange of India Limited (NSE) was established. This period also
saw a sharp spike in interest in the stock market, driven by a bull market led by Harshad Mehta.
The NSE was created to bring greater transparency and efficiency to the market, and it introduced
a modern, fully automated screen-based electronic trading system in 1994, which revolutionized
trading in India.

1994: LAUNCH OF NIFTY 50 INDEX

On April 22, 1994, the NSE launched the Nifty 50 index, a benchmark Indian stock market index
representing the weighted average of 50 of the largest Indian companies listed on the NSE.
Initially, the Nifty 50 was calculated based on the full market capitalization methodology, but from
June 26, 2009, the computation shifted to a free-float methodology. The base period for the Nifty
50 index is November 3, 1995, with a base value set at 1,000.

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1.4 CURRENT STATE OF INDIAN STOCK MARKET

Today, the BSE’s market capitalization is likely to be around $3.8 trillion, and the market
capitalization of the NSE is estimated to be over $3.71 trillion.
The exchanges are still on parity in terms of share trading volumes. Nowadays, people can conduct
online trading sitting in their homes. Facilities such as zero brokerage Demat and live updates are
available.
Investor Education and Awareness (Ongoing)
Ongoing: Various initiatives and awareness campaigns have been launched to educate investors
about the stock market, risk management, and financial literacy.

The history of the Indian stock market has come a long way from its early days as a small, informal
trading platform to a sophisticated and well-regulated financial marketplace. It has played a critical
role in India's economic development, providing opportunities for investors while facing
challenges and setbacks that have led to improvements in regulatory and governance practices.

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 Chapter - 2

LITERATURE REVIEW

REVIEW OF LITERATURE RELATED RESEARCH

Technical analysis operates on the premise that all known information is already reflected in
stock prices and that historical price patterns tend to repeat over time (Murphy, 1999).

Technical indicators, which are mathematical formulas derived from historical price or volume
data, aim to identify potential trading opportunities by signaling trend direction, momentum,
volatility, and volume strength.

Achelis (2001) categorized technical indicators into four primary types: trend-following (e.g.,
Moving Averages), momentum (e.g., Relative Strength Index [RSI], MACD), volatility (e.g.,
Bollinger Bands), and volume-based (e.g., On-Balance Volume [OBV]). Pring (2002)
emphasized the psychological basis of technical analysis, noting that recurring patterns reflect
collective investor behavior and sentiment.

Although technical analysis lacks a strong theoretical foundation compared to fundamental

analysis, empirical studies have increasingly validated its utility in short-term price forecasting.

3. Global Empirical Evidence on Technical Indicators

The seminal study by Brock, Lakonishok, and LeBaron (1992) tested simple trading rules,
such as moving averages and trading ranges, on the Dow Jones Industrial Average. Their results
revealed statistically significant returns over a 90-year period, offering empirical support for the
efficacy of technical indicators.

Hudson, Dempsey, and Keasey (1996) conducted a similar study in the UK market and found
that technical indicators were more effective in the short term, particularly during trending
periods. However, their effectiveness diminished during periods of high volatility and market
noise.

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Neely, Weller, and Dittmar (2009) evaluated the profitability of technical trading rules across
multiple international markets. They concluded that in less efficient markets, such as those in
emerging economies, technical indicators tended to perform better due to more pronounced
behavioral patterns and less competition among traders.

4. Indian Context: Technical Analysis and Stock Forecasting

In India, technical analysis has gained ground as a viable tool for predicting short- to medium-
term stock movements. The market structure, with its mix of retail and institutional participants,
as well as its semi-strong efficiency, provides a conducive environment for chart-based
strategies.

Patel, Patel, and Thakkar (2015) investigated the effectiveness of MACD, RSI, and Stochastic
Oscillator for selected NSE stocks. Their study concluded that combining multiple indicators
yielded more accurate signals than using individual ones. Agarwal and Mittal (2014) supported
this conclusion by showing that Moving Averages and RSI worked well for Nifty index stocks,
especially in trending markets.

Karthikeyan and Shankar (2017) focused on banking sector stocks listed on the BSE. They
found that MACD was particularly useful in identifying buy/sell opportunities for large-cap
stocks with consistent volume, while Bollinger Bands helped in detecting breakouts in mid- and
small-cap stocks with greater price swings.

5. Use of Machine Learning with Technical Indicators

With the increasing availability of computational tools, recent studies have combined traditional
technical analysis with machine learning (ML) and artificial intelligence (AI) models to improve
forecasting accuracy.

Patel et al. (2015) compared four ML models—Artificial Neural Networks (ANN), Support
Vector Machines (SVM), Random Forest (RF), and Naive Bayes—for predicting the directional
movement of Indian stock prices. Their inputs included technical indicators like RSI, MACD,
and Bollinger Bands. Among these models, Random Forest showed superior predictive accuracy
due to its ability to handle non-linearity and noise in financial data.

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Naik and Reddy (2020) used Long Short-Term Memory (LSTM) neural networks trained on
technical indicators to predict stock prices of companies listed on the BSE. Their findings
suggested that LSTM outperformed conventional models like ARIMA and regression-based
methods, especially in volatile market conditions.

