scholarly journals Systematic Risk and Accounting Determinants: An Empirical Assessment in the Indian Stock Market

2019 ◽  
Vol 10 (2) ◽  
pp. 310-334
Author(s):  
Srikanth Parthasarathy
Keyword(s):  
Stock Market ◽  
Robust Regression ◽  
Risk Measures ◽  
Systematic Risk ◽  
Ordinary Least Squares ◽  
Cross Sectional ◽  
Market Beta ◽  
Regression Techniques ◽  
Indian Stock Market ◽  
High Degree

This study explores the contemporaneous association between market determined risk measures and accounting determined risk measures using the large liquid non-financial stocks in the Indian stock market in the recent 2012-2017 period. Two measures of systematic risk and seven accounting determined risk measures are chosen based on prior research. This study uses three regression techniques, namely Ordinary Least Squares (OLS), stepwise regression and robust regression, to identify the influential accounting variables for the systematic risk measured by market beta. The results evidence that there is a high degree of contemporaneous association between market determined and accounting determined risk measures, with nearly 30% of the cross sectional variance in systematic risk explained by accounting determined risk measures. The results suggest that the accounting variables can be used in the predictive models of future risk, leading to superior decision making at the level of individual decision maker.

Variance Ratio Test of Random Walk in Indian Stock Market

2015 ◽  
Vol 2 (2) ◽  
pp. 89-107
Author(s):  
Saloni Gupta ◽  
Neha Bothra
Keyword(s):  
Random Walk ◽  
Stock Market ◽  
Stock Returns ◽  
Ratio Test ◽  
Variance Ratio ◽  
Random Walk Hypothesis ◽  
Variance Ratio Test ◽  
Indian Stock Market ◽  
High Degree ◽  
The Relationship

We conduct tests of the null hypothesis of a random walk at the aggregate level of market indices and disaggregate level of individual shares to the Indian stock market over various data periods and a comparison of two sub-periods namely the pre liberalization and the post liberalization period. For this, we use the Lo-MacKinlay (1988) variance ratio test. Although the oldest test i.e. the serial correlation coefficient test is also applied to the same data to establish the relationship between the two tests but its results are not elaborated in this paper. The strength of this paper lies in the voluminous data base and a powerful testing tool that it makes use of. It is observed that the market is highly inefficient at daily returns level, thus imbibing high degree of predictability in stock returns, and even the weekly returns show the existence of trend. Monthly returns, however, support the random walk hypothesis across all periods. Thus it is concluded that further refinement of reform measures is required.

Performance of Socially Responsible Portfolios Across Sectors in Indian Stock Market

Think India ◽  
2016 ◽  
Vol 19 (1) ◽  
pp. 01-09
Author(s):  
Vanita Tripathi ◽  
Varun Bhandari
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Factor Model ◽  
Sharpe Ratio ◽  
Market Model ◽  
Socially Responsible ◽  
Cross Sectional ◽  
Responsible Investing ◽  
Indian Stock Market ◽  
Three Factor

The question of whether socially responsible stocks outperform or under-perform general stocks has been of keen interest for various researchers and academicians. This paper seeks to empirically examine the performance of socially responsible portfolios across various sectors and index of socially responsible and general companies in Indian stock market. We have taken up S&P ESG and CNX NIFTY as the indices of socially responsible and general companies respectively. ESG index has been classified into six different sectors on the basis of GICS. Performance has been evaluated in terms of risk, return and various risk-adjusted measures like Sharpe ratio, Treynor ratio, Double Sharpe ratio, Modified Sharpe ratio, M2 measure, Jensens alpha, Famas decomposition measure, etc. We have also checked whether market model is sufficient to explain cross sectional variation in stock returns or we need Fama-French three factor model. The study period ranges from January 1996 – December 2013 and it is further divided into different sub-periods. We find that socially responsible stocks across IT, FMCG and financial sectors are well rewarding in Indian stock market by generating significantly higher returns and outperforming the two indices on the basis of risk-adjusted measures employed during 18 year period and different sub-periods. The results uphold even with the use of market model and Fama-French three factor model by generating highest significant excess returns. There is no empirical evidence on the performance evaluation of socially responsible portfolios across different sectors. Hence this study is first of its kind. This will help investors in selecting best sector for investment in socially responsible companies. Significant higher returns of ESG index and socially responsible stocks across different sectors make Socially Responsible Investing (SRI) a better investment vehicle for investors in India. This is the time when general companies should change their approach and agenda towards CSR and start considering ESG issues as their investment themes. The regulators, policy makers and mutual funds should come up with different socially responsible products and sectoral indices to initiate the movement of SRI across different sectors in India.

scholarly journals The Volatility Effect: Evidence from India

2016 ◽  
Vol 5 (1) ◽  
pp. 12 ◽  
Author(s):  
Mayank Joshipura ◽  
Nehal Joshipura
Keyword(s):  
Standard Deviation ◽  
High Risk ◽  
Stock Market ◽  
Empirical Evidence ◽  
Risk Measures ◽  
Benchmark Portfolio ◽  
Beta Effect ◽  
High Volatility ◽  
The Difference ◽  
Indian Stock Market

