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Journal articles on the topic 'Nifty returns'

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

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1

Dharani, M. "Seasonal Anomalies between S&P CNX Nifty Shariah Index and S&P CNX Nifty Index in India." Journal of Social and Development Sciences 1, no. 3 (2011): 101–8. http://dx.doi.org/10.22610/jsds.v1i3.633.

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The present study compares the risk and return of the Nifty Shariah index and Nifty index at days, months and quarters wise during the period 2nd January 2007 to 31st December 2010. The raw returns of the both indices are calculated as today price minus yesterday price divided by yesterday price. The t- test has been used to test the mean returns difference between both indices. The average Monday return of the Nifty Shariah index is compared with average return of the Nifty index by using two sample t-test. Like that, the average returns of the remaining of the days of Nifty Shariah index are

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2

Narayan, Parab, and Y. V. Reddy. "Exploring the Causal Relationship Between Stock Returns, Volume, and Turnover across Sectoral Indices in Indian Stock Market." Metamorphosis: A Journal of Management Research 16, no. 2 (2017): 122–40. http://dx.doi.org/10.1177/0972622517730140.

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The traditional saying “Market Discounts Everything” is applicable to stock returns, trading volume, and turnover as well. The present study is an analytical attempt to examine the causal relationship between stock returns, trading volume, and turnover across 10 sectoral indices of National Stock Exchange (NSE) for the period 2006–2016. To critically examine this relation, the study uses various statistical techniques such as descriptive statistics, correlation analysis, regression analysis, and econometric tests such as Granger causality test and augmented Dickey–Fuller test. The required ana

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3

Mr, Jonnalagadda Anil Kumar*1 &. Dr. Bijaya Kumar Barik2. "A COMPARATIVE ANALYSIS OF PERFORMANCE OF SELECT LARGE CAP EQUITY AND INDEX MUTUAL FUND SCHEMES IN INDIA." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY 9, no. 5 (2020): 289–301. https://doi.org/10.5281/zenodo.3870477.

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The present study investigates the past performance of open-ended, growth-oriented, direct plans of large cap equity and index schemes for 1 year, 3 years and 5 years period. S&P BSE 100 and NIFTY 50 were used as Benchmark indices for Large Cap Equity and Index Schemes, respectively. The historical performance of the selected schemes was evaluated based on Weighted Average Return, Mean, Standard Deviation, Alpha, Beta, Sharpe, Tracking Error and Coefficient of Determination (r<sup>2</sup>); the results of the study will be useful to investors in taking better investment decisions. The retu

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4

Mishra, Ravi Ranjan, and Shirish Mishra. "Asymmetric Effects and Volatility Clustering in NSE NIFTY 50: A Comparative Analysis of GARCH Models." Asian Journal of Economics, Business and Accounting 24, no. 11 (2024): 142–52. http://dx.doi.org/10.9734/ajeba/2024/v24i111547.

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This study aims to analyze the volatility patterns, Clustering, and asymmetric effects in the NSE NIFTY 50 index. It involves using daily returns data from the NSE NIFTY 50 from 01 Jan 2010 to 31 Dec 2023. Daily closing prices are obtained from the official NSE website, and returns are calculated based on these prices. EGARCH (1, 1), TARCH (1, 1), GARCH (1, 1), GARCH-M (1,1), and models are utilized to predict volatility, capturing volatility clustering and leverage effects. Using both the Akaike and Schwarz criteria, EGARCH (1,1) was demonstrated to be the best model. The findings reveal that

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P.R, Roshni, and E. Sulaiman. "PERFORMANCE OF NIFTY 50 EXCHANGE TRADED FUNDS." International Journal of Advanced Research 9, no. 02 (2021): 77–83. http://dx.doi.org/10.21474/ijar01/12420.

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The study evaluated the performance of selected Nifty 50 ETFs tracking Nifty 50 Index listed in National Stock Exchange in India during a period of six years starting from 1st April, 2014 to 31st March, 2020. The performance of ETFs is measured using Average Daily Returns, CAGR, HPR, Standard Deviation, Tracking Error, R squared and Beta. It is found that there is difference in the risk-return pattern of Nifty 50 ETFs and its index Nifty 50. Aditya Birla Nifty ETF is the performing fund among the selected ETFs.

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6

Dharani, M. "Equanimity of Risk and Return Relationship between Shariah Index and General Index in India." Journal of Economics and Behavioral Studies 2, no. 5 (2011): 213–22. http://dx.doi.org/10.22610/jebs.v2i5.239.

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The present study empirically examines the risk and return of the Nifty Shariah index and Nifty index during the period 2nd January 2007 to 31st December 2010. The sample period is further divided into bull market period and bear market period based on the movement of the both indices during the study period. The objective of the study is to analyse the performance of the Islamic index and common index and to test whether any significant difference between both indices in India. Based on the previous studies, the present paper employs Risk adjusted measurement such as Sharpe index, Treynor Ind

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7

Pranchana, R., S. Sudhamathi, and S. Benneet. "Evaluating the Impact of Sectoral Indices on Stock Market Performance in the National Stock Exchange." Indian Journal of Information Sources and Services 15, no. 1 (2025): 238–43. https://doi.org/10.51983/ijiss-2025.ijiss.15.1.30.

