Exploring the Causal Relationship Between Stock Returns, Volume, and Turnover across Sectoral Indices in Indian Stock Market

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 analyses have been performed using statistical software E-views, SPSS, and Microsoft Excel. The study noticed a weak positive relationship between stock returns and turnover for Nifty Auto Index, Nifty Bank Index, Nifty Financial Services Index, Nifty Media Index, Nifty Metal Index, and Nifty Private Bank Index. The study also found a significant impact of turnover on stock returns in the case of Nifty Auto Index, Nifty Bank Index, Nifty FMCG Index, Nifty Metal Index, and Nifty Pharma Index and a significant impact of volume on stock returns in the case of Nifty Bank Index, Nifty FMCG Index, and Nifty Pharma Index. Augmented Dickey–Fuller test suggests that there exists no unit root in the data ( p < 1) and the data are stationary. It is evident from the study that the causal relationship between stock returns, turnover, and volume varies across the sectoral indices.

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Do Macroeconomic Variables Impact the Indian Stock Market?

Journal of Commerce and Accounting Research ◽

10.21863/jcar/2016.5.3.031 ◽

2016 ◽

Vol 5 (3) ◽

Author(s):

Khalid Ul Islam ◽

Mohsina Habib

Keyword(s):

Exchange Rate ◽

Stock Market ◽

Stock Returns ◽

Causal Relationship ◽

Granger Causality ◽

Oil Prices ◽

Granger Causality Test ◽

Causality Test ◽

Macroeconomic Variables ◽

Indian Stock Market

This paper is intended to study the impact of various macroeconomic variables on Indian stock market. Based on the Arbitrage Pricing Theory (APT) propounded by Ross in 1976 and various other studies, a number of macroeconomic variables including, inflation, industrial production, exchange rate, money supply, interest rate, and oil price have been identified to have a significant impact on the stock market. We have applied the multivariate extension of the classical linear regression model computed on Ordinary Least Squares method and Granger Causality test to re-establish the relationship between macroeconomic variables and stock returns over a period of 10 years from 2005 to 2015 using monthly observations. The results of this study show that only exchange rate has a significant negative impact on stock returns. The other macroeconomic variables are not significantly affecting stock returns, however, their impact is in accordance with the economic theory. The Granger Causality test reveals absence of any causal relationship between stock returns and macroeconomic variables, except in case of oil prices, where we find a unidirectional causal relationship running from stock returns to oil prices. However, the Granger Causality results should not be taken in the conventional meaning of causality, but results merely identifying precedence.

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Disposition effect at the market level: evidence from Indian stock market

Review of Behavioral Finance ◽

10.1108/rbf-12-2018-0132 ◽

2019 ◽

Vol 12 (2) ◽

pp. 69-82

Author(s):

Sravani Bharandev ◽

Sapar Narayan Rao

Keyword(s):

Trading Volume ◽

Stock Exchange ◽

Reference Points ◽

Disposition Effect ◽

Content Type ◽

Ex Post ◽

Abnormal Trading Volume ◽

The Difference ◽

Trading Volumes ◽

Indian Stock Market

Purpose The purpose of this paper is to test the disposition effect at market level and propose an appropriate reference point for testing disposition at market level. Design/methodology/approach This is an empirical study conducted on 500 index stocks of NSE500 (National Stock Exchange). Winning and losing days for each stock are calculated using 52-week high and low prices as reference points. To test disposition effect, abnormal trading volumes of stocks are regressed on their percentage of winning (losing) days. Further using ANOVA, the difference between mean of percentage of winning (losing) days of high abnormal trading volume deciles and low abnormal trading volume deciles is tested. Findings Results show that a stock’s abnormal trading volume is positively influenced by the percentage of winning days whereas percentage of losing days show no such effect. Findings are consistent even after controlling for volatility and liquidity. ANOVA results show the presence of high percentage of winning days in higher deciles of abnormal trading volumes and no such pattern in case of losing days confirms the presence of disposition effect. Further an ex post analysis indicates that disposition prone investors accumulate losses. Originality/value This is the first study, which proposes the use of 52-week high and low prices as reference points to test the market-level disposition effect. Findings of this study enhance the limited literature available on disposition effect in emerging markets by providing evidence from Indian stock markets.