We offer empirical evidence that stocks with low volatility earn higher risk-adjusted returns compared to high volatility stocks in the Indian stock market. The annualised excess returns for the low and high volatility decile portfolios amount to 11.40% and 1.30%, respectively, over the period January 2001 to June 2015. The difference of returns is statistically and economically significant for both low and high-risk stocks. Using risk measures of standard deviation and beta, the volatility effect remains after controlling for size, value and momentum. We uncover that the volatility effect is not statistically significant after controlling for beta effect. Our evidence for volatility effect is not dominated by small and illiquid stocks. Our results show that the low volatility portfolio outperforms benchmark portfolio not only in down market but also in up market conditions.

Impact of herding on the returns in the Indian stock market: an empirical study

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sunaina Kanojia ◽  
Deepti Singh ◽  
Ashutosh Goswami
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Market Condition ◽  
Individual Investors ◽  
Herd Behavior ◽  
Market Conditions ◽  
Absolute Deviation ◽  
Cross Sectional ◽  
Content Type ◽  
Indian Stock Market

PurposeHerd behavior has been studied herein and tested based on primary respondents from Indian markets.Design/methodology/approachThe paper expounds the empirical evidence by applying the cross-sectional absolute deviation method and reporting on herd behavior among decision-makers who are engaged in trading in the Indian stock market. Further, the study attempts to analyze the market-wide herding in the Indian stock market using 2230 daily, 470 weekly and 108 monthly observations of Nifty 50 stock returns for a period of nine years from April 1, 2009 to March 31, 2018 during the normal market conditions, extreme market conditions and in both increasing and decreasing market conditions.FindingsIn a span of a decade witnessing different market cycles, the authors’ results exhibit that there is no evidence of herding in any market condition in Indian stock market primarily due to the dominance of institutional investors and secondly because of low market participation by individual investors.Originality/valueThe results reveal that there is no impact of herd behavior on the stock returns in the Indian equity market during the normal market conditions. It highlights that the participation of individuals who are more prone to herding is more evident for short-run investments, contrary to long-term holdings.

Conditional multifactor asset pricing model and market anomalies

2013 ◽  
Vol 5 (4) ◽  
pp. 271-294 ◽  
Author(s):  
Saumya Ranjan Dash ◽  
Jitendra Mahakud
Keyword(s):  
Stock Market ◽  
Size Effect ◽  
Investment Strategy ◽  
Momentum Effect ◽  
Market Anomalies ◽  
Cross Sectional ◽  
Content Type ◽  
Short Run ◽  
The Cross ◽  
Indian Stock Market

Purpose – The purpose of this paper is to investigate the firm-specific anomaly effect and to identify market anomalies that account for the cross-sectional regularity in the Indian stock market. The paper also examines the cross-sectional return predictability of market anomalies after making the firm-specific raw return risk adjusted with respect to the systematic risk factors in the unconditional and conditional multifactor specifications. Design/methodology/approach – The paper employs first step time series regression approach to drive the risk-adjusted return of individual firms. For examining the predictability of firm characteristics on the risk-adjusted return, the panel data estimation technique has been used. Findings – There is a weak anomaly effect in the Indian stock market. The choice of a five-factor model (FFM) in its unconditional and conditional specifications is able to capture the book-to-market equity, liquidity and medium-term momentum effect. The size, market leverage and short-run momentum effect are found to be persistent in the Indian stock market even with the alternative conditional specifications of the FFM. The results also suggest that it is naï argue for disappearing size effect in the cross-sectional regularity. Research limitations/implications – Constrained upon the data availability, certain market anomalies and conditioning variables cannot be included in the analysis. Practical implications – Considering the practitioners' prospective, the results indicate that the profitable investment strategy with respect to the small size effect is still persistent and warrants close-ended mutual fund investment portfolio strategy for enhancing the long-term profitability. The short-run momentum effect can generate potential profits given a short-term investment horizon. Originality/value – This paper provides the first-ever empirical evidence from an emerging stock market towards the use of alternative conditional multifactor models for the complete explanation of market anomalies. In an attempt to analyze the anomaly effect in the Indian stock market, this paper provides further evidence towards the long-short hedge portfolio return variations in terms of a wide set of market anomalies that have been documented in prior literature.

scholarly journals Liquidity and Asset Pricing: Evidence from Indian Stock Market

2020 ◽  
Vol 4 (1) ◽  
pp. 109-116
Author(s):  
Sharad Nath Bhattacharya ◽  
Mousumi Bhattacharya ◽  
Sumit Kumar Jha
Keyword(s):  
Asset Pricing ◽  
Stock Market ◽  
Stock Returns ◽  
Risk Premium ◽  
Negative Impact ◽  
Stock Exchange ◽  
Systematic Risk ◽  
Liquidity Premium ◽  
Significant Negative Impact ◽  
Indian Stock Market

In this research article, we present a liquidity premium based asset pricing model and test it in the Indian stock market. Using high-frequency data of stocks listed in the National Stock Exchange, we show that observed illiquidity has a significant negative impact on realized stock returns even after controlling for the up and down market, volatility, and effects of derivatives trading. The illiquidity measure is modified for its time variations, and then the modified measure is used to assess its impact on returns. Using a cross-section of stocks, we show the year wise results of the model and extend it to show that it has some role in explaining returns across industries. Findings show that the down market has contemporaneous systematic risk at higher levels, and the market risk premium is higher in down markets. Finance, utility and real estate sector companies have higher systematic risk in both up and down market and investors of these sectors has relatively higher expected higher returns in comparison to companies from the rest of the segments.