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Economic growth can be measured by the stock market index industry survey, which measures the key indicators of a country's economic development. Furthermore, analyzing various indicators assists governments and investors in using them as a reference. This paper aims to explore the capital market efficiency of the NSE sector indexes by analyzing daily stock price returns. The study seeks to evaluate the effectiveness of the weak form of the selected indicators listed in the NSE. The paper will assess market efficiency by utilizing series and autocorrelation tests and testing the selected NSE i

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Gangwani, Mayank, and Dhun Sehrawat. "Covid-19-A Baleful Aftermath for the Stocks of Indian Pharmaceutical Companies." International Journal of Science, Engineering and Management 9, no. 9 (2022): 21–31. http://dx.doi.org/10.36647/ijsem/09.09.a004.

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Covid-19 catastrophe has not spared any market across the world due to widespread disruptions in its supply chain operations. In today's world, however, stock markets serve as a catalyst for a country's economic and financial development. But, with the development of Covid-19 infection and widespread lockdown in the majority of countries, its stock market has plummeted even further into the depths. Therefore, to determine whether the Covid-19 outbreak has impacted the expected return of Nifty Pharma and stock return of 3 leading pharmaceutical companies Cipla, Dr. Reddy's, and Sun Pharma in th

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9

Chittineni, Jyothi. "The Impact of COVID-19 Pandemic on the Relationship between India’s Volatility Index and Nifty 50 Returns." Indian Journal of Finance and Banking 4, no. 2 (2020): 58–63. http://dx.doi.org/10.46281/ijfb.v4i2.731.

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The paper intends to re-examine the relationship between India’s Implied Volatility Index (IVIX) and Nifty 50 Returns during this COVID-19 pandemic. The study results are important for two reasons, one is to understand whether Indian VIX is fulfilling the purpose of measuring the near future volatility of Nifty 50 during this pandemic, and secondly, it reports the impact of COVID-19 on the investors’ perceptions about the returns and its volatility. The study results documented that the Nifty return and IVIX are moving independently during the COVID-19 pandemic and there is no association betw

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10

Kumar, Pushpender, Noella Nazareth, and Harsh Pratap Singh. "Do Monetary Policy Announcements Affect Stock Market Performance: Evidence from Emerging Economy." Journal of Commerce and Accounting Research 14, no. 4 (2025): 65–76. https://doi.org/10.21863/jcar/2025.14.4.007.

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This study aims to examine the effect of monetary policy announcements on returns in the Indian stock market. An event study methodology is employed to evaluate the influence of such announcements. The research utilises daily time series data from broad market indices like the Nifty 50, Nifty 100, Nifty 200, and Nifty 500 to represent the Indian stock market, alongside sectoral indices including Nifty Auto, Nifty Bank, Nifty Financial Services, Nifty FMCG, Nifty IT, Nifty Media, Nifty Metal, Nifty Pharma, Nifty Private Bank, Nifty PSU Bank, and Nifty Realty. The results reveal that a reduction

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Pushkar Dilip Parulekar. "Systematic Investment Plan vs. Lumpsum Investment: A Comparative study across Time and Indexes." Communications on Applied Nonlinear Analysis 32, no. 8s (2025): 362–82. https://doi.org/10.52783/cana.v32.3681.

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Introduction: SIP is based on the logic of rupee cost averaging wherein regular periodic investments are made (generally monthly) as LI which means one time investment There is always a debate between active and passive investing. Even though some active investors might outperform passive investors, there will be balancing underperformers as well. Considering transaction cost and risk adjusted returns passive investors tend to outperform the active investors over the longer time horizon. Objectives: This paper compares success of two popular methods of passive investing that could be used by r

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12

Rabia, Najaf, and Najaf Khakan. "A STUDY OF EXCHANGE RATES MOVEMENT AND STOCK MARKET VOLATILITY." International Journal of Research – Granthaalayah 4, no. 1 (2017): 70–79. https://doi.org/10.5281/zenodo.848175.

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In this paper we have analyzed the relationship between Indian rupess-USdollar exchange rate and Nifty returns. This research is based on dynamic behavior between stock markets movement and volatility of stock market for this purpose; we have applied several statistical tests. .we have taken the data from period of October 2008, to march, 2010.It study has proved that exchange rate and Nifty returns are non-normally disturbed. Unit root tests have proved that Nifty returns and exchange rate are stationary and they are stationary at level form. There is negative relationship between exchange ra

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13

Valluri, Venkata Rao, and Ravi Kumar. "A Sector-Wise Risk-Adjusted Return Analysis of Selected Indian Stocks." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 07 (2025): 1–9. https://doi.org/10.55041/ijsrem51346.

