plage

by Singh Rohit

Submission date: 07-Nov-2024 02:23PM (UTC+0600)

Submission ID: 2511355441
File name: plage.docx
(517.21K) Word count: 38738
Character count: 225643
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 CHAPTER IV

DATA ANALYSIS AND INTERPRETATION

GRAPH No. 4.1

GRAPH SHOWING CLOSING PRICE OF CRUDE OIL

 100

22
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107

209

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 -
12.060,0u·e well below the critical values, again leading to the rejection of the null hypo•. This
consistent rejection of the null hypothesis across all tests suggests that the first-differenced series of crude oil
prices is stationary. This implies that after differencing, the crude oil prices no longer follow a random walk or
stochastic trend, making the series suitable for further time series modeling, such as ARI:MA or VAR analysis,
where stationarity is a crucial requirement.

GRAPH No.43

GRAPH SHOWING SENSEX COLlSING PRICE FOR THE STUDY PERIOD

Sensex

90,000

80,000

70,000

60,000

50,000

40,000

30,000

20,000

10,000

0
25 50 75 100 125 150 175 200 225 250 275

GRAPH No. 4.4

GRAPH SHOWING DESCRIPTIVE STATISTICS (SENSEX)

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90

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115

38

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122 99

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162 82

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 -
TABLE SHOWING VECTOR ERROR CORRECTION ESTIMATES
TABLE No.4.9

Coint CointE 1
SENSEX(-1) 1.00000
CO_BRENT(-1) -344.117
-172.673
(-1.99289]
C -1481.11
Error Correction: D(SENSEX) D(CO_BRENT)
CointEql 0.016472 l.54E-05
-0.004830 -1.90E-05
[ 3.40910] [ 0.79478]
D(SENSEX(-1)) -0.039210 0.000440
-0.060060 -0.000240
(-0.65288] [ 1.82747]
D(SENSEX(-2)) -0.115370 -3.78E-05
-0.060500 -0.000240
(-1.90690] [-0.15608]
D(CO_BRENT(-1)) 4.622210 0.339799
-14.92900 -0.059810
[ 0.30961l [ 5.68139]
D(CO_BRENT(-2)) 17.96493 -0.046820
-14.72520 -0.058990
[ 1.22001l [-0.79371]
C 299.0856 0.019647
-84.10560 -0.336950

m
R-sguared
[ 3.55607]
0.045892
[ 0.05831]
0.130054
Adj. R-squared 0.029270 0.114898
Sum sq. resids 554E+08 8893.952
S.E. equation 1389.536 5.566810
F-statistic 2.760903 8.581078
Log likelihood -2533.080 -915.7470
Akaike AJC 17.33159 6.291787
Schwarz SC 17.40696 6.367149
Mean dependent 264.2428 0.182229
S.D. de ndent 1410.330 5.917111
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understanding, and examination of VAR residuals is essential for developing robust forecasts and drawing
meaningful conclusions from time series analyses.

GRAPH No. 4.5

GRAPH SHOWING CORRELOGRAM-Q STATISTICS

8,000

4,000

-4,000

-8,000
2,500
f-----------tl-o--..,...._-, ,_ .. ;l\-ri---t--Trr-tl--1-,-tt1rtt1·ttfhrtttt-.,,-tt-tr -12,000

-2,500

-5,000
-7,500

-10,000 -+- ,,-/

255075100 1 25 150 175 200 225 250 275

I -- Residual -- Actual -- Fttted

Correlogram - Q Statistics
 CORRELOGRAM SQUARED RESIDUALS

TABLE No. 4.12

TABLE SHOWING CORRELOGRAM SQUARED RESIDUALS (ARCH OR GARCH MODEL)

Autocorrelation Partial Correlation AC PAC a-stat Prob'

0.005 0.005 0.0710 0.790

2 -0.004 -0.004 0.1255 0.939
3 -0.004 -0.004 0.1660 0.983
4 -0.004 -0.004 0.2058 0.995
5 -0.004 -0.004 0.2596 0.998
6 -0.004 -0.004 0.3135 0.999
7 -0.005 -0.005 0.3919 1.000
8 -0.002 -0.002 0.4027 1.000
9 -0.003 -0.003 0.4339 1.000
10 -0.001 -0.002 0.4399 1.000
11 -0.001 -0.001 0.4443 1.000
12 -0.006 -0.006 0.5313 1.000
13 -0.006 -0.006 0.6158 1.000
14 -0.004 -0.004 0.6591 1.000
15 0.006 0.006 0.7733 1.000
16 -0.003 -0.003 0.7978 1.000
17 -0.002 -0.002 0.8119 1.000
18 -0.000 -0.001 0.8124 1.000
19 -0.003 -0.003 0.8337 1.000
20 0.023 0.023 2.3233 1.000
21 -0.002 -0.002 2.3298 1.000
22 -0.003 -0.003 2.3631 1.000
23 -0.004 -0.004 2.4017 1.000
24 -0.005 -0.005 2.4738 1.000
25 -0.004 -0.004 2.5193 1.000
26 -0.005 -0.005 2.5847 1.000
27 -0.002 -0.002 2.5983 1.000
28 -0.004 -0.004 2.6450 1.000
29 -0.005 -0.005 2.7148 1.000
30 -0.003 -0.003 2.7402 1.000
31 -0.002 -0.003 2.7566 1.000
32 -0.004 -0.004 2.8042 1.000
33 -0.004 -0.004 2.8396 1.000
34 -0.005 -0.006 2.9234 1.000
35 -0.003 -0.003 2.9413 1.000
36 0.005 0.005 3.0088 1.000

m
Analysis: When the correlogram of squared residuals from an ARCH or GAR CH model s;Jws p-values greater
than 0.05, it indicates that there is no significant autocorrelation in the squared residuals. This suggests that the
model has successfully captured the volatility clustering in thedata. ln other words, the ARCH or CH
effects are well accounted for, and there is no remaining conditional heteroskedasticity. A lack .significant
autocorrelation in the squared residuals implies that the residuals behave like white noise, affi.rming that the model
is appropriate for the data and that no further volatility modeling is required. This outcome is a sign of a well
fitted model.

GRAPH No. 4.6

GRAPH SHOWING JARQUE-BERA TEST RESULT

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investments, especially in sectors heavily reliant on energy inputs. The IRFs indicate that both crude oil prices
and the Nifty Sensex are subject to dynamic interdependencies, with shocks having significant and lasting
impacts on thei.r respective movements. Investors and analysts should pay close attention to these relationships,
as they can provide valuable insights for forecasting and decision-making.

TABLE No. 4.18

TABLE SHOWING VARIANCE DECOMPOSITION OF NSEN AND DBRENT

mVariance Decom sition of NSEN
Period S.E. NSEN DBRENT
1414.929 100.0000 0 .000000
2 1415.025 99.99897 0.001028
3 1419.793 99.70066 0.299339
4 1420.084 99.66636 0.333642
5 1420.121 99.66637 0.333630
6 1420.121 99.66632 0.333679
7 1420.122 99.66632 0.333681
8 1420.122 99.66632 0.333682
9 1420.122 99.66632 0.333682
IO m 1420.122 99.66632
Variance Decomposition of DBRENT
0.333682

Period S.E. NSEN DBRENT

1 5.563250 2.078140 97.92186
2 5.940868 4.422128 95.57787
3 5.958259 4.643068 95.35693
4 5.958568 4.642809 95.35719
5 5.958593 4.642903 95.35710
6 5.958594 4.642916 95.35708
7 5.958594 4.642918 95.35708
8 5.958594 4.642918 95.35708
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 EJ
Historical Docompcsition usir,;J Cholesky (no d.f. adjustmoot)Weights
iooofNSEN
DecoflllOSitiooof DBRENT
6.000

4,000

2.000

-2,000

-4,000

-6,000-

-8,000

25 :50 75 100 125. 150 175, :200 2:25 250 275,

25 50 75 100 125 150 175 200 225 250 275
□Tolil,fodia,lc
-NSEI, LJTotil:;b::hasi:::
-DBREt,T _N5El,
-OBIIENT

GRAPH No. 4.11

GRAPH SHOWING VAR RESLDUALS (SENSEX)