Performance of Socially Responsible Portfolios Across Sectors in Indian Stock Market

2016 ◽  
Vol 5 (1) ◽  
Author(s):  
Vanita Tripathi ◽  
Varun Bhandari
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Factor Model ◽  
Sharpe Ratio ◽  
Market Model ◽  
Socially Responsible ◽  
Cross Sectional ◽  
Responsible Investing ◽  
Indian Stock Market ◽  
Three Factor

The question of whether socially responsible stocks outperform or under-perform general stocks has been of keen interest for various researchers and academicians. This paper seeks to empirically examine the performance of socially responsible portfolios across various sectors and index of socially responsible and general companies in Indian stock market. We have taken up S&P ESG and CNX NIFTY as the indices of socially responsible and general companies respectively. ESG index has been classified into six different sectors on the basis of GICS. Performance has been evaluated in terms of risk, return and various risk-adjusted measures like Sharpe ratio, Treynor ratio, Double Sharpe ratio, Modified Sharpe ratio, M2 measure, Jensens alpha, Famas decomposition measure, etc. We have also checked whether market model is sufficient to explain cross sectional variation in stock returns or we need Fama-French three factor model. The study period ranges from January 1996 December 2013 and it is further divided into different sub-periods. We find that socially responsible stocks across IT, FMCG and financial sectors are well rewarding in Indian stock market by generating significantly higher returns and outperforming the two indices on the basis of risk-adjusted measures employed during 18 year period and different sub-periods. The results uphold even with the use of market model and Fama-French three factor model by generating highest significant excess returns. There is no empirical evidence on the performance evaluation of socially responsible portfolios across different sectors. Hence this study is first of its kind. This will help investors in selecting best sector for investment in socially responsible companies. Significant higher returns of ESG index and socially responsible stocks across different sectors make Socially Responsible Investing (SRI) a better investment vehicle for investors in India. This is the time when general companies should change their approach and agenda towards CSR and start considering ESG issues as their investment themes. The regulators, policy makers and mutual funds should come up with different socially responsible products and sectoral indices to initiate the movement of SRI across different sectors in India.

scholarly journals Social sentiment segregation: Evidence from Twitter and Google Trends in Chile during the COVID-19 dynamic quarantine strategy

PLoS ONE ◽  
2021 ◽  
Vol 16 (7) ◽  
pp. e0254638
Author(s):  
Fernando Díaz ◽  
Pablo A. Henríquez
Keyword(s):  
Stock Market ◽  
Media Coverage ◽  
Google Trends ◽  
Cross Sectional ◽  
Market Reactions ◽  
The Public ◽  
Health Authorities ◽  
Stock Market Reactions ◽  
High Degree ◽  
The Impact

The Chilean health authorities have implemented a sanitary strategy known as dynamic quarantine or strategic quarantine to cope with the COVID-19 pandemic. Under this system, lockdowns were established, lifted, or prolonged according to the weekly health authorities’ assessment of municipalities’ epidemiological situation. The public announcements about the confinement situation of municipalities country-wide are made typically on Tuesdays or Wednesdays before noon, have received extensive media coverage, and generated sharp stock market fluctuations. Municipalities are the smallest administrative division in Chile, with each city broken down typically into several municipalities. We analyze social media behavior in response to the confinement situation of the population at the municipal level. The dynamic quarantine scheme offers a unique opportunity for our analysis, given that municipalities display a high degree of heterogeneity, both in size and in the socioeconomic status of their population. We exploit the variability over time in municipalities’ confinement situations, resulting from the dynamic quarantine strategy, and the cross-sectional variability in their socioeconomic characteristics to evaluate the impact of these characteristics on social sentiment. Using event study and panel data methods, we find that proxies for social sentiment based on Twitter queries are negatively related (more pessimistic) to increases in the number of confined people, but with a statistically significant effect concentrated on people from the wealthiest cohorts of the population. For indicators of social sentiment based on Google Trends, we found that search intensity during the periods surrounding government announcements is positively related to increases in the total number of confined people. Still, this effect does not seem to be dependent on the segments of the population affected by the quarantine. Furthermore, we show that the observed heterogeneity in sentiment mirrors heterogeneity in stock market reactions to government announcements. We provide evidence that the observed stock market behavior around quarantine announcements can be explained by the number of people from the wealthiest segments of the population entering or exiting lockdown.

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