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This study analyses the return, risk, and Sharpe Ratio of selected stocks from three major sectors of the Indian economy — Information Technology (IT), Pharmaceuticals, and Oil & Gas — over the period 2015 to 2024. Using annual data, the research evaluates the performance of Infosys, TCS, Nifty IT; Dr. Reddy, Sun Pharma, Nifty Pharma; and Reliance Ltd, Indian Oil, Nifty Oil & Gas. The Sharpe Ratio is employed to measure risk-adjusted returns, considering a risk-free rate of 6%. Among IT stocks, TCS showed the highest Sharpe Ratio (0.53), indicating better efficiency. In the pharmaceuti

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14

Babu, Manivannan, A. Antony Lourdesraj, C. Hariharan, et al. "Dynamics of Volatility Spillover between Energy and Environmental, Social and Sustainable Indices." International Journal of Energy Economics and Policy 12, no. 6 (2022): 50–55. http://dx.doi.org/10.32479/ijeep.13482.

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The purpose of this research was to examine the dynamics of volatility spillover between energy and environmental, social, and sustainable indices. COVID19 prompted the research to select April 2019 to March 2022 as a sample period, and the respective data (Daily Prices) of the Nifty Energy and Nifty ESG indices were obtained from the National Stock Exchange of India Limited. The outcomes of the study confirmed that the daily returns of Nifty Energy and Nifty 100 ESG indices were not normally distributed and reached stationarity at level difference. Further, the study employed GARCH Models suc

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15

Chellaswamy, Karthigai Prakasam, Natchimuthu N., and Muhammadriyaj Faniband. "Chinese and Indian Stock Markets: Linkages and Interdependencies." Research in World Economy 12, no. 2 (2021): 228. http://dx.doi.org/10.5430/rwe.v12n2p228.

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This paper examines the stock market linkages and interdependencies between China and India. We use the quantile regression approach as an alternative to Ordinary Least Squares estimation due to its flexibleness and robustness. Our results of the entire time period reveal the influence of Chinese CPI and ER on Nifty returns is not the same across the different quantiles. However, Chinese IR has no impact on Nifty returns. Further, Indian CPI has a negligible effect on SSE returns. In contrast, IR and ER do not affect SSE returns. This study also observes that the dependence structure between C

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Dr K Sridevi and Adakankar Pashupathinath. "Comparative Risk-Return Analysis of Cryptocurrencies and Indian Stock Indices: Insights for Investors in Emerging and Traditional Markets." International Journal of Latest Technology in Engineering Management & Applied Science 14, no. 5 (2025): 1041–50. https://doi.org/10.51583/ijltemas.2025.140500111.

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Abstract: This study examines the risk-return profile of Cryptocurrencies compared to Indian stock Indices, BSE Sensex and Nifty 50, to identify their unique investment characteristics. By analysing data from ten major Cryptocurrencies alongside Sensex and Nifty 50, the study applies statistical measures, including mean, variance, skewness, kurtosis, Jarque-Bera (JB) test, two-sample t-test, ANOVA test and Tukey HSD test. Findings reveal that Cryptocurrencies offer higher returns but are significantly more volatile, while Indian Stock Indices provide moderate, stable returns with implications

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Ms., B. Kishori, and Sangavi S. "Impact of Demonetisation on Indian Stock Market: with special referance to NSE." RESEARCH REVIEW International Journal of Multidisciplinary 03, no. 06 (2018): 146–49. https://doi.org/10.5281/zenodo.1285875.

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Demonetization is an act of seizing a currency unit of its status as legal tender. Demonetization is necessary whenever there is a need to change national currency. The government claimed that the action would “curtail the shadow economy and crack down on the use of illicit and counterfeit cash to fund illegal activity and terrorism”. The Objectives of the study were (a) to measure the returns of the NIFTY 50 stocks, pre and post demonetisation, using BETA(b)to find the expected returns of the selected stocks pre and post demonetisation, using ANOVA model and (c) to study the impac

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18

Anchan, Veerendra. "Factors Affecting NIFTY 50 and its Returns." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 07, no. 12 (2023): 1–11. http://dx.doi.org/10.55041/ijsrem27529.

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The key objective of the present study is to explore the impact of different macroeconomic variables on the stock prices in India using annual data from 2014-15 to 2022-23. A multiple regression model is designed to test the effects of macroeconomic variables on the stock prices and granger causality test is conducted to examine whether there exists any causal linkage between stock prices and macro-economic variables. The project will use a variety of methods to analyze the impact of these factors on Nifty returns. These methods may include regression analysis, seasonality regression, Johnasen

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19

Paul, Parmod Kumar, Om Prakash Mahela та Baseem Khan. "Analyzing the Association between Pattern and Returns Using Goodman–Kruskal Prediction Error Reduction Index (λ)". Complexity 2022 (15 січня 2022): 1–8. http://dx.doi.org/10.1155/2022/8196436.