VAR (Vector Autoregression) residuals are a crucial asP<'j of the VAR modelling framework, serving as
indicators of model fit and validity. These residuals represent the differences between the observed values and
the values predicted by the VAR model, encapsulating the portion of the data not explained by the included
variables. Analysing VAR residuals helps assess the model's adequacy, particularly concerning assumptions of
linearity, normality, and independence. Key characteristics of residuals include their statistical properties;
ideally, they
should exhibit no autOCOITelation, homoscedailii,city (constant variance), and a normal distribution. The presence
EU
of autocorrelation in residuals, indicated by tests such as the Breusch-Godfrey LM test, suggests that the model
may be mis specified, necessitating adjustments such as including lagged variables or altering model
specifications. Homoscedasticity is vital for ensuring that variance remains constant over time; tests like the
ARCH (Autoref,rressive Conditional Heteroskedasticity) test help identify any heteroskedasticity in residuals,
which can bias standard error estimates and lead to inefficient parameter estimates. Additionally, normality of
the residuals is often assessed through f,rraphical analysis, such as Q-Q plots, and formal statistical tests like the
Jarque Bera test. Non-normal residuals can indicate om. variables or incorrect functional forms in the model.
The residual analysis also plays a critical role in the evaluation of impulse response functions and variance
decomposition, as reliable estimates depend on correctly specified VAR models. Overall, thorough residual
analysis is essential for ensuring that the VAR model provides a robust and reliable representation of the
underlying time series relationships, ultimately leading to valid inferences and policy recommendations.
 VAR Residuals
NSEN Residuals
5,000

2,500

-2,500

-5,000

-7,500

-10,000 -'-r- r----,---0

50 100 150 200 250

DBRENT Residuals

50 100 150 200 250

GRAPH No. 4.12

 GRAPH SHOWING CORRELOGRAM FOR NSEN AND DBRENT
a
Autocorrelationsw hAwroximale2 Sid.Err.Bourds
Cor(NSEN,NSEN(-i)) Cor(NSEN,DBRENT(-i))

2 3 4 5 6 7 8 9 10 11 12 2 3 4 5 6 7 8 9 10 11 12

Cor(DBRENT,NSEN(•i)) Cor(DBRENT,DBRENT(-i))

-.1 -.1

2 3 4 5 6 7 8 9 10 11 12 2 3 4 5 6 7 8 9 10 11 12

Analysis: The correlogram of the residuals shows that none of the spikes violate the two standard error lines,
which indicates that the residuals do not exhibit any statistically significant autOCOITelation at any lag. This is a
key result, as it suggests that the model used to generate the residuals has successfully captured the underlying
structure or the data. In other words, the model has accounted for the time-dependent patterns, and what remains
(the residuals) behaves like white noise. When residuals show no significant autOCOITelation, it implies that
there is no systematic pattern left unexplained by the model. This is important because significant autocorrelation
in residuals would indicate model misspecification, meaning the model may have failed to account for certain
aspects of the data, leading to biased or inefficient forecasts. The lack or autocorrelation also suggests that the
residuals are stationary, with constant mean and v,u·iance over time, and do not exhibit seasonality or other
cyclical behaviour. Essentially, the residuals appear to be random, validating the appropriateness of the model.
The correlogram analysis of the residuals confirms that the model fits the data well, as there are no patterns or
dependencies left unexplained. This result supports the adequacy of the model for forecasting and analysis
purposes.

TABLE No. 4.19

m
TABLE SHOWING VAR RESIDUAL PORTMANTEA TESTS FOR AUTOCORRELATIONS

Lags Q-Stat 'Prob.* Adj Q-Stat 'Prob.* df

I 0.031689 0.031797
2 0.102606 0.103202
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 THE CORRELOGRAM OF SQUARED RESIDUALS

TABLE No. 4.33

TABLESUOWlNG VAR RESIDUALS( lFfY)

Autocorrelation Partial Correlation AC PAC a-stat Prob•

1 0.020 0.020 1.1615 0.281

2 -0.011 -0.012 1.5046 0.471
3 -0 004 -0 004 1.5540 0670
4 -0.021 -0.021 2.8109 0.590
5 0.018 0.019 3.6864 0.595
6 0.005 0.004 3.7689 0.708
7 0.041 0.041 8.3743 0.301
8 0.009 0.007 8.5941 0.378
9 -0.011 -0.009 8.9195 0.445
10 0.003 0.004 8.9482 0.537
11 -0.017 -0.016 9.7744 0.551
12 0.007 0.006 9.9065 0.624
13 -0.003 -0.004 9.9266 0.700
14 -0.013 -0.014 10.375 0.734
15 -0.003 -0.004 10.403 0.794
16 -0.015 -0.014 11.043 0.807
17 0.014 0.015 11.624 0.822
18 -0.012 -0.013 12.060 0.844
19 -0.015 -0.014 12.711 0.853
20 0.005 0.005 12.783 0.886
21 -0.022 -0.020 14.128 0.864
22 0.009 0.009 14.355 0.888
23 -0.003 -0.003 14.378 0.916
24 -0.003 -0.003 14.396 0.937
25 0.003 0.002 14.423 0.954
26 -0.001 0.002 14.427 0.967
27 -0.032 -0.033 17.320 0.923
28 -0.014 -0.011 17.856 0.930
29 0.030 0.029 20.397 0.880
30 -0.006 -0.009 20.487 0.903
31 0.073 0.074 35.394 0.268
32 0.009 0.005 35.633 0.301
33 0.034 0.038 38.867 0.222
34 0.018 0.018 39.828 0.227
35 -0.001 0.003 39.831 0.264
36 -0.025 -0.029 41.542 0.242

• Probabilities mav not be valid for this eaualion soecification.

Analysis: When the correlogram of squared residuals from an ARCH or GAR CH model 1Jws p-values m
greater than 0.05, it indicates that there is no significant autocorrelation in the squared residuals. This suggests
that the model has successfully captured the volatility clustering in thedata. ln other words, the ARCH or
CH effects are well accounted for, and there is no remaining conditional heteroskedasticity. A lack
19significant autocorrelation in the squared residuals implies that the residuals behave like white noise, affirming
that the model is appropriate for the data and that no further volatility modeling is required. This outcome is a
sign of a well
fitted model.
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 GRAPH No. 4.20

GRAPH SHOWING CORRELOGRAM FOR DNI.FfY AND DCRUDE

Autocorrelations with Approximate 2 Std.Err. Bounds

Cor(DNIFTY,DNIFTY(-i)) Cor(DNIFTY,DCRUDE(- )
2 2

,1

0 .0

• .1

2 -2
2 3 4 5 6 7 8 9 10 11 12 2 3 4 5 6 7 8 9 10 11 12

Cor(DCRUDE,DNIFTY(-i)) Cor(DCRUDE,DCRUDE(-i))
2 2

.1

0 .0

• .1

2 -.2
Anal 2 3 4 5 6 7 8 9 10 11 12 2 3 4 5 6 7 8 9 10 11 12 lines,
which indicates that the residuals do not exhibit any statistically significant autOCOITelation at any lag. This is a key result, as it
suggests that the model used to generate the residuals has successfully captured the underlying structure of the data. In other words,
the model has accounted for the time-dependent patterns, and what remains (the residuals) behaves like white noise. When residuals
show no significant autOCOITelation, it implies that there is no systematic pattern left unexplained by the model. This is important
because significant autocorrelation in residuals would indicate model misspecification, meaning the model may have failed to account
for certain aspects of the data, leading to biased or inefficient forecasts. The lack of autocorrelation also suggests that the residuals
are stationary, with constant mean and variance over time, and do not exhibit seasonality or other cyclical behaviour. Essentially,
the residuals appear to be nmdom, validating the appropriateness of the model. The correlogram analysis of the residuals confirms
that the model fits the data well, as there are no patterns or
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By steering clients toward sector rotation strateg .brokers can help them capitalize on macroeconomic
w
cycles. Sector rotation involves reallocating investments based on the different phases of the economic cycle
expansion,
peak, contraction, and trough. For instance, during economic expansion, cyclical sectors like consumer goods,
industrials, and financials may perform well, while during downturns, defensive sectors such as healthcare,
utilities, and consumer staples often offer more stable returns. In addition, brokers should monitor corporate
earnings and balance sheets for their clients to identify stocks that are fundamentally strong, regardless of short
term,mu·ket fluctuations. Strong e,m1ings growth, low debt levels, and competitive advantages often signal
companies that can weather volatile periods better than those dependent on commodity price movements like
crude oil. Ultimately, a comprehensive, data-driven approach to portfolio management one that includes multiple
asset classes, global macroeconomic insights, and sector-specific analysis will better serve clients in the long run.
This approach reduces overreliance on any one variable (such as crnde oil prices) and helps investors achieve
stable, long-term returns. In volatile times, like periods of oil price fluctuation, this strategy would protect clients
from sudden market drops and give them the flexibility to adjust to evolving market conditions.