Sharma and Singh (2022) extended this approach by integrating both technical indicators and
fundamental variables into hybrid ML models. Their study demonstrated improved portfolio
performance and forecasting stability, even during macroeconomic uncertainty.

6. Stock-Specific and Sectoral Forecasting Studies

Some researchers have concentrated on sector-specific forecasting using technical indicators.

Ramesh and Elangovan (2018) studied IT sector stocks using 10-day and 50-day Moving
Averages and RSI. They found that short-term indicators performed better in volatile sectors like
technology, while long-term indicators were more effective in stable sectors such as utilities and
energy.

Verma and Sinha (2021) analyzed large-cap banking stocks using MACD and Bollinger Bands.
Their findings indicated that MACD crossover signals were particularly reliable during trending
market phases, while Bollinger Bands provided early warning signals during periods of price
consolidation.

These findings underline the necessity of tailoring technical analysis strategies based on industry
characteristics, volatility profiles, and liquidity levels.

7. Limitations of Technical Indicators and Existing Research Gaps

Despite promising results, technical indicators are not without limitations. One major criticism is
that most indicators are lagging—they react to price movements rather than predict them
proactively. This delay can result in missed opportunities or false signals, particularly during
trend reversals (Tsai & Hsiao, 2010).

Overfitting is another major issue, especially in machine learning models. Many studies,
including those by Patel et al. (2015) and Naik and Reddy (2020), have noted that predictive

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models often show excellent back-tested performance but struggle in live trading due to a lack of
generalization.

In the Indian context, there is limited research examining long-term forecasting using technical
indicators. Furthermore, few studies consider the combined impact of macroeconomic
variables—such as interest rates, inflation, and foreign institutional investment (FII) flows—on
stock prices in conjunction with technical indicators. Also, most Indian studies focus
predominantly on large-cap stocks, neglecting the behavior of small- and mid-cap equities,
which exhibit different volatility and liquidity dynamics.

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 Chapter 3

RESEARCH METHODOLOGY

3.1 STATEMENT OF THE PROBLEM

The Indian stock market has become increasingly volatile, driven by global economic conditions,
investor sentiment, and real-time information flow. This dynamic environment makes predicting
stock price movements a significant challenge for retail and institutional investors alike.
Traditional forecasting methods may fall short due to the complex and non-linear nature of
financial markets. Technical analysis, by contrast, offers a practical approach rooted in historical
price behavior, aiming to identify recurring patterns and momentum signals that can guide
investment decisions. This research seeks to address the problem of short-term stock price
prediction using selected technical indicators that are widely used and easily interpretable by
traders.

3.2 OBJECTIVES OF THE STUDY

The main objective of this study is to explore the role of technical indicators in forecasting the
short-term movements of Indian stocks. Specifically, the study aims:

1. To understand the theoretical framework and practical application of selected technical

indicators such as RSI, SMA, and candlestick patterns.

2. To track and analyze historical stock price data for selected companies over a six-month
period.

3. To generate forecasts based on technical indicator signals and compare them with actual
stock performance.

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 4. To assess the strengths and limitations of each technical tool used in the context of short-
term trading.

5. To evaluate the consistency and reliability of these indicators across different industries
and market conditions.

6. To assist investors in enhancing decision-making by integrating technical analysis into

their trading strategies.

3.3 SCOPE OF THE STUDY

1. The study covers a period of 4 months from September 2023 to February 2024.

2. The study helps to find out the future trends in the prices of selected Nifty 50 shares.

3.4 RESEARCH DESIGN

This study adopts a quantitative, analytical, and descriptive research design. It is quantitative
because it deals with numerical stock price data, analytical because it involves technical
computation and trend analysis, and descriptive as it interprets the significance of observed
patterns and indicators. The non-experimental nature of the study implies that there is no
manipulation of variables; instead, existing market data is used to draw conclusions about trends
and potential price directions.

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3.5 SAMPLE DESIGN

The sample has been selected using purposive sampling, focusing on high-volume,
fundamentally strong companies that belong to different sectors. The following companies listed
on the National Stock Exchange (NSE) are selected:

● Tata Steel Ltd (representing the metal and mining sector)

● State Bank of India (SBIN) (representing the banking and financial services sector)

● Bharti Airtel Ltd (representing the telecommunications sector)

These companies are not only major constituents of their respective sectors but also actively
traded stocks, ensuring the availability of consistent and reliable data for analysis. Their
inclusion also ensures that the study captures trends across different segments of the Indian
economy.

3.5. DATA COLLECTION

This research is entirely based on secondary data. The data collected includes daily open, high,
low, and close (OHLC) prices of the selected stocks over a six-month period, specifically from
September 2023 to February 2024. This period was chosen to capture recent market behavior
under regular and volatile conditions. The data was sourced from:

● National Stock Exchange of India (www.nseindia.com) – the official exchange

providing accurate and up-to-date stock prices.

● Fyers.in – a discount brokerage platform offering historical and real-time market data.

● TradingView.com – a global charting and analysis tool that provides advanced technical
indicators, drawing tools, and candlestick charting capabilities.