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For selecting and interpreting appropriate behaviour of proportion between buy/neutral/sell patterns and high/moderate/low returns, the prediction error reduction index is a very useful tool. It is operationally interpretable in terms of the proportional reduction in error of estimation. We first obtain the buy/sell pattern using an Optimal Band. The analysis of the association between patterns and returns is based on the Goodman–Kruskal prediction error reduction index ( λ ). Empirical analysis suggests that the prediction of returns from patterns is more impressive or of less error as compar

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20

Kotha, Kiran Kumar, and Shreya Bose. "Dynamic Linkages between Singapore and NSE listed NIFTY Futures and NIFTY Spot Markets." Journal of Prediction Markets 10, no. 2 (2017): 1–13. http://dx.doi.org/10.5750/jpm.v10i2.1253.

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This study examines the dynamic linkages of Nifty stock index and Nifty index futures contract traded on the home market, National Stock Exchange (NSE) and on the off-shore market, Singapore Stock Exchange (SGX). The study uses daily closing prices of the Nifty index and the Nifty futures contract traded on both the exchanges for the period July 15, 2010 to July 15, 2016. The study finds a causality running from the returns of the spot market to the returns from the Nifty futures market in both the exchanges, NSE and SGX, with the help of Vector Error Correction model and Granger causality tes

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Mulimani, Mr Chidanand M. "A Study on Analysing Risk and Return Profiles of Top Two Companies in Nifty 50." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 10 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem37975.

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This study conducts a comparative analysis of the risk and return profiles of two leading software companies in the Nifty 50 index, Tata Consultancy Services (TCS) and Infosys, over the period from 2019 to 2024. The analysis aims to provide insights into the historical returns, volatility, and risk-adjusted performance of these companies using financial metrics such as standard deviation, beta, and alpha. Through hypothesis testing, the study evaluates correlations between risk and return, examining both companies’ sensitivity to market conditions. Findings indicate that while both firms offer

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D Shah, Dr Manita. "Predicting Bank Nifty Movements Based on ICICI, HDFC, and Axis Bank Returns." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 11 (2024): 1–8. http://dx.doi.org/10.55041/ijsrem38568.

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This study investigates the link between the returns of ICICI Bank, HDFC Bank, and Axis Bank and the overall performance of the Bank Nifty index, which is a crucial measure of the Indian banking sector's health on the National Stock Exchange. Using five years of historical data, regression analysis and descriptive statistics evaluate trends, correlations, and prediction accuracy in anticipating Bank Nifty returns based on the performance of these large banks. The study finds that while Bank Nifty displays stability as it aggregates multiple bank stocks, individual banks like Axis Bank and HDFC

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Mahato, Pankaj Kumar. "An event study analysis of the impact of bonus share announcements on Nifty 100 and Nifty Midcap 100 companies." International Journal of Accounting, Business and Finance 2, no. 1 (2022): 14–30. http://dx.doi.org/10.55429/ijabf.v2i1.90.

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This study examines how the large-cap and mid-cap firms listed on the National Stock Exchange responded to bonus share announcements between January 1, 2006, to September 30, 2022. The conventional event study approach has been utilized, along with the commonly used market model assessment of predicted returns to analyze 45 pure events during this period consisting of 20 events of large-cap and 25 events of midcap stocks. According to the analysis, stock values significantly changed around the time of occurrence. Announcements of stock dividends typically increase stock prices. The mean of ave

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Kumar, S. S. S. "Sensex and Nifty Indices: Are They the Right Benchmarks for Mutual Funds in India?" Jindal Journal of Business Research 7, no. 1 (2018): 1–12. http://dx.doi.org/10.1177/2278682118761686.

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Recently two significant developments took place in the Indian capital markets: (a) SEBI’s decision making it mandatory for all mutual funds to disclose the scheme returns against a common benchmark index such as Nifty or Sensex and (b) Employee’ Provident Fund Organisation (EPFO) is permitted to invest a part of their funds into stock market through the exchange-traded fund (ETF) route, particularly SBI Sensex and SBI Nifty ETFs. Both the developments are tied by a common concept that stock market indices such as Nifty and Sensex are passive without any statistically significant alpha. In the

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A., Kadakia,, and Gupta, P. "Establishment of Portfolio Based On Momentum Strategy and Analyzing the Factors Affecting the Portfolio Returns." CARDIOMETRY, no. 24 (November 30, 2022): 708–17. http://dx.doi.org/10.18137/cardiometry.2022.24.708717.

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For many years, momentum strategy for investment in stocks is being investigated, which suggests that investing in the stocks in momentum generally generates excessive returns. The study explores establishing the portfolio based on the momentum strategy adopting the methodology of Jegadeesh and Titman with minor modification. Building on Indian data from the National Stock Exchange, stocks of Index Nifty 50, and Next Nifty from January 2010 to December 2019, this paper analyzes the return to see the effectiveness of momentum strategy. The stocks in the portfolio are included based on defined c

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Krishnan, Prema, and M. N. Periasamy. "Testing of Semi–Strong Form of Efficiency: an Empirical Study on Stock Market Reaction Around Dividend Announcement." International Journal of Professional Business Review 7, no. 2 (2022): e0483. http://dx.doi.org/10.26668/businessreview/2022.v7i2.483.