FOR INVESTORS AND TRADERS

fJ
lnvest◊rs and traders should carefully consider the study's findings regarding the limited long-term impact of oil
prices on Indian stock indices like SENSEX and Nifty 50 when formulating thei.r strategies. The research
highlights that while Brent crude oil price fluctuations can cause temporary movements in the stock market, these
effects tend to dissipate within a relatively short timeframe approximately 5.5 days. As such,oil price movements
offer little predictive power for the long-term performance of these equity indices, which should prompt both
investors and traders to reconsider the weight they place on crude oil trends when making investment decisions.
For long-term investors, this means focusing on fundamental factors such as corporate earnings, economic growth,
and sectoral performance is a far more robust strategy than attempting to time the market based on oil price
volatility. While energy prices can influence certain sectors, their overall impact on broad market indices like
SENSEX and Nifty 50 is relatively short-lived. Consequently, building a portfolio based on long-term economic
indicators and fundamental analysis is crucial. Investors should diversify thei.r portfolios to include other asset
classes, such as bonds, real estate, and alternative investments like commodities or private equity, to hedge against
market volatility. Diversifying helps protect against the unprediclllbility of external factors such as geopolitical
tensions or sudden oil price spikes, which can create shorl-lenn noise but have little bearing on long-term market
trends.

Incorporating bonds into the portfolio, for example, provides a hedge during periods of stock market volatility
or uncertainty driven by global factors. Alternative investments, such as commodities (beyond crude oil),
precious metals, or even infrastructure funds, offer additional protection agains,tmu·ket shocks by spreading
risk across different asset classes that may react differently to global economic conditions. This balanced
approach ensures that investors are not overly reliant on the unpredictable and often volatile oil market. On the
other hand, short term traders can still find opp.unities in the oil rruu·ket, but they should be highly aware of
the short-lived nature of these opportunities. Given that the impact of oil price movements on stock indices is
temporary, active traders might consider employing momentum trading, scalping, or short-term arbib·age
strategies to captl.ains from rapid price adjustments. Momentum trading, for instance, allows traders to take
advantage of quick price shifts in the stock market that occur immediately after an oil price shock. However,
they must be cautious about the timing
of entry and exit points. Since the influence of crude oil prices is transient, technical analysis bec-Omes crucial.
Using technical indicators such as moving averages, relative strength index (RSI), or Bollinger Bands can help
traders identify optimal moments to initiate or close positions. For example, when oil prices experience a sharp
rise due to geopolitical tensions or supply constraints, ce1tain sectors like energy, t:ranspo1tation, and
manufacturing may see rapid price changes. Traders can exploit this short-term volatility by trading in stocks or
derivatives related to these sectors. However, traders need to remain vigilant, as the effects of these price
movements tend to subside within a few days. If they hold positions for too long, they may risk losses as the
market returns to its previous state. Risk management becomes especially important for b·aders dealing with oil
related shocks. Given the rapid dissipation of the effects, it is advisable for traders to implement stop-loss orders
or use options strategies to limit potential downsides. Stop-loss mechanisms can protect traders from holding onto
positions that reverse quickly after the initial price shock fades, while options such as protective puts or covered
calls can help hedge against unexpected market reversals. Short-term oil price fluctuations can present trading
opportunities, particularly for active traders, the study underscores the fact that long-term gains in lndian equity
markets are unlikely to be driven by oil price trends. Therefore, long-term investors should prioritize diversified
portfolios that include a variety of asset classes and focus on economic fundamentals, while short-term traders
should remain alert and adopt technical trading strategies to make the most of temporary price movements without

-
over-relying on oil price volatility.

FOR MARKET ANALYSTS

Fo,rmu·ket analysts, the findings 06 this study emphasize the necessity of adopting a more com rehensive
approach when forecasting stock market movements. While crude oil prices are frequently scrutinized and often
perceived as a key driver of market perfonnance, the analysis reveals that they do not play a dominant role in
influencing lndian stock indices such as SENSEX and Nifty 50. This suggests that analysts should be cautious
in overemphasizing oil prices in thei1· forecasts and instead consider a broader array of economic indicators
that could provide a more nuanced and accurate picture of market dynamics. One critical area for analysts to
focus on is interest rate movements. Changes in centml bank policies, such as adjustments to the repo rate or
reverse rep◊ rate, can have profound implications for borrowing costs, consumer spending, and overall
economic growth. Analysts should closely monitor central bank communications and economic reports to
understand the potential impacts of interest rate changes on stock market valuations and sector performances.
For instance, rising interest rates might dampen consumer spending and corporate investment, leading to slower
economic growth and negatively impacting stock prices. Additionally, inflation is another significant variable
that can shape market sentiment and investment decisions. High inflation can erode purchasing power, leading
to decreased consumer confidence and spending, which in tum 'E!l1'1dversely affect corporate earnings and stock
prices. Analysts should incorporate inflation indicators, such as the Consumer Price Index (CPI) and Wholesale
Price Index (WPl), into their models to gauge how rising prices may influence market performance. By
analysing these factors, analysts can better predict sectors that might benefit or suffer under various inflationary
scenarios.

Furthermore, global trade conditions can play a pivotal role in determining stock market trends. Analysts should
take into account developments in intemational trade agreements, tariffs, and geopolitical events that could disrupt
supply chains or affect export-import dynamics. For instance, shifts in trade policies, such as those resulting from
tensions between major economies, can significantly impact certain sectors, particularly those heavily reliant on
exports or imports. By integrating global economic indicators, analysts can gain insights into how external
factors may influence domestic stock performance. Lastly, domestic fiscal policies should not be overlooked.
Government budgets, taxation policies, and public spending decisions can significantly affect market sentiment
and economic growth prospects. Analysts should keep abreast of the government's fiscal measures and thei.r
potential implications for various industries. For instance, increased infrastructure spending could benefit
consb·uction and engineering stocks, while tax hikes might pressure consumer-focused sectors.Therefore,
market analysts are encouraged to embrace a more holistic approach when forecasting stock market
movements. By integrating a diverse set of economic indicators including interest rates, inflation, global b·ade
conditions, and domestic fiscal policies into their analytical frameworks, they can provide clients and
stakeholders with more accurate and comprehensive insights. This multifaceted perspective will enhance their
ability to identify potential market b·ends and opportunities, ultimately leading to better-informed investment
decisions and sb·ategies. By moving beyond a narrow focus on crude oil prices, mrnlysts can improve their
predictive accuracy and conh·ibute more effectively to the understm1ding of complex market dynamics.
plage
ORIGINALITY REPORT

26 %
SIMILARITY INDEX
17%
INTERNET SOURCES
24%
PUBLICATIONS
11%
STUDENT PAPERS

PRIMARY SOURCES

1
Prince Dorian Rivel Bambi, Jean Baptiste
Bernard Pea-Assounga. "Assessing the
1
%
influence of land use, agricultural,
industrialization, CO2 emissions, and energy
intensity on cereal production", Journal of
Environmental Management, 2024
Publication

Submitted to RMIT University

2 Student Paper 1%
eprints.kingston.ac.uk
3 Internet Source 1%
Submitted to University of Greenwich
4 Student Paper 1%
dspace.lib.uom.gr
5 Internet Source 1%
6
Tarak Nath Sahu. "Macroeconomic
Variables and Security Prices in India 1
during the Liberalized Period", Springer %
Science and Business Media LLC, 2015
Publication
7 Hosseini, Seyedmehdi. "Stock Market and Its
Determinants: Three Empirical Studies",
1%
University of Kent (United Kingdom), 2022
Publication

<1%
8 phd-dissertations.unizik.edu.ng
Internet Source

<1%
9 iibf.org.in
Internet Source

<1%
10 idoc.pub
Internet Source

<1%
11 Submitted to Galileo Global Education
Student Paper

<1%
12 Yasser Hussain. "The Impact of Climate
Change on Rice Production in Punjab: An Auto
Regression Distributed Lag Model", Current
Agriculture Research Journal, 2024
Publication

<1%
13 epe.lac-bac.gc.ca
Internet Source

<1%
14 Submitted to Asia Pacific University College of
Technology and Innovation (UCTI)
Student Paper

<1%
15 Uğur Soytaş, Ramazan Sarı. "Routledge
Handbook of Energy Economics", Routledge,
2019
Publication
 repositorio.iscte-iul.pt
16 Internet Source <1%
17 Nagwa Amin Abdelkawy, Abdullah Sultan Al
Shammre. "Fiscal Policy and Economic
<1%
Resilience: The Impact of Government
Consumption Alongside Oil and Non-Oil
Revenues on Saudi Arabia’s GDP during Crises
(1969–2022)", Sustainability, 2024
Publication