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Do Indian stock market sentiments impact contemporaneous returns?

South Asian Journal of Business Studies ◽

10.1108/sajbs-06-2018-0064 ◽

2018 ◽

Vol 7 (3) ◽

pp. 332-346

Author(s):

Divya Aggarwal ◽

Pitabas Mohanty

Keyword(s):

Stock Market ◽

Stock Returns ◽

Temporal Dynamics ◽

Stock Exchange ◽

Principal Component ◽

Stock Index ◽

Content Type ◽

Investor Sentiments ◽

Indian Stock Market ◽

The Impact

Purpose The purpose of this paper is to analyse the impact of Indian investor sentiments on contemporaneous stock returns of Bombay Stock Exchange, National Stock Exchange and various sectoral indices in India by developing a sentiment index. Design/methodology/approach The study uses principal component analysis to develop a sentiment index as a proxy for Indian stock market sentiments over a time frame from April 1996 to January 2017. It uses an exploratory approach to identify relevant proxies in building a sentiment index using indirect market measures and macro variables of Indian and US markets. Findings The study finds that there is a significant positive correlation between the sentiment index and stock index returns. Sectors which are more dependent on institutional fund flows show a significant impact of the change in sentiments on their respective sectoral indices. Research limitations/implications The study has used data at a monthly frequency. Analysing higher frequency data can explain short-term temporal dynamics between sentiments and returns better. Further studies can be done to explore whether sentiments can be used to predict stock returns. Practical implications The results imply that one can develop profitable trading strategies by investing in sectors like metals and capital goods, which are more susceptible to generate positive returns when the sentiment index is high. Originality/value The study supplements the existing literature on the impact of investor sentiments on contemporaneous stock returns in the context of a developing market. It identifies relevant proxies of investor sentiments for the Indian stock market.

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Dynamic linkage between nifty-fifty and sectorial indices of national stock exchange

American Journal of Economics and Business Management ◽

10.31150/ajebm.v3i2.148 ◽

2020 ◽

Vol 3 (2) ◽

pp. 17-27

Author(s):

Kamaljit Singh ◽

Vinod Kumar

Keyword(s):

Causal Relationship ◽

Granger Causality ◽

Unit Root ◽

Service Sector ◽

Banking Sector ◽

Stock Exchange ◽

Unit Root Test ◽

Granger Causality Test ◽

Financial Service ◽

Causality Test

The main objective of this paper is to analyze the trend and pattern of the Nifty-Fifty and sectorial indices. An attempt has been also made to find out the causal relationship among the Nifty-Fifty and NSE sectorial Indices. The unit root test and Granger-causality test has been applied to check the causal relationship between Nifty-Fifty and sectorial indices. The finding of the study shows that the financial service sector had performed better and followed by the banking sector among all the indices while the Pharma sector and the Realty sector were Under-performed in comparison to other indices. The Nifty-Fifty has been found less volatile in comparison to other sectorial indices however Realty sector indices show the highest volatility during the study period.

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The dynamic relationship between stock returns and trading volumes in Nepalese stock market

Management Dynamics ◽

10.3126/md.v23i2.35819 ◽

2020 ◽

Vol 23 (2) ◽

pp. 161-172

Author(s):

Prem Lal Adhikari

Keyword(s):