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These platforms were chosen for their reliability, accessibility, and professional-grade tools
suitable for academic and market research.

3.6. TOOLS AND TECHNIQUES USED

The analysis is centered on technical analysis, specifically using the following indicators and
charting methods:

● Relative Strength Index (RSI): A momentum oscillator that evaluates overbought or

oversold conditions. RSI readings above 70 typically indicate an overbought market,
while readings below 30 suggest oversold conditions.

● Simple Moving Average (SMA): A trend-following indicator that calculates the average
closing price over a specific period (e.g., 20-day or 50-day SMA), helping smooth out
price fluctuations and identify trend direction.

● Candlestick Chart Patterns: These visual tools provide insight into investor sentiment
and market psychology. Key patterns like doji, engulfing, hammer, and shooting star
were

analyzed for their potential to signal trend reversals or continuations.

The technical analysis was conducted using Microsoft Excel for calculations, data organization,
and graph plotting, and TradingView.com for candlestick charting and advanced visualization of
price movements and indicators.

7. LIMITATIONS OF THE STUDY

Despite the structured approach, the study has certain limitations:

● The research is limited to a short time frame (6 months), which may not fully capture
cyclical market trends or long-term behaviors.

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● Only three companies were selected, limiting the scope of generalizability across the
entire market.

● The study relies solely on technical indicators, excluding fundamental analysis and
macroeconomic variables that may significantly impact price movements.

● Unpredictable market events such as geopolitical tensions, earnings announcements, or

economic policy changes were not incorporated into the analysis.

● All tools used assume past patterns can predict future behavior, which may not always
hold true in volatile or irrational markets.

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 CHAPTER - 4

DATA ANALYSIS & INTERPRETATIONS

4.1 TYPES OF ANALYSIS-

4.1.1 FUNDAMENTAL ANALYSIS–

Fundamental analysis involves examining a company's financial statements and broader

economic indicators to uncover a security's intrinsic value. The result of such an analysis should
give you the investment's true worth based on a company's financial health, the market, and
economic conditions. Investors perform fundamental analysis to gauge whether or not to invest
in a company based on its current and projected worth.

An analyst works to develop a formula for estimating the approximate value of an organization’s
share price based on publicly available information (Segal, 2021b). This is just an estimation,
based on the analyst’s informed judgment of what the entity’s stock may be worth in comparison
to the current market price. The intrinsic value of a business is a term used by some analysts to
describe their estimated price.

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QUANTITATIVE AND QUALITATIVE FUNDAMENTAL ANALYSIS

The problem with describing the term ‘fundamentals’ is that it can refer to something that has to
do with a company's financial health. They obviously include sales and benefits, but they can
also include everything from a company’s market share to its management efficiency.
Quantitative and qualitative considerations can be used to classify the different fundamental
factors. Quantitative analysis is concerned with data that can be represented in numbers and
quantities (Seagal, 2021b).

Qualitative analysis relates to the nature or quality of something instead of its quantity.
Quantitative fundamentals deal with figures in this sense. They are a company’s observable
characteristics. As a result, financial statements are the most common source of quantitative data.
Revenue, benefit, assets, and other factors can all be precisely calculated. Qualitative
fundamentals are not more tangible. They could include a company’s main executives’
qualifications, market awareness, patents, and proprietary technologies. Intrinsically, neither
qualitative nor quantitative analysis is superior. Most experts use both of them.

QUALITATIVE FUNDAMENTALS TO CONSIDER

When it comes to a business, analysts often consider four main fundamentals. Rather than being
quantitative, they are all qualitative. They are as follows

1- The business model: What exactly does the company do? This isn’t quite as easy as it would
seem. If an organization is based on selling bread, is it realizing profits? Is it simply surviving on
royalties and franchise fees?

2- Competitive advantage: A company’s capability to compete successfully and hold its

position is critical to its long-term sustainability. Brand names can allow organizations to hold
rivals back while they are growing and profiting themselves. When a business is able to gain a
competitive edge, its shareholders will benefit for years.

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3- Management: Some people agree that the most significant factor for investing in a business is
management. This is true, even the strongest business models can crash if the managers of the
organization fail to operate them efficiently. Although it’s difficult for institutional investors to
meet and truly assess managers, you can look at the company’s website and review the top
executives’ and board members’ resumes. How did they do in previous positions? Is it true that
they’ve been selling off a lot of their stock recently?

4- Corporate governance: Corporate governance refers to the policies in place within an entity
that define management’s, directors’, and stakeholders’ interactions and obligations. These
policies are specified and decided in the company charter and its bylaws, along with corporate
laws and regulations. You want to work with a company that operates with integrity, fairness,
transparency, and efficiency. Take special note of whether management adheres to shareholder
rights and interests. Ensure that their shareholder interactions are open, direct, and
understandable. It’s likely that you won’t get it because they wouldn’t like you to know.

QUANTITATIVE FUNDAMENTALS TO CONSIDER

Financial statements are the means by which a business communicates details about its financial
results. Fundamental analysts make investment decisions based on quantitative data obtained
from financial statements. Income statements, balance sheets, and cash flow statements are the
three most relevant financial statements.