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Purpose: The purpose of this study is to examine the efficiency of the Indian stock market of the Nifty IT index over the dividend announcement for five years from 2016 to 2020. Theoretical framework: A reward procured by the shareholders on their equities is, of course, the dividend. A leading area of concern is the dividend announcement. According to the theory of efficient markets, stock prices accurately reflect all available information. This demonstrates that the prices are correct and fair. The market should therefore respond immediately to an event in this instance the dividend announc

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Ashri, Dhananjay, Bibhu Prasad Sahoo, Ankita Gulati, and Irfan UL Haq. "Repercussions of COVID-19 on the Indian stock market." Linguistics and Culture Review 5, S1 (2021): 1495–509. http://dx.doi.org/10.21744/lingcure.v5ns1.1792.

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The present paper determines the repercussions of the coronavirus on the Indian financial markets by taking the eight sectoral indices into account. By taking the sectoral indices into account, the study deduces the impact of virus outbreak on the various sectoral indices of the Indian stock market. Employing Welch's t-test and Non-parametric Mann-Whitney U test, we empirically analysed the daily returns of eight sectoral indices: Nifty Auto, Nifty FMCG, Nifty IT, Nifty Media, Nifty Metal, Nifty Oil and Gas, Nifty Pharma, and Nifty Bank. The results unveiled that pandemic had a negative impact

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Sujata, Suvarnapathaki. "Examining the Distributional Characteristics of Daily Returns of Nifty 50: Normality Assessment and Implications." International Journal of Current Science Research and Review 07, no. 05 (2024): 2781–85. https://doi.org/10.5281/zenodo.11189808.

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Abstract : This paper investigates the distributional characteristics of daily returns of the Nifty 50 index, a benchmark index comprising 50 large-cap stocks traded on the National Stock Exchange of India. Utilizing historical data spanning a specified time period, we conduct normality testing to assess the adequacy of the normal distribution assumption underlying many financial models. Our analysis provides insights into the departure from normality. As a result of departure from Normality, it may affect the tail behaviour, and volatility dynamics of Nifty 50 daily returns, offering implicat

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Kumar Digal, Sabat, Yashmin Khatun, and Braja Sundar Seet. "COVID-19 Impact on Nifty Banks: An Event Study Methodology." Journal of International Business and Economy 22, no. 1 (2020): 83–108. http://dx.doi.org/10.51240/jibe.2021.1.4.

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The financial sector, because of its catalytic role in the economy, has always been in the eye of the storm in economic difficulties. Due to the pandemic, the stock market had lost about 27 percent by April 2020 and bank nifty has had a lion’s share in pushing the index down to this level. Uncertainty arose as the containment of the disease and the availability of vaccines remain uncertain; this contributed to the plunge in investor confidence. Because of the central role of banks in the development initiatives of the governments, COVID-19 has become a significant threat to the sustainability

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Mamilla, Rajesh, Chinnadurai Kathiravan, Aidin Salamzadeh, Léo-Paul Dana, and Mohamed Elheddad. "COVID-19 Pandemic and Indices Volatility: Evidence from GARCH Models." Journal of Risk and Financial Management 16, no. 10 (2023): 447. http://dx.doi.org/10.3390/jrfm16100447.

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This study examines the impact of volatility on the returns of nine National Stock Exchange (NSE) indices before, during, and after the COVID-19 pandemic. The study employed generalized autoregressive conditional heteroskedasticity (GARCH) modelling to analyse investor risk and the impact of volatility on returns. The study makes several contributions to the existing literature. First, it uses advanced volatility forecasting models, such as ARCH and GARCH, to improve volatility estimates and anticipate future volatility. Second, it enhances the analysis of index return volatility. The study fo

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Siddiqui, Saif, and Preeti Roy. "Predicting Volatility and Dynamic Relation Between Stock Market, Exchange Rate and Select Commodities." Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis 67, no. 6 (2019): 1597–611. http://dx.doi.org/10.11118/actaun201967061597.

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Commodities play a vital role in the development of emerging economies, like India. From this perspective, the study presents dynamic correlation in the prices of gold, crude oil, exchange rate and Indian stock market from April 01, 2014 to March 28, 2018. VARMA-BEKK-GARCH model is estimated for return and volatility spillovers across markets. Bidirectional returns spillover was found between Nifty and WTI and WTI and Gold pair. Whereas the bidirectional volatility spillover between Nifty and Gold pair. From the DCC-GARCH correlational analysis, Gold was found to be effective hedging commodity

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Vikram, Debasis Mohanty, and Archa Agrawal. "An Empirical Study on the Impact of FII and DII on Volatility, Leverage and Long-Term Returns of the Indian Stock Index." Asian Journal of Economics, Business and Accounting 25, no. 4 (2025): 131–37. https://doi.org/10.9734/ajeba/2025/v25i41739.