<1%
18 mpra.ub.uni-muenchen.de
Internet Source

<1%
19 Submitted to University of Durham
Student Paper

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20 Submitted to University of Westminster
Student Paper

<1%
21 M. A. H. Dempster, Ke Tang. "Commodities",
Chapman and Hall/CRC, 2019
Publication

<1%
22 Dimitriadou, Athanasia. "The Influence of
News and Investor Sentiment on Exchange
Rate Determination: New Evidence Using
Panel Data in the Banking Sector", University
of Derby (United Kingdom), 2024
Publication

Submitted to University of Essex

23 Student Paper <1%
24 hdl.handle.net
Internet Source <1%
25 nek.istanbul.edu.tr:4444
Internet Source <1%
26 "The Interrelationship Between Financial and
Energy Markets", Springer Science and
<1%
Business Media LLC, 2014
Publication

<1%
27 Nadeem Baig, Sani I. Abba, Jamil Usman,
Ibrahim Muhammad, Ismail Abdulazeez, A.G.
Usman, Isam H. Aljundi. "Bio-inspired MXene
membranes for enhanced separation and
anti-fouling in oil-in-water emulsions: SHAP
explainability ML", Cleaner Water, 2024
Publication

<1%
28 ebin.pub
Internet Source

<1%
29 Foday Daboh, Ezekiel K. Duramany-Lakkoh,
Terrence Laurel Knox-Goba. "Analyzing the
Structural Relationship between Money
Supply, Inflation, and Economic Growth in
Sierra Leone: A VAR Model Approach",
Theoretical Economics Letters, 2024
Publication

Submitted to Universidad Nacional de San

30
Cristóbal de Huamanga <1%
Student Paper
 <1%
31 www.cbsl.gov.lk
Internet Source

32 dspace.unza.zm
Internet Source <1%
33 Submitted to Liverpool John Moores
University
<1%
Student Paper

34 keffi.nsuk.edu.ng
Internet Source <1%

<1%
35 Wenshuo Song, Weihua Cao, Yan Yuan, Kang-
Zhi Liu. "A new spatiotemporal long-term
prediction method for Continuous Annealing
Processes", Engineering Applications of
Artificial Intelligence, 2025
Publication

<1%
36 iuokada.edu.ng
Internet Source

<1%
37 moam.info
Internet Source

<1%
38 "Handbook of Research on Emerging
Theories, Models, and Applications of
Financial Econometrics", Springer Science and
Business Media LLC, 2021
Publication

Avinash K. Shrivastava, Rana Sudhir, Amiya

39
Kumar Mohapatra, Mangey Ram. "Advances <1%
 in Management Research - Innovation and
Technology", CRC Press, 2019
Publication

40
Nikhil Yadav, Priyanka Tandon, Ravindra
Tripathi, Rajesh Kumar Shastri. "A dynamic
<1%
relationship between crude oil price and
Indian equity market: an empirical study
with special reference to Indian benchmark
index Sensex", Benchmarking: An
International Journal, 2020
Publication

<1%
I Gusti Ngurah Agung. "Cross Section
41
and Experimental Data Analysis Using
Eviews", Wiley, 2011
Publication

core.ac.uk
42 Internet Source <1%
ben Dahmash, Nouf. "Oil Price Shocks: The
43
Impact on Returns, Exchange Rates, and the <1%
Role of Economic Policy Uncertainty", The
University of Manchester (United Kingdom),
2024
Publication

jibe-net.com
44 Internet Source <1%
repository.library.du.ac.bd:8080
45 Internet Source <1%
46 www.amf.org.ae
Internet Source <1%
47 Namburete, Salvador. "The Export
Competitiveness of Mozambique's Cashew
<1%
Nut Industry: Applying Porter's Diamond
Model", ISCTE - Instituto Universitario de
Lisboa (Portugal), 2023
Publication

<1%
48 kups.ub.uni-koeln.de
Internet Source

<1%
49 www.ncbi.nlm.nih.gov
Internet Source

<1%
50 Chung-ki Min. "Applied Econometrics - A
Practical Guide", Routledge, 2019
Publication

<1%
51 Sunil K. Mohanty, Mohan Nandha. "Oil Shocks
and Equity Returns: An Empirical Analysis of
the US Transportation Sector", Review of
Pacific Basin Financial Markets and Policies,
2011
Publication

www.ng-epf.si
52 Internet Source <1%
www.rassweb.com
53 Internet Source <1%
vital.seals.ac.za
54 Internet Source

<1%
55 Muhammad Qasim Mahmood, Xiuquan
Wang, Farhan Aziz, Tianze Pang. "Evaluating
<1%
the sustainability of groundwater
abstraction in small watersheds using time
series analysis", Groundwater for
Sustainable Development, 2024
Publication

56
<1%
Submitted to Trinity College Dublin
Student Paper

57
<1%
financedocbox.com
Internet Source

58
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prr.hec.gov.pk
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59
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pure.royalholloway.ac.uk
Internet Source

60
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repository.oiu.edu.sd:8080
Internet Source

61
<1%
www.ijraset.com
Internet Source

62
<1%
Submitted to CITY College, Affiliated Institute
of the University of Sheffield
Student Paper
63 Monika W. Koczar, Francisco Jareño, Ana
Escribano. "Dynamic linkages and contagion
<1%
effects: Analyzing the linkages between crude
oil prices, US market sector indices and
energy markets", The North American Journal
of Economics and Finance, 2024
Publication

<1%
64 Sotiris Tsolacos, Mark Andrew. "Applied
Quantitative Analysis for Real Estate",
Routledge, 2020
Publication

<1%
65 WEI YANG, AI HAN, SHOUYANG WANG.
"ANALYSIS OF THE INTERACTION BETWEEN
CRUDE OIL PRICE AND US STOCK MARKET
BASED ON INTERVAL DATA", International
Journal of Energy and Statistics, 2013
Publication

Emmanuel S. Akpan, Gamaliel O. Eweke.

66
"Foreign Direct Investment and Industrial <1%
Sector Performance: Assessing the Long-Run
Implication on Economic Growth in Nigeria",
Journal of Mathematical Finance, 2017
Publication

Submitted to Universidad San Ignacio de

67
Loyola <1%
Student Paper

etd.uwc.ac.za
68 Internet Source <1%
69 Chengsi Zhang. "Inflation in China -
Microfoundations, Macroeconomic Dynamics,
<1%
and Monetary Policy", Routledge, 2020
Publication

<1%
70 Gloria González-Rivera. "Forecasting for
Economics and Business", Routledge, 2016
Publication

<1%
71 Qaiser Munir, Sook Ching Kok. "Information
Efficiency and Anomalies in Asian Equity
Markets - Theories and evidence", Routledge,
2019
Publication

<1%
72
Submitted to University of Southampton
Student Paper

<1%
73
Uğur Uzun, Zafer Adalı. "chapter 16
Investigation for the Role of Oil and Natural
Gas in the BIST Sector Indexes in Turkey", IGI
Global, 2021
Publication

Zhu, Hui-Ming, Rong Li, and Sufang Li.

74
"Modelling dynamic dependence between <1%
crude oil prices and Asia-Pacific stock market
returns", International Review of Economics &
Finance, 2013.
Publication

Baranidharan Subburayan. "Causality and

75
volatility spillovers of banks' stock price <1%
 Publication
returns on BSE Bankex returns", Journal of
Corporate Accounting & Finance, 2023
Publication

Submitted to Fachhochschule fuer Wirtschaft

76
Berlin
Student Paper

Tóth, Arnold. "Advanced Imaging in Traumatic

77
Brain Injury", University of Pécs
(Hungary), 2024
Publication

Abdulazeez, Suwaibat Arinola. "Determinants

78
of Agricultural Output Growth in Nigeria",
Kwara State University (Nigeria), 2023
Publication

WEIWEN NG. "OIL PRICE VOLATILITY

79
AND THE SINGAPORE
MACROECONOMY", The
Singapore Economic Review, 2012
Publication

80
dione.lib.unipi.gr
Internet Source

81
Franck Ramaharo. "LMDI decomposition and
macroeconomic drivers of electricity intensity
in Madagascar", Cambridge University Press
(CUP), 2024
Publication