1- The balance sheet: A balance sheet is a document that shows a company’s assets, liabilities,
and equity at a given point in time (Segal, 2021b). The balance sheet gets its name from the fact
that a company’s financial structure balances out as follows:

Liabilities + Shareholders’ Equity = Assets

At any given moment, assets reflect the capital that the company owns or regulates. This
includes items such as cash, inventory, machinery, and buildings. The net value of the funding

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the business used to purchase those properties is represented on the other side of the equation.
Liabilities or equity provide the basis for financing. Liabilities reflect liability (which must be
repaid), while equity reflects the cumulative amount of money invested in the company by the
owners, including investment gains (profit earned in past years).

2- The income statement: The income statement examines a company’s success over a
particular time period, while the balance sheet uses a snapshot approach to assessing a
corporation. Technically, a balance sheet may be for a month or even a day, but public
corporations only report quarterly and annually. The income statement shows how much money
was made, how much was spent, and how much profit was made during that time period as a
result of the company’s activities.

3- Cash flow statements: The statement of cash flows is a chart that shows a company’s cash
inflows and outflows across a specified time period. Since it’s impossible for a company to
exploit its cash situation, the cash flow statement is crucial. Some accountants can do a lot of
things to manipulate profits, but it's almost impossible to fake cash in the bank.

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4.1.2 TECHNICAL ANALYSIS

Technical analysis is the use of historical market data to predict future price movements. Using
insights from market psychology, behavioral economics, and quantitative analysis, technical
analysts aim to use past performance to predict future market behavior. The two most common
forms of technical analysis are chart patterns and technical (statistical) indicators.

4.1.2.1 TYPES OF CHARTS

A chart is a graphical representation of a series of prices over a set time frame. The X-axis on a
chart plots the periods for which prices are plotted and the Y-axis plots the value or the price of
the share. The periods showing different price levels, as plotted, may range from a few hours to a
few years. Thus, charts or the timelines of charts can be hourly, daily, weekly, monthly, quarterly
and yearly, based on data in respective timeframes. Even minute charts are a possibility.

‘Short-term’ traders trade on the basis of daily charts as they are interested in the immediate
movement in a stock price, whereas ‘medium-term’ to ‘long-term’ traders are more dependent on
weekly/monthly charts as they want higher returns, for which they are prepared to wait for a
longer duration.

The three important types of charts, commonly used by chartists, are:

1. LINE CHART:

Line chart represents any variable over a set period of time.

• The roots of line charts can be traced back to the 18th century when they were first used by
mathematicians and scientists to illustrate various mathematical functions. However, the modern
concept of line charts gained prominence in the 19th century, notably with the works of
renowned statisticians like William Playfair.

The line is formed by connecting values of the represented variable over the time frame

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• Line charts do not provide visual information of the trading range for the individual points,
such as the high, low and opening prices, and closing price.

• They depict any variable like volume of a security, index number, price, etc.

Tata Consumer Products Ltd

2. BAR CHART:

This is a popular technique for showing the price variation and volume on a particular day.

• The chart is made up of a series of vertical lines that represent each data point.

• This vertical line represents the high and low for the trading period, along with the closing
price.

• The close and open are represented on the vertical line by a horizontal dash.

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 Tata Consumer Products Ltd

3. CANDLESTICK CHART:

Candlestick charts are based on the same market data as regular bar charts but present that data
in a different way. The components of candlestick charts are the opening price level, the closing
price level, the high price, and the low price of any data compression rate, be it weekly, daily or
intraday data.

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HISTORY OF THE JAPANESE CANDLESTICK

The origins of the Japanese candlestick charting technique can be traced back to 18th-century
Japan. This method was initially developed by Homma Munehisa, a prominent rice trader from
the city of Sakata. He is credited with using early forms of candlestick charts to analyze the price
movements of rice contracts, thereby enhancing trade efficiency and profitability. His methods
incorporated not only market price but also psychological elements of trading behavior, laying
the foundation for what would later become an integral part of technical analysis.

Despite their widespread use in Japan, candlestick charts remained largely unknown in the
Western world until the 1980s. It was during this period that Steve Nison, an American trader
and analyst, introduced the concept to a global audience. After extensive research and study,
Nison authored the seminal work "Japanese Candlestick Charting Techniques", which played a
crucial role in popularizing the method among Western traders and analysts. His efforts marked
the beginning of a global shift toward more visually intuitive forms of charting in technical
analysis.

Today, Japanese candlesticks are a fundamental tool in the toolkit of traders across the globe.
Many of the patterns and terminologies continue to retain their original Japanese names—such as
doji, harami, and engulfing—preserving their cultural and historical significance. Their enduring
popularity can be attributed to their ability to provide a clear and concise representation of
market sentiment and price action.

CANDLESTICK ANATOMY

Candlestick charts, or candle charts, are a useful trading tool as each candlestick can reveal four
points of data:

● Open: This is the price that an asset starts a trading session at and is represented by the
body’s bottom for the green (or blue) candles, and the body’s top for the red candles.
● Close: This is the price at which an asset finishes the trading session. It’s represented at
the top for green (or blue) candles, and bottom for red.