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Estimating volatility is the key factor to be analyzed in taking the financial decisions. Financial strategies are framed after due investigation of financial market volatility. This study examines the impact of foreign institutional investment (FII) & Domestic Institutional investment (DII) in Indian stock market and analyses the volatility of National Stock Exchange (NSE) categorical indices for the period of 10 years from 20th February 2014 to 20th February 2024. The study is conducted using the logarithmic return of series of Nifty 50, Nifty Midcap 50 & Nifty Small Cap 50. GARCH (1

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Krishna Sharma Raavinuthala, Satya, Girish Jain, and Gokulananda Patel. "Spillovers across global stock markets before and after the declaration of Russia’s invasion of Ukraine." Investment Management and Financial Innovations 21, no. 2 (2024): 130–43. http://dx.doi.org/10.21511/imfi.21(2).2024.10.

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Since the financial meltdown, studies on systemic risk and financial contagion have gained currency. Events like the COVID pandemic and the Russian invasion of Ukraine have fueled such an importance. This study examines the impact of the invasion on volatility transmissions across major stock markets worldwide. The stock indices considered in this study are ASX 200, ESTOXX 40, FTSE 100, HNGSNG, NIFTY 50, NIKKIE, and S&amp;amp;P 500. The work uses Vector Auto Regression (VAR) to study the transmission of returns. Later, the work performs Dynamic Conditional Covariance-Generalized Auto Regre

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Mohanty, Priyakrushna, and Anubha Srivastava. "The Impact of Israel-Hamas War on The Various Sectors of Indian Stock Market." Ushus Journal of Business Management 23, no. 4 (2025): 57–83. https://doi.org/10.12725/ujbm.69.4.

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This study investigates the impact of the Israel-Hamas conflict of October 2023 on the Indian stock indices and sector-based companies with a particular focus on the steel, oil and gas, defence, and pharmaceutical sectors. Employing an event study methodology, the research analyses the effects of the conflict on the respective Nifty indices and individual stocks within these critical sectors. The findings unveil a tapestry of sector-specific impacts, ranging from heightened volatility in the Nifty Oil and Gas Index due to surging crude prices to an uptick in the Nifty Defence Index, reflecting

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Dr. Rajani. "Impact of Automobile Companies Stock Returns on Indian Stock Market Indices with Special Reference to Nifty Fifty Index." International Journal of Management and Humanities 10, no. 5 (2024): 31–37. http://dx.doi.org/10.35940/ijmh.e1676.10050124.

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The Nifty Fifty Index has a free-float market capitalization-weighted index.it represents the weighted average of the top 50 Indian companies listed on the National Stock Exchange ,and it is one of the main stock indices being used in India, besides the BSE Sensex of the Bombay Stock Exchange. The Nifty 50 index represents 62% of the free float market capitalization of the stocks listed in the NSE (NATIONAL STOCK EXCHANGE) as on September 30,2022.sectors ‘s stocks are performing more consistently and provide high return with high risk in (NSE)NATIONAL STOCK EXCHANGE ,these stocks are emerging

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Dr., Rajani. "Impact of Automobile Companies Stock Returns on Indian Stock Market Indices with Special Reference to Nifty Fifty Index." International Journal of Management and Humanities (IJMH) 10, no. 5 (2024): 31–37. https://doi.org/10.35940/ijmh.E1676.10050124.

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<strong>Abstract:</strong> The Nifty Fifty Index has a free-float market capitalization-weighted index.it represents the weighted average of the top 50 Indian companies listed on the National Stock Exchange ,and it is one of the main stock indices being used in India, besides the BSE Sensex of the Bombay Stock Exchange. The Nifty 50 index represents 62% of the free float market capitalization of the stocks listed in the NSE (NATIONAL STOCK EXCHANGE) as on September 30,2022.sectors ‘s stocks are performing more consistently and provide high return with high risk in (NSE)NATIONAL STOCK EXC

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Chandy, Jacob. "Index Returns and Institutional Trading." Shanlax International Journal of Management 9, S1-Feb (2022): 218–25. http://dx.doi.org/10.34293/management.v9is1.4863.

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It is acknowledged that only 2% of the Indian public invest in stock markets. This compares with 55% in the USA and about 25% in the EU. The Indian public is therefore a miniscule proportion of investors and the power of the Indian public to move markets is negligible.This means that most trading activity in Indian stock markets are by institutional investors consisting of Foreign Institutional Investors (FIIs) and Domestic Institutional Investors (DIIs). It seems reasonable to hypothesize that their trading activities influence market returns. This paper aims to verify whether this hypothesis

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Kumar, P. Pavan, and Archana H. N. "A Comparative Evaluation of Performance of Nifty IT Companies in Relation with Nifty IT Index." GBS Impact: Journal of Multi Disciplinary Research 8, no. 1 (2022): 25–34. http://dx.doi.org/10.58419/gbs.v8i1.812203.