Stock Market ◽

Stock Returns ◽

Trading Volume ◽

Time Series Data ◽

Stock Exchange ◽

Causal Effect ◽

Empirical Relationship ◽

Insurance Companies ◽

Series Data ◽

Dynamic Relationship

In finance, the relationship between stock returns and trading volume has been the subject of extensive research over the past years. The main motivation for these studies is the central role that trading volume plays in the pricing of financial assets when new information comes in. As being interrelated and interdependent subjects, a study regarding the trading volume and stock returns seem to be vital. It is a well-researched area in developed markets. However, very few pieces of literature are available regarding the Nepalese stock market that explores the association between trading volume and stock return. Realizing this fact, this paper aims to examine the empirical relationship between trading volume and stock returns in the Nepalese stock market using time series data. The study sample is comprised of 49 stocks traded on the Nepal Stock Exchange (NEPSE) from mid-July 2011 to mid-July 2018. This study examines the Granger Causality relationship between stock returns and trading volume using the bivariate VAR model used by de Medeiros and Van Doornik (2008). The study found that the overall Nepalese stock market does not have a causal relationship between trading volume and return on the stock. In the case of sector-wise study, there is a unidirectional causality running from trading volume to stock returns in commercial banks and stock returns to trading volume in finance companies, hydropower companies, and insurance companies. There is no indication of any causal effect in the development bank, hotel, and other sectors. This study also finds that there is no evidence of bidirectional causality relationships in any sector of the Nepalese stock market.

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The Impact of US Monetary Growth on Bitcoin Trading Volume in the Current Economic Uncertainty

Advances in Marketing, Customer Relationship Management, and E-Services - Handbook of Research on Decision-Making Techniques in Financial Marketing ◽

10.4018/978-1-7998-2559-3.ch023 ◽

2020 ◽

pp. 493-509

Author(s):

İsmail Canöz

Keyword(s):

Causal Relationship ◽

Trading Volume ◽

Causal Effect ◽

Study Data ◽

Time Interval ◽

Time Varying ◽

Economic Uncertainty ◽

Causality Test ◽

Data Set ◽

The Impact

This study examines the effect of US monetary growth on Bitcoin trading volume. To achieve this purpose, firstly, the symmetric causality test is used. Following this test, another symmetric causality test is used to reveal a time-varying causal effect between variables. The data set covers the period from July 2010 to July 2019. The results of the first symmetric causality test, which considers the time interval of the study data as a whole, show that there is no causal relationship between variables. According to the results of the second causality test, these support the previous results substantially. However, an interesting detail is the causal relationship between variables for the period between April 2019 and July 2019. The reason for this relationship could be that investors who are indecisive during the current economic uncertainty add Bitcoin to their portfolios in response to the Federal Reserve's decisions.

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A Study of Black–Scholes Model’s Applicability in Indian Capital Markets

Paradigm ◽

10.1177/0971890720914102 ◽

2020 ◽

Vol 24 (1) ◽

pp. 73-92

Author(s):

Anubha Srivastava ◽

Manjula Shastri

Keyword(s):

Stock Market ◽

Option Pricing ◽

Trading Volume ◽

Stock Exchange ◽

Market Price ◽

Significant Degree ◽

Pricing Model ◽

Fair Price ◽

Black Scholes ◽

Indian Stock Market

Derivative trading, started in mid-2000, has become an integral and significant part of Indian stock market. The tremendous increase in trading volume in Indian stock market has reflected into high volatility in the option prices. The pricing of options is very complex aspect of applied finance and has been subject of extensive research. Black–Scholes option model is a scientific pricing model which is applied for determining the fair price for option contracts. This article examines if Black–Scholes option pricing model (BSOPM) is a good indicator of option pricing in Indian context. The literature review highlights that various studies have been conducted on BSOPM in various stock exchange across the world with mixed outcome on its relevance and applicability. This article is an empirical study to test the relevance of BSOPM for which 10 most popular industry’s stock listed on National Stock Exchange have been taken. Then the BSOPM has been applied using volatility and risk-free rate. Furthermore, t-test has been used to test the hypothesis and determine the significant relationship between BS model values and actual model values. This study concludes that BSOPM involves significant degree of mispricing. Hence, this model alone cannot be adopted as an indicator for option pricing. The variation from market price is synchronised with respect to moneyness and time to maturity of the option.