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 ● High: The highest price point in a trading session. If a candle stands for a day, this would
be called an intraday high.
● Low: And vice versa, this is the lowest price point in a trading session. For a daily
candle, this would be called an intraday low.

Using these data points, traders can interpret the price movements quickly and efficiently. They
can also search for repetitive candlestick patterns of specific candle shapes and forms, such as
different lengths of wicks, or bodies, or their proportion to each other.

4.2 ASSUMPTIONS OF TECHNICAL ANALYSIS-

Technical analysis is based on three important assumptions mentioned below:

1- CURRENT PRICE DISCOUNTS FOR EVERY INFORMATION-

The assumption that current price discounts everything is possibly the most important premise
of Technical Analysis. When applying Technical Analysis, the analyst must assume that the

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current price of an asset reflects every available piece of information that could possibly impact
the demand and supply of the asset. The only exception to this is acts of God, such as
earthquakes, tsunamis, etc., as such natural events cannot be anticipated beforehand.
Nonetheless, the impact of such events, once they occur, is quickly discounted by the market and
reflected in the price of an asset.

2- PRICE CHANGES ARE NOT RANDOM-

This is possibly the second most important assumption of Technical Analysis. When analyzing
an asset, the analyst must assume that the price of the asset trends and that price changes are not
random. The basic premise behind this assumption is that unless an analyst accepts that price
trends exist, there is no point in analyzing an asset from a technical standpoint. In fact, the
objective of Technical Analysis is to identify the prevailing trend of the asset and then to ride on
that trend until evidence emerges that the trend is possibly reversing or has already reversed.
There are three types of trends, each of which will be discussed later.

3- HISTORY TENDS TO REPEAT ITSELF-

The next major premise of Technical Analysis is that history tends to repeat itself. We will be
discussing a lot of price patterns later as we progress through the course. These price patterns
have worked very well in the past, and as such, it must be assumed that they will work well in
the future also. Recognizing a specific price pattern that is unfolding and knowing that such
patterns have worked well in the past enables an analyst to use such information to predict the
future movement of an asset. After all, while time keeps changing, the basic human psychology
relating to greed and fear remains the same, thereby causing patterns to keep repeating.

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4.3 TECHNICAL INDICATORS

Technical indicators play a crucial role in technical analysis by providing valuable insights into
various aspects of market trends, with one of the most significant being momentum. Momentum
refers to the rate at which the price of a security is changing over time, reflecting the strength or
weakness of a prevailing trend. The primary function of technical indicators is to help traders
understand this momentum more clearly, as it is often not immediately apparent from price
action alone.

In the early stages of a trend, whether an uptrend or downtrend, momentum tends to increase as
the price begins to move in the new direction. This initial acceleration is typically driven by a
shift in market sentiment and the initiation of a new trend. For example, in an uptrend, as buying
interest rises and more participants enter the market, the rate of price appreciation increases.
However, as the trend matures, the momentum begins to wane. The velocity of price change
slows down because the trend is becoming more established and fewer participants are willing to
enter at the current price levels.

This slowing momentum often becomes difficult to detect just by observing price action alone.
While a trader may notice that the price is still trending in a particular direction, they may not
immediately recognize that the rate of change is decreasing. This is where technical indicators
prove invaluable, as they offer a clearer picture of the underlying momentum. By using
indicators such as the Relative Strength Index (RSI), Moving Average Convergence Divergence
(MACD), or the Stochastic Oscillator, traders can gain a better understanding of whether the
current momentum is strong, whether it is beginning to slow down, or whether it might indicate
an impending trend reversal.

For example, as the momentum in an uptrend starts to diminish, technical indicators can help
highlight this deceleration, which might signal that a reversal is near. These tools allow traders to
quantify the changes in momentum and make more informed decisions about potential market
turning points. In essence, technical indicators provide a layer of analysis that helps to uncover
momentum shifts that are not always visible through the price chart alone. By answering critical
questions such as "Is the momentum still strong?" or "Is a trend reversal likely?" these indicators

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become essential in anticipating future price movements and managing trading strategies more
effectively.

4.3.1 SIMPLE MOVING AVERAGE (SMA)

Moving averages are a fundamental tool in technical analysis, primarily used to identify the
direction of a stock's trend and to determine its support and resistance levels. Essentially, a
moving average is a statistical calculation that smooths out price data by creating a constantly
updated average price over a specific period. As such, moving averages are considered trend-
following indicators, meaning they are designed to reflect past price movements, and therefore,
they are often categorized as lagging indicators. This characteristic makes them effective in
confirming trends but not in predicting them in real-time.

The period selected for calculating the moving average plays a crucial role in determining its
sensitivity and the extent to which it lags behind the actual price movements. The longer the
period, the greater the lag. For example, a 200-day moving average (200-day MA) incorporates
data from the past 200 days, thus making it a slower-moving indicator that responds more
gradually to changes in price. In contrast, a 20-day moving average (20-day MA) reacts more
quickly to recent price fluctuations because it is based on a shorter time frame, making it more
suitable for capturing short-term price movements. The disparity in response time between short-
term and long-term moving averages is important to understand for making decisions about
trading strategies.