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The Information Technology sector is central to the nation’s security, economy and public health. It is one of the fastest growing sectors in Indian Stock Market. This paper evaluated the performance of companies listed in Nifty IT index with an objective to find out the significance level of each company with Nifty IT index with the help of paired sample T-test. The study covered five years starting from 1s January 2017 to 31 December 2021. Mean returns and standard deviation is calculated to analyze and compare the risk return characteristics of the companies listed in Nifty IT index. Correl

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Ainapur, Jyoti, Maheshkumar Maharudrappa, Harshavardhan M, et al. "PERFORMANCE MATRIX: COMPARATIVE INSIGHTS INTO NIFTY'S BANKING, IT, FMCG, PHARMA, ENERGY, AND INFRASTRUCTURE SECTORS." International Journal of Research in Commerce and Management Studies 06, no. 05 (2024): 64–85. http://dx.doi.org/10.38193/ijrcms.2024.6504.

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This study presents a comprehensive performance matrix of six key Nifty sectors - Banking, IT, FMCG, Pharma, Energy, and Infrastructure - over the decade spanning 2014-2024. Employing a mixed-methods approach, this research analyzes sector-specific trends, volatility patterns, and yearly returns to provide actionable insights for investors. The findings reveal significant performance differentials, with Nifty IT emerging as the top-performing sector, while Nifty FMCG demonstrates resilience and Nifty Bank exhibits volatility. Statistical analysis and hypothesis testing validate these trends. T

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Parthasarathy, Srikanth. "Impact of the Changes in the Nifty Index Constituents." International Journal of Accounting and Financial Reporting 9, no. 3 (2019): 180. http://dx.doi.org/10.5296/ijafr.v9i3.15320.

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The objective of this study is to conduct an empirical examination of the S&P CNX Nifty index reconstitutions, between 2009 and 2018, focusing on both the price and non-price effects and the explanations surrounding them. The event methodology, with multiple abnormal return computational methods, is employed to improve the robustness and reliability of the results. The results show that the Nifty index additions (deletions) are associated with significant positive (negative) permanent abnormal returns. But the evidence of permanent abnormal volume is limited, unlike the developed markets.

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Panigrahi, Ashok Kumar, Kushal Vachhani, and Suman Kalyan Chaudhury. "Trend identification with the relative strength index (RSI) technical indicator –A conceptual study." Journal of Management Research and Analysis 8, no. 4 (2021): 159–69. http://dx.doi.org/10.18231/j.jmra.2021.033.

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We all must agree that the word "trend" is now the buzzword of the stock market. As a part of investment strategy and analysis, it is always suggested that the investors should keep an eye on medium-term and short-term changes in addition to longer-term (secular) patterns. Traders and investors use the RSI as a momentum indicator. Overbought and oversold situations are indicated by RSI values between 70 and 30. Over the past two decades, several techniques have been developed to analyze NIFTY 50 data for investment purposes. In this paper, we have estimated the returns by looking at the two tr

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Yadav, Rakesh, Ameya Patil, Krishna Sarda, and Makarand Milind Bapat. "Does Contrarian Investing Beat the Conventional Strategies and the Index?" SocioEconomic Challenges 8, no. 2 (2024): 31–43. http://dx.doi.org/10.61093/sec.8(2).31-43.2024.

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Traditional momentum strategies on the stock market are implemented in accordance with the efficient market hypothesis and involve making investments in accordance with market trends. However, this hypothesis has been repeatedly criticized by supporters of behavioral finance, who allow the irrational nature of investment decisions, which led to the emergence of contrarian investment strategies, based on the overreaction hypothesis and the reversal effect (over a longer horizon, loser stocks outperform winners), according to which investments are made in opposite direction to the market, involv

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Dr. Avijit Sikdar. "Study of Association between Volatility Index and Nifty using VECM." International Journal of Engineering and Management Research 11, no. 1 (2021): 200–204. http://dx.doi.org/10.31033/ijemr.11.1.27.

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Volatility in capital markets is the measure degree of variability of stock return from their expected return. The volatility in the capital market is the basis for price discovery in the financial asset. The volatility index (VIX) is the measurement index of the volatility of the capital market. It is the fear index of the capital market. The concept is first coined in 1993 in Chicago Board Options Exchange (CBOE). In India, such an index was introduced in 2008 by NSE. India VIX calculates the expected market volatility over the coming thirty days on Nifty Options. It Market index is the perf

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Singh, Rajdeep, Kanwaljeet Singh, and Prabhjot Kaur. "DYNAMICS OF FOREIGN INSTITUTIONAL INVESTMENTS AND EQUITY RETURNS IN INDIA." International Journal of Research -GRANTHAALAYAH 4, no. 6 (2016): 1–7. http://dx.doi.org/10.29121/granthaalayah.v4.i6.2016.2630.