82
Semssar, Salim A.. "Predictive Quality
Analytics.", Purdue University, 2023
 1%
<1%
<
1
%

<1%
<
1
%

<
1
%

<
1
%

<
83 eprints.glos.ac.uk
Internet Source <1%
84 gemini.econ.umd.edu
Internet Source <1%
85 idoc.tips
Internet Source <1%
86 Ijambo, Bertha Deshimona. "An Econometric
Analysis of Spatial Market Integration and
<1%
Price Formation in the Namibian Sheep
Industry", University of Pretoria (South
Africa), 2023
Publication

<1%
87 store.ectap.ro
Internet Source

<1%
88 Fan-Ping Chiu, Chia-Sheng Hsu, Alan Ho, Chi-
Chung Chen. "Modeling the price
relationships between crude oil, energy
crops and biofuels", Energy, 2016
Publication

<1%
89 Isiaka Akande Raifu, Sebil Olalekan Oshota.
"Re-examining oil price-stock market
returns nexus in Nigeria using a two-stage
Markov regime switching approach",
International Journal of Energy Sector
Management, 2022
Publication
90 Shahid Raza, Sun Baiqing, Pwint Kay-Khine,
Muhammad Ali Kemal. "Uncovering the Effect
<1%
of News Signals on Daily Stock Market
Performance: An Econometric Analysis",
International Journal of Financial Studies,
2023
Publication

<1%
91 Rizwan Ahmed, Xihui Haviour Chen,
Chamaiporn Kumpamool, Dung T.K. Nguyen.
"Inflation, oil prices, and economic activity in
recent crisis: Evidence from the UK", Energy
Economics, 2023
Publication

www.aessweb.com
92 Internet Source <1%
Sachu Sarasan, Sajith Sarasan, Aneesha K.
93
Shaji. "Chapter 97 Volatility Spillover Effect <1%
and Relationship Between the Oil Price and
Stock Market Returns of the United States: A
Scoping Review for Future Research
Trajectories", Springer Science and Business
Media LLC, 2025
Publication

Wu, Xiangyu. "Performance of Value Investors

94
Versus Technical Investors on the US Stock <1%
Market.", Webster University, 2023
Publication
95 www.gla.ac.uk
Internet Source <1%
96 www.univ-oran2.dz
Internet Source <1%
97 Ahmad A. Al-Majali, Sulieman D. Al-Oshaibat,
Ahmad A. Al-Sarayreh, Sufian Radwan Al-
<1%
Manaseer. "The effect of digital financial
literacy on financial development and
governance: Using panel vector
autoregressive model", Journal of Governance
and Regulation, 2024
Publication

<1%
98 Submitted to University of Nottingham
Student Paper

<1%
99 repository.smuc.edu.et
Internet Source

<1%
100 baadalsg.inflibnet.ac.in
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<1%
101 www.asjp.cerist.dz
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<1%
102 anzdoc.com
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<1%
103 Submitted to University of Brighton
Student Paper

104 vital.seals.ac.za:8080
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<1%
105
www.ojcoca.org
Internet Source <1%
106
Satyendra Kumar Sharma, Praveen Goyal,
Udayan Chanda. "Handbook of Evidence
<1%
Based Management Practices in Business",
Routledge, 2023
Publication

<1%
Wenming Shi, Zhongzhi Yang, Kevin X. Li. "The
107
impact of crude oil price on the tanker
market", Maritime Policy & Management,
2013
Publication

<1%
repository.nwu.ac.za
108 Internet Source

<1%
vuir.vu.edu.au
109 Internet Source

<1%
Degiannakis, Stavros, George Filis, and
110
Christos Floros. "Oil and stock returns:
Evidence from European industrial sector
indices in a time-varying environment",
Journal of International Financial Markets
Institutions and Money, 2013.
Publication

Submitted to University of KwaZulu-Natal

111 Student Paper <1%
112 Chicas, Beatriz. "Oil Price Shocks and its Effect
on the Brazilian, German, and Norwegian
<1%
Stock Markets", Universidade do Porto
(Portugal), 2024
Publication

<1%
113 Submitted to University of Rwanda
Student Paper

<1%
114 dspace.lib.ntua.gr
Internet Source

<1%
115 James Ajuong Arou, Kanbiro Orkaido
Deyganto. "The Influence of Inflation Rate
on Economic Growth in South Sudan", Qeios
Ltd, 2024
Publication

<1%
116 Kupabado, Moses Mananyi. "Price and
Volatility Effects of Commodity
Financialization", Friedrich-Alexander-
Universitaet Erlangen-Nuernberg (Germany),
2024
Publication

uir.unisa.ac.za
117 Internet Source <1%
sigarra.up.pt
118 Internet Source <1%
Reboredo, Juan C., and Miguel A. Rivera-
119
Castro. "Wavelet-based evidence of the <1%
 impact of oil prices on stock returns",
International Review of Economics & Finance,
2013.
Publication

<1%
Submitted to Science High School
120 Student Paper

<1%
Submitted to University of Wales Institute,
121
Cardiff
Student Paper

<1%
das Neves, Ana Miriam Mata. "A Relação
122
Família-Escola em Famílias das
Comunidades Ciganas e em Famílias
Residentes em Áreas de Baixo Nível
Socioeconómico", ISCTE - Instituto
Universitario de Lisboa (Portugal), 2024
Publication

Akoum, Ibrahim, Michael Graham, Jarno

123
Kivihaho, Jussi Nikkinen, and Mohammed <1%
Omran. "Co-movement of oil and stock prices
in the GCC region: A wavelet analysis", The
Quarterly Review of Economics and Finance,
2012.
Publication

Submitted to Lebanese University

124 Student Paper <1%
vdoc.pub
125 Internet Source <1%
126 Submitted to University of Warwick
Student Paper <1%
127 Farman Ali, Pradeep Suri, Tarunpreet Kaur,
Deepa Bisht. "Cointegration and
<1%
causality relationship of Indian stock
market with selected world markets",
F1000Research, 2023
Publication

<1%
128 dspace.cuni.cz
Internet Source

<1%
129 Adamu, Ibrahim Mohammed. "Dynamic
Effects of External Debt Accumulation on
Public Capital Formation and Economic
Growth: Empirical Evidence from Nigeria",
University of Malaya (Malaysia), 2023
Publication

K. Nirmal Ravi Kumar. "Econometrics", CRC

130
Press, 2020 <1%
Publication

Victor Ogneru, Oana Mădălina Popescu,

131
Stelian Stancu. "Relationship between VAT <1%
Revenue and Intermediate Consumption - A
VAR Approach", Proceedings of the
International Conference on Applied
Statistics, 2019
Publication

Submitted to Bogazici University

132 Student Paper

<1%
133 G. Gozgor, B. Kablamaci. "The linkage
between oil and agricultural commodity
<1%
prices in the light of the perceived global
risk", Agricultural Economics (Zemědělská
ekonomika), 2014
Publication

134
<1%
Jawad, Khadija Ali. "Inflation in Saudi Arabia:
Long and Short Run Determinants", The
British University in Dubai, 2023
Publication

135
<1%
Probir Kumar Bhowmik, Muhammad Rakibul
Islam. "Factors Propelling Financial Inclusion
in an Emerging Economy: An analysis through
the ARDL Model", Springer Science and
Business Media LLC, 2024
Publication

136 Maliaga, Lufuno. "The Impact of Trade

Openness on Economic Growth in South <1%
Africa.", University of Johannesburg (South
Africa), 2021
Publication

137 Mercy Olufunke ADE-WILLIAMS, Simon

Amodu YUNISA. "Assets Management <1%
Corporation and Bank Stability in Nigeria",
 LASU Journal of Employment Relations &
Human Resource Management, 2023
Publication

138
Muhammad Farhan Bashir. "Oil price
shocks, stock market returns, and volatility
<1%
spillovers: a bibliometric analysis and its
implications", Environmental Science and
Pollution Research, 2022
Publication

<1%
Jabar, Kale Kamaran. "Petrol Fiyatları ve Borsa
139
Endeks Değeri Arasındaki Ilişki: Suudi
Arabistan Orneği", Marmara Universitesi
(Turkey), 2024
Publication

Li, Su-Fang, Hui-Ming Zhu, and Keming Yu.