Among the various moving averages, the 50-day and 200-day moving averages are the most
widely followed by both investors and traders due to their significance in identifying the
prevailing trend. These specific moving averages are considered key trading signals. For
instance, when the short-term 50-day MA crosses above the long-term 200-day MA, it is
typically interpreted as a golden cross, signaling a potential bullish market trend. Conversely,
when the 50-day MA falls below the 200-day MA, it is known as a death cross, which is seen as
an indicator of a bearish market.

The selection of the period for calculating a moving average depends largely on the investors or
trader’s objectives. Shorter moving averages, such as the 20-day or 50-day, are favored by those

Page | 37
engaged in short-term trading, as they provide quicker signals that align with the rapid pace of
short-term market fluctuations. These shorter-term moving averages are particularly useful for
active traders who need to respond quickly to price movements. On the other hand, longer
moving averages, such as the 200-day MA, are more suitable for long-term investors who are
interested in identifying the overall trend over an extended period. These longer-term averages
provide a broader view of the stock's price action and help in smoothing out daily price noise,
making them valuable tools for assessing the general market direction and determining key
levels of support and resistance.

Overall, moving averages serve as an essential tool for both short-term traders and long-term
investors, offering valuable insights into trend direction and market sentiment. By understanding
the relationship between the moving average period and its lag, traders can adjust their strategies
to better align with their objectives, ensuring they make informed decisions based on the trend's
direction and strength.

The Simple Moving Average (SMA) represents a fundamental method of smoothing data over a
defined period by calculating the arithmetic mean of a specified number of data points. It is
commonly used in financial analysis to assess trends by averaging a series of prices (such as
closing prices) over a set number of time intervals. Mathematically, the SMA is expressed as:

SMA = (A1 + A2 + ⋯ + An) / n

Where:

● A = the value (e.g., price) at each time period,

● n = the total number of time periods considered.
This technique mitigates short-term fluctuations, thereby providing a clearer view of the
underlying trend.

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WHAT DOES A MOVING AVERAGE INDICATE?

A moving average is a statistical measure used to represent the average variation in a data series
over a defined period. In financial analysis, it is widely utilized by technical analysts to observe
and interpret the price trends of specific securities. An upward movement in the moving average
generally indicates increasing price momentum or a bullish trend, whereas a downward
movement suggests a decline in value or bearish momentum.

Short term - 50-day moving average

Mid-term - 100-day moving average
Long term - 200-day moving average

Tata Motors Ltd.

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4.3.2 RELATIVE STRENGTH INDEX (RSI)

The Relative Strength Index (RSI), developed by Welles Wilder, is a momentum-based technical
indicator widely used to assess the speed and magnitude of recent price changes in a security. It
is designed to measure the velocity and variation of price movements over a specified time
period, providing insight into the strength of a trend. The primary purpose of the RSI is to
identify potential overbought or oversold conditions in financial markets, offering traders
valuable signals for market entry and exit.

The RSI operates on a scale from 0 to 100. In practical terms, technical analysts typically
interpret RSI values below 30 as indicating oversold conditions, suggesting that the security may
be undervalued and could be poised for a price rebound. Conversely, values above 70 are
interpreted as overbought conditions, implying that the security may be overvalued and a price
correction could be forthcoming.

These threshold values serve as critical signals for trading decisions:

● Buy Signal: A common buy signal occurs when the RSI crosses above the 30 level from
below, indicating a potential reversal from oversold conditions and the start of an upward
price movement.

● Sell Signal: A sell signal is typically generated when the RSI crosses below the 70 level
from above, suggesting that the security may be due for a price correction after reaching
overbought levels.

Page | 40
 Tata Motors Ltd.

The other means of using RSI is to look at divergences between price peaks/troughs and
indicator peaks/troughs. If the price makes a new higher peak, but the indicator does not make a
corresponding higher peak, this indicates there is less power driving the new price high. The
momentum behind the price rise is low. Since there is less power or support for the new higher
price, a reversal could be expected.

Similarly, if the price makes a new lower trough but the momentum indicator does not make a
corresponding lower trough, then it can be surmised that the downward movement is running out
of strength and a reversal upward could soon be expected.

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Here is the RSI calculation breakdown:

RSI FORMULA-
The Relative Strength Index (RSI) is calculated using this formula:

RSI = 100 − (100 / (1 + RS))

Where:
RS = Average Gain over n periods / Average Loss over n periods

n = 14 days is used as the standard period for calculation.

EXAMPLE OF RSI CALCULATION

Consider a stock with the following 14-day price changes (gains and losses in closing prices):

● Gains over 14 days: 1.2, 0.8, 1.0, 0.5, 1.4 → Sum = 4.9

● Losses over 14 days: -0.7, -0.6, -0.9, -0.3, -0.5 → Absolute sum = 3.0

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Calculations

1. Compute the average gain and average loss:

○ Average Gain = 4.9 / 14 ≈ 0.35
○ Average Loss = 3.0 / 14 ≈ 0.21

2. Compute the relative strength:

○ RS = 0.35 / 0.21 ≈ 1.67

3. Plug into the RSI formula:

○ RSI = 100 − (100 / (1 + 1.67))
○ RSI ≈ 100 − (100 / 2.67)
○ RSI ≈ 100 − 37.45
○ RSI ≈ 62.55

Result- The RSI is approximately 62.55, indicating a moderately strong trend but not yet
overbought.