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Leveraged Bootstrap Test of Volatility: A Novel Approach to the Energy Consumption and Economic Growth Puzzle

International Journal of Economics and Finance ◽

10.5539/ijef.v9n9p117 ◽

2017 ◽

Vol 9 (9) ◽

pp. 117 ◽

Cited By ~ 1

Author(s):

Kuo-Hao Lee ◽

Jonathan Ohn ◽

Evren Eryilmaz

Keyword(s):

Economic Growth ◽

Energy Consumption ◽

Stock Returns ◽

Causal Relationship ◽

Stock Prices ◽

Granger Causality Test ◽

Energy Industry ◽

Causality Test ◽

Bootstrap Test ◽

Novel Approach

The main purpose of this research is to examine the causal relationship between the Energy industry and nine other industries by use of volatility instead of returns. Existing literatures find a causal relationship by use of stock returns, however, we find that using volatility reveals a causal relationship that might not otherwise be revealed through returns alone. Since the existing literature shows that volatility of stock prices is informative, we apply a Granger causality test by use of a leveraged bootstrap test developed by Hacker and Hatemi (2006) to investigate the causal behavior of the volatility. Our results show that volatility of the Energy industry causes volatility in two other industries- Industrials and Health Care. Also, the Energy industry market is affected by the Materials, Consumer Staples and Utilities industries. This finding is substantially different from the findings of previous research, and provides a novel approach to analyzing and solving the energy consumption and economic growth puzzle.

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What Factors Affect Stocks’ Abnormal Return during the COVID-19 Pandemic: Data from the Indonesia Stock Exchange

European Journal of Business Management and Research ◽

10.24018/ejbmr.2021.6.6.1139 ◽

2021 ◽

Vol 6 (6) ◽

pp. 1-11

Author(s):

Yohanes Indrayono

Keyword(s):

Financial Crisis ◽

Stock Returns ◽

Stock Prices ◽

Trading Volume ◽

Stock Exchange ◽

Abnormal Returns ◽

Early Period ◽

World Health ◽

Book Value ◽

Market Capitalization

This study identifies Indonesian investors’ reactions to the drop in stock prices on the Indonesia Stock Exchange market, during the early months of the COVID-19 crisis, before and after the World Health Organization (WHO) announced that its global spread constitutes a pandemic. It also explores variables that influence stock returns on this market during the financial crisis caused by the COVID-19 pandemic. This study uses a regression analysis of 70 firms, listed on the Indonesia Stock Exchange to examine the pandemic’s influence on trading volume, market capitalization, profitability, and book value for the period December 31, 2019, to April 30, 2020. The results show that stock returns were lower in the early period of the financial crisis caused by the pandemic. Firms’ trading volumes, profitability and book values positively affected stock returns and their market capitalization negatively affected stock returns during the study period. This study contributes useful insights to the finance literature and stock-market participants in terms of dealing with stock markets during financial crises. This study recommends that in any crisis investors should begin buying stocks or increasing their stock purchases to achieve abnormal returns by choosing stocks that perform well in terms of firm profitability and book value by looking a number of financial factors.

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Changes In Stock Returns And Trading Volume Of American Depositary Receipts Around Their U.S. Stock Exchange Listing Switches

Journal of Applied Business Research (JABR) ◽

10.19030/jabr.v28i6.7353 ◽

2012 ◽

Vol 28 (6) ◽

pp. 1445

Author(s):

Kam C. Chan ◽

Annie Wong

Keyword(s):

New York ◽

Stock Returns ◽

Trading Volume ◽

Stock Exchange ◽

Market Performance ◽

Foreign Firms ◽

American Depositary Receipts ◽

Font Size ◽

Depositary Receipts ◽

Year 2000

This study examines the change in stock returns and trading volume of American Depositary Receipts when foreign firms switched their listings from a major U.S. stock exchange to a more prestigious U.S. stock exchange; namely from the NASDAQ or American Stock Exchange to the New York Stock Exchange or from the American Stock Exchange to the NASDAQ since year 2000. We find that the stock returns of these American Depositary Receipts changed from better-than-market performance before the listing changes to just market performance after the listing changes. This evidence is consistent with a timing behavior of the management. We also find significant increase in their trading volume after the listing changes. This leads us to conclude that switching to a more prestigious stock exchange was able to create more investor interest.

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