140
"Oil prices and stock market in China: A sector <1%
analysis using panel cointegration with
multiple breaks", Energy Economics, 2012.
Publication

Mustafa Uysal, Zafer Adalı. "chapter 67 The

141
Relationship Between Commodity Prices and <1%
Selected Macroeconomic Variables in Turkey",
IGI Global, 2022
Publication

Nida Akram, Shahla Andleeb, Khalil ur

142
Rehman, Muhammad Waqar Akram, <1%
Muhammad Zubair Tariq. "Does CPEC benefit
the sustainable agricultural development in
 Pakistan: a comparison with open
investment policy 1997", Environment,
Development and Sustainability, 2024
Publication

<1%
www.scribd.com
143 Internet Source

<1%
"Digital Technologies and Applications",
144
Springer Science and Business Media LLC,
2024
Publication

<1%
Fakunmoju , Segun Kamaru. "Nexus Between
145
Market Liquidity and Volatility of Stock
Return in Nigeria.", Kwara State University
(Nigeria), 2020
Publication

Nathrah, Mohd Yacob. "The Determinants of

146
Stock Market Volatility: Macroeconomic <1%
Fundamentals and Investor Sentiment",
University of Malaya (Malaysia), 2023
Publication

Parnia Shahrestani, Meysam Rafei. "The

147
impact of oil price shocks on Tehran Stock <1%
Exchange returns: Application of the Markov
switching vector autoregressive models",
Resources Policy, 2020
Publication
148 Submitted to Queen Mary and Westfield
College
< 1%
Student Paper

149 Silva, Bruno Miguel Romão. "Operações de

Apoio à Paz: Guarda Nacional Republicana
< 1%
no Iraque (2003-2005)", Universidade de
Evora (Portugal), 2024
Publication

< 1%
150 Supply Chain Management: An International
Journal, Volume 19, Issue 3 (2014-09-16)
Publication

< 1%
151 Yitong, Chen. "Empirical Study on the Impact
of Intermediate Target of Monetary Policy
on Real Estate Market Prices in China", ISCTE -
Instituto Universitario de Lisboa (Portugal),
2024
Publication

Gonçalves, Diana Raquel Sousa. "A

152
Adequação da Política Monetária do Bce a < 1%
Portugal: Uma Análise Baseada nos Choques
Que Afetam a Economia", ISCTE - Instituto
Universitario de Lisboa (Portugal), 2023
Publication

Houda BenMabrouk. "Cross-herding behavior

153
between the stock market and the crude oil < 1%
market during financial distress", Managerial
Finance, 2018
Publication
154 Khalid Eltayeb Elfaki, Elsadig Musa Ahmed.
"Globalization and financial development
<1%
contributions toward economic growth in
Sudan", Research in Globalization, 2024
Publication

<1%
155 Motshana, Dumisani. "An Analysis of
Productivity and Demand as Drivers of
Structural Change in South Africa, 1970-
2014", University of Johannesburg (South
Africa), 2021
Publication

<1%
156 Oderinde Lukmon, Sanusi Gbenga, Adelakun
Ojo, Agbawn Matthew. "Response of self-
owned businesses to monetary policy in a
developing economy", BRICS Journal of
Economics, 2024
Publication

Sehgal, S., and R. Kapur. "Relationship

157
between Oil Price Shocks and Stock Market <1%
Performance: Evidence for Select Global
Equity Markets", Vision The Journal of
Business Perspective, 2012.
Publication

Thomas Andreas Maurer. "Exploring the

158
Financial Landscape in the Digital Age", <1%
CRC Press, 2024
Publication

etheses.whiterose.ac.uk
159 Internet Source

<1%
160 pdffox.com
Internet Source <1%
161 Ayuba, Kazeem. "Determinants of Exchange
Rate Fluctuations in Nigeria", Kwara State
<1%
University (Nigeria), 2023
Publication

162
<1%
Muhammad Rizwan, Kiran Zahara Gillani,
Maira Bashir, Muhammad Abubakar.
"Unleashing the Dynamics Among Energy
Consumption, Gross Domestic Product,
Environmental Degradation and
Urbanization: An Evidence from Belt and
Road Initiative Countries", Pakistan Journal
of Humanities and Social Sciences, 2023
Publication

163 Quanxing, Zhang. "Using the Baidu Index to

Predict Chinese Housing Price and Volume - A <1%
Survey-Based Keyword Selection Approach",
Universidade NOVA de Lisboa (Portugal),
2024
Publication

164 Samuel Oweh Abang, Bassey Okon Ebi, Felix

Awara Eke. "Inflation, income distribution <1%
nexus. A pathway to Nigeria's long term
socioeconomic development. A chain rule
 effect", Springer Science and Business
Media LLC, 2024
Publication

165
Scott M.R. Mahadeo, Reinhold Heinlein,
Gabriella D. Legrenzi. "Energy contagion
<1%
analysis: A new perspective with application
to a small petroleum economy", Energy
Economics, 2019
Publication

<1%
Stevenson, Katherine A.. "Interactive
166
Effects of Predation and Assembly Time on
Tropical but Not Temperate Marine
Invasions", North Dakota State University,
2024
Publication

167
Susan Chiu, Domingo Tavella. "Data Mining <1%
and Market Intelligence for Optimal
Marketing Returns", Elsevier, 2008
Publication

168
hydra.hull.ac.uk <1%
Internet Source

169
nrb.org.np <1%
Internet Source

170
repository.unam.edu.na <1%
Internet Source

171
www.sciedu.ca <1%
Internet Source
172 Babatunde Olatunji Odusami. "Crude oil
shocks and stock market returns", Applied
< 1%
Financial Economics, 2009
Publication

< 1%
173 Ki-Hong Choi, Ramzi Nekhili, Walid Mensi,
Ferihane Zaraa Boubaker, Seong-Min Yoon.
"Systemic risk-sharing between natural gas,
oil, and stock markets in top energy
producer and consumer countries",
International Review of Economics & Finance,
2024
Publication

174
Titus Ayobami Ojeyinka, Dauda Olalekan < 1%
Yinusa. "External shocks and output
composition: evidence from Nigeria", Journal
of Economic and Administrative Sciences,
2020
Publication

175
Liang Shen, Yukun Bao, Najmul Hasan, < 1%
Yanmei Huang, Xiaohong Zhou, Changrui
Deng. "Intelligent crude oil price probability
forecasting: Deep learning models and
industry applications", Computers in
Industry, 2024
Publication

176
Liming Wang. "Rising China in the Changing < 1%
World Economy", Routledge, 2012
Publication
177 Mdluli, Bonginhlanhla. "The Impact of the
Sovereign Bond Rating Revisions and their
<1%
Spillover Effects within the BRICS Listed
Equity Markets", University of Johannesburg
(South Africa), 2023
Publication

<1%
178 Yu Li, Muhammad Umair. "The Protective
Nature of Gold During Times of Oil Price
Volatility: An Analysis of the COVID-19
Pandemic", The Extractive Industries and
Society, 2023
Publication

<1%
179 www.globalscientificjournal.com
Internet Source

Natanelov, Valeri, Manoj Dora, Xavier

180
Gellynck, and Guido Van Huylenbroeck. <1%
"Crises, crude oil and BRIC stock markets",
International Journal of Business and
Emerging Markets, 2013.
Publication

Niftiyev, Ibrahim. "Dutch Disease-Led De-

181
Industrialization in the Azerbaijan's Economy: <1%
Analysis of the Chemicals Industry",
Szegedi Tudomanyegyetem (Hungary),
2023
Publication

182
Olatunji A. Shobande, Simplice A. Asongu. <1%
"Financial development, human capital
 development and climate change in East and
Southern Africa", Environmental Science and
Pollution Research, 2021
Publication

<1%
dos Santos Coelho, Paula Cristina Oliveira.
183
"Coping e Presentismo: Que Relação?", ISCTE
- Instituto Universitario de Lisboa
(Portugal), 2024
Publication

<1%
file.scirp.org
184 Internet Source

<1%
www.boj.org.jm
185 Internet Source

<1%
Delessa Terefe Kitessa, Teera Jewaria.
186
"Determinants of tax revenue in East African
countries: An application of multivariate
panel data cointegration analysis", Journal of
Economics and International Finance, 2018
Publication

Jammazi, Rania. "Cross dynamics of oil-stock

187
interactions: A redundant wavelet analysis", <1%
Energy, 2012.
Publication

Mané, Sana Eteki M`Boumena.