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4.4 CHART ANALYSIS

4.4.1 TATA STEEL LTD

Tata Steel Ltd, a flagship company of the Tata Group, is one of the largest steel manufacturers in
the world. Founded in 1907, the company has played a significant role in shaping the steel
industry in India and globally. Headquartered in Mumbai, India, Tata Steel operates in more than
26 countries and has a presence across key markets in Europe, Asia, and Africa. The company
produces a wide range of steel products, including flat and long products, with applications in
industries such as automotive, construction, engineering, and energy.

Tata Steel is known for its commitment to quality, sustainability, and innovation. The company
has been at the forefront of adopting environmentally responsible practices, including energy-
efficient production processes and the recycling of materials. With a production capacity of over
30 million tons annually, Tata Steel is recognized as one of the top steel producers worldwide.
The company’s core philosophy of excellence, integrity, and leadership in the steel sector has
earned it numerous awards and a solid reputation in the global market.

Through strategic expansions, including the acquisition of Corus (now Tata Steel Europe) in
2007, Tata Steel has strengthened its position in international markets. The company continues to
focus on enhancing its product offerings, improving operational efficiency, and exploring new
growth opportunities, making it a prominent player in the global steel industry.

PRODUCT PORTFOLIO

The company’s product mix includes flat products such as hot rolled coils, cold rolled coils and
galvanized steel, and long products such as wire rods, rebar, ferro alloys, tubes, bearings and
wires. The product segments cater to agriculture, automotive, construction, consumer goods,
energy and power, engineering and material handling etc.

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At Tata Steel Ltd. - February 2024 Analysis

OBSERVATIONS:

● Monthly RSI (February 1, 2024): 63.30

● Weekly Chart: Above 60

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 ● Analysis: Both monthly and weekly RSI indicators suggested a bullish trend in February
2024.
● Result: Tata Steel Ltd. showed a bullish trend on the daily chart during February 2024.

The convergence of the monthly and weekly RSI values above key thresholds (60 and 63.30) in
February 2024 indicated strong positive momentum for Tata Steel Ltd. This alignment
significantly increased the probability of a corresponding bullish trend on the daily chart, which
ultimately materialized.

Bullish signals from monthly and weekly charts effectively predicted the bullish daily chart
performance of Tata Steel Ltd. in February 2024.

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4.4.2 STATE BANK OF INDIA

The State Bank of India (SBI) is the largest public-sector bank in India and one of the most
prominent financial institutions in the country. Established in 1955, SBI traces its origins to the
Bank of Calcutta, founded in 1806, which later merged with other entities to form the current
institution. With a rich history spanning over two centuries, SBI has played a pivotal role in
shaping India’s banking and financial landscape.

Headquartered in Mumbai, SBI offers a wide range of services, including retail banking,
corporate banking, investment banking, and wealth management, both domestically and
internationally. It has a robust network of over 22,000 branches across India and operates in
several countries, providing banking solutions to millions of customers.

As a state-owned entity, SBI holds a significant role in the Indian economy, with a strong
emphasis on financial inclusion, rural development, and fostering economic growth. It is also
known for its efforts in digitizing banking services and improving accessibility for its customers.
Additionally, SBI is listed on major Indian stock exchanges and is one of the most influential
banks in terms of market capitalization.

Through its wide array of services and its extensive customer base, the State Bank of India
continues to maintain a central position in India's financial sector, contributing to the nation’s
economic progress and stability.

MARKET SHARE-

As of FY24, the bank has a deposit market share of about 22.55% and a net advance share of
19.06% in India.

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 Monthly, weekly and daily chart of
Sbi

Based on the RSI analysis of the State Bank of India (SBI) in January 2024:

● Monthly RSI (January 2024): 63.30

● Weekly RSI (Last week of January 2024): 62.41

Both the monthly and weekly RSI values being above 60 indicated a bullish trend. Consequently,
there was a higher probability of a bullish trend on the daily chart for SBI in January 2024,
which aligned with the observed upward price movement.

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4.4.3 BHARTI AIRTEL LIMITED

Bharti Airtel Limited is one of the largest telecommunications companies in India and a global
player in the telecommunications industry. Founded in 1995, it operates in over 18 countries
across South Asia and Africa, providing a wide range of services, including mobile voice and
data, broadband, digital television, and enterprise solutions. Bharti Airtel is known for its
extensive network infrastructure, which has made it a dominant force in the Indian telecom
market, with a significant market share in both mobile services and broadband.

The company is recognized for its strong brand presence, innovative services, and strategic
partnerships. It has played a key role in driving digital inclusion in India, offering affordable
mobile and internet services to a broad customer base. Bharti Airtel has also been involved in
various technological advancements, including the rollout of 4G and 5G networks, and has made
significant strides in its digital transformation through initiatives like Airtel Payments Bank and
Airtel Xstream.