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India has become a focus point and an attractive hub for foreign investor’s post 199. This international flow of capital was facilitated by increased globalization and the growth of information technology which has blurred national borders. Thus FII flows in India have continuously grown in importance post 1991. This paper examines the trend of FII flow in India from 2001 and 2015 and also examines the relationship between FII and the two important barometers of the Indian stock market, i.e., S&P BSE Sensex and CNX Nifty. The impacts of FII on the proxies for stock market, i.e., Sensex and

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Sehgal, Meru, and Shruti Gupta. "Stock Markets in Changing Times." International Journal of Business Analytics 8, no. 3 (2021): 14–25. http://dx.doi.org/10.4018/ijban.2021070102.

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The impact of COVID-19 on the stock markets of US, UK, and India has been analyzed. Daily market returns of the stock indices (Dow Jones Industrial Average, FTSE-100, Nifty 50 Index, and Nifty Bank Index) have been examined using paired t-test for 40 days before and after the reporting of the first case. Index performance has also been investigated for the quarter ending June 2020 along with comparative performance analysis of the indices with Nifty Bank Index. The results showed that markets have borne substantially negative returns, but they are not statistically significant. This indicates

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Dey, Sanjeeb Kumar, and Debabrata Sharma. "Impact of Corporate Governance on Financial Returns of Indian Listed Companies." SEISENSE Journal of Management 4, no. 4 (2021): 88–99. http://dx.doi.org/10.33215/sjom.v4i4.717.

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Purpose- In this paper, we have evaluated the relationship of corporate governance with companies’ financial returns using return on assets (ROA) and return on capital employed (ROCE) as proxies. For this purpose, companies listed in Nifty-50 are considered as a sample. Design/Methodology- The present study is conducted on the NIFTY-50 Index with a final sample of 35 companies after excluding banking companies, financial services companies, and companies that did not have the required data in the sample period. Data has been collected for ten years from 2009-10 to 2018-19, and they are analyze

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Sangh, Neeraj. "Static Systematic Risk Profile of Nifty 100 Stocks: A Year on Year Analysis of Beta." GIS Business 12, no. 5 (2017): 75–83. http://dx.doi.org/10.26643/gis.v12i5.3346.

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Beta Coefficient, as a measurement statistic of systematic risk of securities, was initially explained by Sharpe as a slope of simple linear regression function using rate of return on a market index as independent variable and a securitys rate of return as dependent variable. National Stock Exchange (NSE), the leading stock exchange of India, practice this ordinary least square (OLS) regression based single index market model for disseminating beta coefficients of prominent NIFTY 100 stocks. OLS regression based index model presumes that beta coefficients of securities should remain stable fo

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R, Dharshan. "Optimizing Portfolio Construction Using Nifty India Manufacturing Index: A Risk-Return Analysis with Python." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 04 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem31211.

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This paper presents a comprehensive analysis of portfolio construction strategies aimed at maximizing risk-adjusted returns for investors. Utilizing historical data on stock returns and risks, a meticulous selection process was employed to identify 15 stocks with superior risk-return profiles. These stocks were chosen based on their outperformance relative to the dataset's average measures, prioritizing returns higher than the dataset average and risks lower than average risk levels. The selected stocks, representing a diverse range of manufacturing-related businesses, formed the cornerstone o

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DR, BHADRAPPA HARALAYYA. "A STUDY ON EMPRICAL ANALYSIS OF RELATIONSHIP BETWEEN FPI AND NIFTY RETURNS." Journal of Advanced Research in Accounting & Finance Management 3, no. 2 (2022): 3–22. https://doi.org/10.5281/zenodo.6253916.

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The study is an attempt to evaluate and analyse the relationship between Foreign Portfolio Investors (FPI) and the Indian stock market returns. With the stable economy, better growth prospects, liberal government policies and many more profitable opportunities. India has become a hot destination for FPI investments. Thus, there is a need to study the impact of these investments on the market returns. Daily data of foreign net investment and Nifty returns, for the period starting from January 2016 to June 2017, has been used for evaluating the presence of feedback trading among the foreign inve

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MAHAJAN, Sarika, and Priya MAHAJAN. "Impact of COVID-19 on Stock Market and Gold Returns in India." Eurasian Journal of Business and Economics 14, no. 27 (2021): 29–46. http://dx.doi.org/10.17015/ejbe.2021.027.02.

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The spread of COVID-19 has caused severe damage to human lives and the global economy. The stock markets around the world have plummeted to their lowest levels since the 2008 Global Financial Crisis. This paper attempts to examine the joint dynamics of gold and stock market returns during unprecedented times of health and financial shock due to COVID-19 between January 2020 and May 2020 using granger test, ARMA model, and symmetric and asymmetric GARCH models to improve the understanding of the microstructure of investment scenario in India. The period considered in the study helps to evaluate

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