188
"Determinantes do Incumprimento dos <1%
Bancos na Guiné-Bissau", ISCTE - Instituto
Universitario de Lisboa (Portugal), 2024
Publication
189 Mashele, Shighughudwana. "The Impact of
Bank Intermediation on Economic Growth in
<1%
South Africa, 1981-2007.", University of
Johannesburg (South Africa), 2021
Publication

<1%
190 Submitted to Nottingham Trent University
Student Paper

<1%
191 Robert McNown, Omar S. Aburizaizah,
Charles Howe, Nathan Adkins. "Forecasting
annual water demands dominated by
seasonal variations: the case of water
demands in Mecca", Applied Economics, 2014
Publication

<1%
192 Thai-Ha Le. "Do Soaring Global Oil Prices
Heat up the Housing Market? Evidence from
Malaysia", Economics: The Open-Access,
Open-Assessment E-Journal, 2015
Publication

Tii N. Nchofoung. "Oil price shocks and

193
energy transition in Africa", Energy Policy, <1%
2024
Publication

Submitted to University of Leicester

194 Student Paper <1%
www.esds.ac.uk
195 Internet Source <1%
196 Пјешчић, Веселин M.. "Mogućnosti I
Ograničenja Politike Deviznog Kursa U
<1%
Kontekstu Ciljanja Inflacije", University of Nis
(Serbia), 2024
Publication

<1%
197 B. Faye, E. Le Fur, S. Prat. "Dynamics of fine
wine and asset prices: evidence from short-
and long-run co-movements", Applied
Economics, 2015
Publication

<1%
198 Gonçalves, Daniel Alexandre Alves. "Unveiling
the Global Ripple Effect: How the Fed's
Monetary Policy Shaped Foreign Financial
Markets in the Pre and Post Global
Financial Crisis Era", Universidade do Porto
(Portugal), 2024
Publication

Hanan Naser, Fatima Al-aali, Yomna Abdulla,

199
Rabab Ebrahim. "The impact of oil price <1%
and COVID-19 pandemic on clean energy
stocks: an empirical approach using ARDL",
Arab Gulf Journal of Scientific Research, 2023
Publication

Ogunjemilua, Oluwafemi David. "Protein

200
Premiums in Hard Red Spring Wheat: A <1%
Comparison of Econometric and Machine-
Learning Approaches", North Dakota State
University, 2023
 Publication

201
Pinar Göktaş. "Can Unprocessed Food Prices
Really Be One of the Main Responsible
<1%
Causes for not Achieving Inflation Targets in
Turkey?", Zeszyty Naukowe SGGW w
Warszawie - Problemy Rolnictwa Światowego,
2016
Publication

<1%
Submitted to UNIVERSITY OF LUSAKA
202 Student Paper

<1%
Valentyna Ozimkovska, Stanislaw Kubielas.
203
"Deviation of the Ukrainian hryvnia from the
equilibrium exchange rate", Post-Communist
Economies, 2013
Publication

Wei Luo, Maria Ciurea, Santosh Kumar.

204
"Computational Social Science", CRC Press, <1%
2021
Publication

etd.aau.edu.et
205 Internet Source <1%
Ani Stoykova, Mariya Paskaleva. "SOUTHEAST
206
EUROPEAN CAPITAL MARKETS: DYNAMICS, <1%
RELATIONSHIP AND SOVEREIGN CREDIT
RISK", Walter de Gruyter GmbH, 2018
Publication
207 Juan C. Reboredo. "Nonlinear effects of oil
shocks on stock returns: a Markov-switching
<1%
approach", Applied Economics, 2010
Publication

<1%
208 Olivier Lamotte, Thomas Porcher, Christophe
Schalck, Stephan Silvestre. "Asymmetric
gasoline price responses in France",
Applied Economics Letters, 2013
Publication

<1%
209 Submitted to Royal Holloway and
Bedford New College
Student Paper

<1%
210 Tselikis, Panagiotis | Παναγιώτης, Τσελίκης.
"Investment Strategies and Market
Anomalies. The Past and the Future",
University of Piraeus (Greece), 2023
Publication

Submitted to University of Reading

211 Student Paper <1%
Carlos David Cardona Arenas, Lya Paola
212
Sierra Suárez, Francesc Trillas Jané. <1%
"Revealing the New Nexus in Urban
Unemployment Dynamics: The Relationship
between Institutional Variables and Long-
Term Unemployment in Colombia",
Economics, 2024
Publication
213 Carlos Pinho, Mara Madaleno. "Oil prices and
stock returns: nonlinear links across
< 1%
sectors", Portuguese Economic Journal, 2016
Publication

< 1%
214 Costas Grammenos. "The Handbook of
Maritime Economics and Business", Informa
Law from Routledge, 2019
Publication

< 1%
215 David T. Griffiths. "Forecasting income shares:
are mean-reversion assumptions
appropriate?", Applied Economics, 2007
Publication

< 1%
216 Dezhong Xu, Bin Li, Tarlok Singh. "Does gold–
platinum price ratio predict stock returns?
International evidence", International Journal
of Managerial Finance, 2022
Publication

Dinardi, Felipe Bardelli. "Forecasting the Stock

217
Market Using ARIMA and ARCH/GARCH < 1%
Approaches", Universidade NOVA de Lisboa
(Portugal), 2024
Publication

Elsaied, Mayada. "Developing and Forecasting

218
the Egyptian Construction Cost Index", The < 1%
American University in Cairo (Egypt), 2024
Publication
219 Fithri Atika Ulpa. "Causality Analysis Between
Exchange Rate, Current Balance Sheet,
<1%
Inflation, and Gross Domestic Product in
ASEAN-5 1980-2022", International Journal
of Finance Research, 2024
Publication

<1%
220 Kamaralzaman, Surianor. "Market Integration
and International Portfolio Diversification
from Malaysian Perspective", University of
Malaya (Malaysia), 2023
Publication

<1%
221 Lutz Kilian. "Not All Oil Price Shocks Are Alike:
Disentangling Demand and Supply Shocks in
the Crude Oil Market", American Economic
Review, 2009
Publication

Md. Abu Hanif, Zobayer Ahmed, Hakan Acet,

222
Savaş Çevik. "WITHDRAWN: Investigating <1%
Okun’s Law in SAARC Countries: An ARDL
Approach", Research Square Platform LLC,
2020
Publication

Mosab I. Tabash, Umar Farooq, Samir K. Safi,

223
Muhammad Nouman Shafiq. "Nexus Between <1%
Macroeconomic Factors and Economic
Growth in Palestine: An Autoregressive
Distributed Lag Approach", Springer Science
and Business Media LLC, 2021
 Publication

224
Ramkishen S. Rajan. "Exchange Rates and
Foreign Direct Investment in Emerging Asia -
<1%
Selected issues and policy options",
Routledge, 2013
Publication

<1%
Robert B Barsky, Lutz Kilian. "Oil and the
225
Macroeconomy Since the 1970s", Journal of
Economic Perspectives, 2004
Publication

<1%
Sainath A R, Gnanendra M, Mohanasundaram
226
T, Leena James, Sheelan Misra. "Dynamic
Connectedness and Volatility Spillover Effects
of Indian Stock Market with International
Stock Markets: An Empirical Investigation
using DCC GARCH", Scientific Papers of the
University of Pardubice, Series D: Faculty of
Economics and Administration, 2023
Publication

Shahid Ahmed. "Foreign Direct Investment,

227
Trade and Economic Growth - Challenges and <1%
Opportunities", Routledge India, 2014
Publication

Wang, Yudong, Chongfeng Wu, and Li Yang.

228
"Oil price shocks and stock market activities: <1%
Evidence from oil-importing and oil-exporting
countries", Journal of Comparative
Economics, 2013.
 Publication

229
docplayer.gr
Internet Source <1%
230
docs.neu.edu.tr
Internet Source <1%
231
espace.curtin.edu.au
Internet Source <1%
232
ulspace.ul.ac.za
Internet Source <1%
233
ActEd
Publication <1%
234
Allen Webster. "Introductory Regression
Analysis - With Computer Application for
<1%
Business and Economics", Routledge, 2013
Publication

<1%
Andrew C.. "Chapter 3 A State-of-the-Art
235
Review of Finance Research in Physical and
Financial Trading Markets in Crude Oil",
IntechOpen, 2012
Publication

<1%
Arshdeep Singh, Kashish Arora, Suresh
236
Chandra Babu. "Examining the impact of
climate change on cereal production in
India: Empirical evidence from ARDL
modelling approach", Heliyon, 2024
Publication
237 Baharudin, Azfar Hilmi. "An Empirical
Investigation into Malaysia's Economic
<1%
Growth: Income Inequality and Foreign
Direct Investment", University of Malaya
(Malaysia), 2023
Publication

<1%
238 Dennis Bergmann, Declan O’Connor, Andreas
Thümmel. "An analysis of price and volatility
transmission in butter, palm oil and crude oil
markets", Agricultural and Food Economics,
2016
Publication

<1%
239 Dlamini, Thembumenzi Nokwanda.
"Measuring the Impact of Swaziland's Import
Licensing and Price-Setting Policy on Price
Dynamics Between South African and
Swaziland Maize Markets", University of
Pretoria (South Africa), 2023
Publication