As a publicly listed company on the Bombay Stock Exchange (BSE) and National Stock
Exchange (NSE), Bharti Airtel remains a prominent player in the Indian stock market, attracting
investors with its growth potential and strategic positioning in the evolving global
telecommunications landscape.

Monthly , weekly and daily chart of

Bharti Airtel Limited

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Based on the RSI analysis of Bharti Airtel ltd in SEPTEMBER 2023:

● Monthly RSI (SEP 2023): 68.72

● Weekly RSI (4 SEP 2023): 63.54

Both the monthly and weekly RSI values being above 60 indicated a bullish trend. Consequently,
there was a higher probability of a bullish trend on the daily chart for AIRTEL in SEP 2023,
which aligned with the observed upward price movement.

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 CHAPTER - 5

CONCLUSION AND FUTURE RESEARCH DIRECTION

CONCLUSION-

The present study aimed to explore the use of technical indicators—Relative Strength Index
(RSI), Simple Moving Average (SMA), and candlestick chart patterns—for forecasting stock
prices of selected Indian companies. The findings highlight that technical analysis serves as a
crucial tool in understanding market trends and predicting future price movements. By applying
these indicators, investors can gain valuable insights into potential entry and exit points,
enhancing their decision-making process, especially in the short to medium term.

Technical analysis, when used correctly, offers a strategic advantage in identifying price trends
and momentum. The study showed that patterns in stock price movements can be effectively
analyzed using RSI for momentum, SMA for trend direction, and candlestick charts for market
sentiment. However, technical analysis should not be used in isolation. A sound investment
decision often requires the integration of both technical and fundamental analysis to obtain a
holistic view of the market and the underlying performance of the companies in question.

As famously quoted, “There is only one side to the stock market and it is not the bull side or the
bear side but the right side.” Technical analysis helps investors stay on the "right side" by
offering a structured approach to trading decisions.

However, it is important to acknowledge the limitations of technical analysis. It is inherently

based on historical data and market psychology, which may not always predict future movements
accurately, especially in the presence of sudden news events or economic changes. Additionally,
over-reliance on indicators without contextual judgment can lead to misleading conclusions.

FUTURE RESEARCH DIRECTIONS-

Future research can explore the integration of additional technical indicators such as MACD,
Bollinger Bands, and Fibonacci retracements to enhance prediction accuracy. Moreover,

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combining machine learning algorithms with traditional technical tools could offer more robust
forecasting models. Expanding the scope of the study across different sectors and using a longer
time frame could also provide deeper insights. Lastly, a comparative analysis between technical
and fundamental forecasting methods might help validate the effectiveness of hybrid approaches
in real-time investment scenarios.

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 LIST OF ABBREVIATIONS

TA Technical analysis

FA Fundamental analysis

BSE Bombay Stock Exchange

NSE National Stock Exchange

RSI Relative Strength Index

SMA Simple Moving Average

MA Moving Average

MACD Moving Average Convergence Divergence

SBI State Bank of India

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REFERENCES

1- Stock Indices Price Prediction Based on Technical Indicators Using Deep Learning
Researcher: Agrawal, Manish

2-Stock Market Investing for Beginners: Everything You Need to Know to Start Trading and
Achieve Financial Freedom: 1 (Trading Masterclass) by Mark Johnson

3- www.nseindia.com Official website of NSE India.

4- www.fyers.in

5- www.investopedia.com

6- TECHNICAL ANALYSIS IN SELECT STOCKS OF INDIAN COMPANIES

C. Boobalan Assistant Professor, PG and Research Dept. of Commerce, SVM College

7- M.S HEMALATHA- A study on Technical Analysis of Canara Bank Equity Shares – Indian
Journal of Research- ISSN 2250-1991. Volume 2. Issue-4. April -2013.

8. C. BOOBALAN – Technical Analysis in Selected Stocks of Indian Companies – International

Journal of Business and Administration Research Review, Vol.2, Issue.4, Jan – March 2014,
ISSN No. 2347-856X.

9- www.google.com

10- investment decision in merged companies and forecasting price movements using technical
indicators with selected equity stock in Indian stock market ,Sriyank Levi, Dr. R. V Naveenan,
Sarah Merlyn

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11- S. D. Vasantha, “Stock Price movement through Technical Analysis: Empirical evidence
from the IT sector,” Indian J. Financ., vol. 6, no. 10, pp. 4–17, 2012.

12- A. Ţă, “The relative strength index revisited,” African J. Bus. Manag., vol. 5, no. 14, pp.
5855–5862, 2011.

13- Cheol-Ho Park, Scott H. Irwin (2004). “The Profitability of Technical Analysis: Project
Research Report No. 2004-04.

14- IJMBS Vol. 1, Issue 1, March 2011 Technical Analysis on Selected Stocks of Energy
Sector R.Chitra.

15- International Journal of Advanced Research (2013), Volume 1, Issue 4, 430-446 : Technical
Analysis for Selected Companies of Indian IT Sector - Hemal Pandya.

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