Ishaan Dawar, Anupam Dutta, Elie Bouri,

240
Tareq Saeed. "Crude oil prices and clean <1%
energy stock indices: Lagged and asymmetric
effects with quantile regression",
Renewable Energy, 2021
Publication

Islam Abdelbary, Rasha ELshawa. "Economic

241
Sanctions as a Foreign Policy Tool: A Case <1%
 Study of the Iran-West Conflict", Springer
Science and Business Media LLC, 2023
Publication

242
Jawwad Ahmed Farid. "Models at Work",
Springer Science and Business Media LLC,
<1%
2014
Publication

<1%
Jitka Sirohi, Zuzana Hloušková, Klára
243
Bartoňová, Karel Malec, Mansoor Maitah,
Robert Koželský. "The Vertical Price
Transmission in Pork Meat Production in the
Czech Republic", Agriculture, 2023
Publication

McKinney, Steven B.. "Implicit Person

244
Theories and Merchant Careers: How IPT <1%
Influences Mentoring Within the Retail
Industry", Iowa State University, 2023
Publication

Nan Tao, Tiantian Wu, Guo Yan. "To the test of

245
economic recovery: The swings in energy <1%
resource prices", Resources Policy, 2024
Publication

Nanaeva, Zhamal. "Navigating Finance in the

246
Metaverse: A Series of Essays on Emerging <1%
Virtual Market With Insights for Islamic
Finance", Hamad Bin Khalifa University
(Qatar), 2024
Publication
247 Papachrysanthou, Chrysanthos. "How Has
the Economic Crisis as a Result of COVID-19
< 1%
Pandemic Affected the Performance of Listed
Stocks: A Panel Data Analysis on UK and USA
Stock Market With Evidence for the Pre-
COVID-19 and COVID-19 Period", European
University of Cyprus (Cyprus), 2024
Publication

< 1%
248 Perry Sadorsky. "Oil price shocks and stock
market activity", Energy Economics, 1999
Publication

< 1%
249 Prakash, Baria Bhagirath. "Exchange Rate
Pass Through in India", Maharaja Sayajirao
University of Baroda (India), 2024
Publication

Qiang Ji, Ying Fan. "Dynamic integration of

250
world oil prices: A reinvestigation of < 1%
globalisation vs. regionalisation", Applied
Energy, 2015
Publication

Saboin Garcia, Jose Luis. "Essays on

251
Hyperinflation, Seigniorage and Fiscal < 1%
Voracity", George Mason University, 2024
Publication

Sara Ali Alokley, Sawssen Araichi, Gadir

252
Alomair. "Exploring the Relationship and < 1%
Predictive Accuracy for the Tadawul All Share
 Index, Oil Prices, and Bitcoin Using Copulas
and Machine Learning", Energies, 2024
Publication

253
Shao, Wen. "An Empirical Analysis of the
Effects of Technology, Finance, Education and
<1%
Labor on Rural Economic Development",
Temple University, 2023
Publication

<1%
Shuang Wang, Lihong Yang. "Mineral
254
resource extraction and resource
sustainability: Policy initiatives for
agriculture, economy, energy, and the
environment", Resources Policy, 2024
Publication

Terseer Anthony MAKAR, Ayila NGUTSAV,

255
Victor Ushahemba IJIRSHAR, Joyce Mbakosun <1%
AYAGA. "IMPACT OF CORRUPTION ON
ECONOMIC GROWTH: AN EMPIRICAL
EVIDENCE FROM NIGERIA", Journal of Public
Administration, Finance and Law, 2023
Publication

Yezhou Sha, Susan Sunila Sharma. "Research

256
on Pandemics - Lessons from an Economics <1%
and Finance Perspective", Routledge, 2021
Publication

tnsroindia.org.in
257 Internet Source <1%
258 www.nrb.org.np
Internet Source < 1%
259 "Global Stock Markets and Portfolio
Management", Springer Science and Business
< 1%
Media LLC, 2006
Publication

< 1%
260 A. K. Giri, Pooja Joshi. "The Impact of
Macroeconomic Indicators on Indian Stock
Prices: An Empirical Analysis", Studies in
Business and Economics, 2017
Publication

< 1%
261 Alex Khang, Rashmi Gujrati, Hayri Uygun, R.
K. Tailor, Sanjaya Singh Gaur. "Data-Driven
Modelling and Predictive Analytics in Business
and Finance - Concepts, Designs,
Technologies, and Applications", CRC Press,
2024
Publication

Andrew Adewale Alola, Festus Victor Bekun,

262
Uju Violet Alola. "Economic Trends and < 1%
Sustainable Environmental Assessment", CRC
Press, 2024
Publication

Aviral Kumar Tiwari, Bibhuti Ranjan Mishra,

263
Sakiru Adebola Solarin. "Analysing the < 1%
spillovers between crude oil prices, stock
 prices and metal prices: The importance of
frequency domain in USA", Energy, 2021
Publication

264
Bernice Nkrumah-Boadu, George Tweneboah,
Siaw Frimpong. "On the partial impact of
< 1%
uncertainties on the nexus between
macroeconomic fundamentals in West
Africa", Heliyon, 2024
Publication

< 1%
Broadstock, David C., Hong Cao, and Dayong
265
Zhang. "Oil shocks and their impact on
energy related stocks in China", Energy
Economics, 2012.
Publication

Jun Wang, Huopo Pan, Fajiang Liu.

266
"Forecasting Crude Oil Price and Stock Price < 1%
by Jump Stochastic Time Effective Neural
Network Model", Journal of Applied
Mathematics, 2012
Publication

Lutz Kilian. "Exogenous Oil Supply Shocks:

267
How Big Are They and How Much Do They < 1%
Matter for the U.S. Economy?", Review of
Economics and Statistics, 2008
Publication

Mustapha, Rafiu Ayobanji. "Determinants of

268
Financial Depth in Nigeria: A Disaggregated < 1%
 Analysis", Kwara State University (Nigeria),
2023
Publication

269
Naifar, Nader, and Mohammed Saleh Al
Dohaiman. "Nonlinear analysis among crude
<1%
oil prices, stock markets' return and
macroeconomic variables", International
Review of Economics & Finance, 2013.
Publication

<1%
Ramesh Chandra Das. "Optimum Size of
270
Government Intervention - Emerging
Economies and Their Challenges", Routledge,
2021
Publication

Santosh Kunwar, Sunil Nepal. "Government

271
Expenditure and Economic Growth of Nepal", <1%
The Lumbini Journal of Business and
Economics, 2024
Publication

Shuddhasattwa Rafiq, Ruhul Salim. "Does oil

272
price volatility matter for Asian emerging <1%
economies?", Economic Analysis and Policy,
2014
Publication

Zaouali, Safa. "The Financial Contagion

273
Between Developed and Emerging Countries <1%
with us Market : an Analysis Using Nardl
 Models", Instituto Politecnico de Braganca
(Portugal), 2024
Publication

274
Asad-Uz-Zaman, Mohammad. "Does
Government Expenditure Affect Growth and
< 1%
Human Development? Evidence from
Bangladesh", The University of Manchester
(United Kingdom), 2024
Publication

< 1%
David Mhlanga, Mufaro Dzingirai.
275
"Responsible Business and Sustainable
Development - The Use of Data and Metrics in
the Global South", Routledge, 2024
Publication

Filis, G.. "Dynamic correlation between stock

276
market and oil prices: The case of oil- < 1%
importing and oil-exporting countries",
International Review of Financial Analysis,
201106
Publication

Indranarain Ramlall. "Economics and Finance

277
in Mauritius", Springer Science and Business < 1%
Media LLC, 2017
Publication

International Journal of Energy Sector

278
Management, Volume 6, Issue 4 (2014-09-16) < 1%
Publication
279 Mutawakil M. Zankawah, Chris Stewart.
"Measuring the volatility spill-over effects of
<1%
crude oil prices on the exchange rate and
stock market in Ghana", The Journal of
International Trade & Economic Development,
2019
Publication

<1%
280 Saba, Charles Shaaba. "Essay on Military
Expenditure, Industrialisation and Economic
Growth in Africa", University of Johannesburg
(South Africa), 2021
Publication

<1%
281 Souček, Michael. "Crude oil, equity and gold
futures open interest co-movements", Energy
Economics, 2013.
Publication

de Abreu, Eva. "Examining the Influence of

282
Foreign Direct Investment on Economic <1%
Growth in South Africa", University of
Pretoria (South Africa), 2023
Publication

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