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.

scholarly journals Returns to Low Risk Investment Strategy

2017 ◽  
Vol 6 (01) ◽  
pp. 2-15 ◽  
Author(s):  
Shilpa Girish Peswani
Keyword(s):  
High Risk ◽  
Stock Exchange ◽  
Risk Measures ◽  
Risk Measure ◽  
Investment Strategy ◽  
Low Risk ◽  
Total Risk ◽  
Excess Returns ◽  
Benchmark Portfolio ◽  
The Difference

The paper studies the low risk anomaly in the Indian market using entire National Stock Exchange (NSE) as sample from January 2001 to June 2016. It provides evidence that low risk portfolio sorted for total risk, systematic risk as well as unsystematic risk individually for the large cap, mid cap, small cap and the entire NSE universe give higher returns to the investor as compared to high risk portfolio. The difference of returns from low risk portfolio versus high risk portfolio is positive as well as economically and statistically significant for all the risk measures. The results also prove that low risk portfolio investing strategy returns outperform the benchmark portfolio. Using either total volatility, idiosyncratic volatility or beta as a risk measure in stocks, the low risk portfolio gives higher returns even after controlling for the well-known size, value and momentum factors. The excess returns are the highest for low risk portfolio sorted for volatility of large cap stocks. Most of the low risk portfolios consists of growth and winner stocks. In conclusion, the low risk portfolio investment strategy is independent of size and gives positive excess returns as compared to high risk portfolio in the Indian stock market.

scholarly journals The volatility effect across size buckets: evidence from the Indian stock market

2019 ◽  
Vol 16 (3) ◽  
pp. 62-75 ◽  
Author(s):  
Shilpa Peswani ◽  
Mayank Joshipura
Keyword(s):  
High Risk ◽  
Stock Market ◽  
Significant Risk ◽  
Equity Market ◽  
Sharpe Ratio ◽  
Portfolio Construction ◽  
Market Capitalization ◽  
Value Stocks ◽  
High Volatility ◽  
Indian Stock Market

The portfolio of low-volatility stocks earns high risk-adjusted returns over a full market cycle. The annual alpha spread of low versus high-volatility quintile portfolios is 25.53% in the Indian equity market for the period from January 2000 to September 2018. The low-volatility (LV) effect is not an overlap of other established factors such as size, value or momentum. The effect persists across various size buckets (market capitalization). The performance of the low-volatility effect within various size buckets is analyzed using three different portfolio formation methods. Irrespective of the method of portfolio construction, the low-volatility effect exists and it also generates economically and statistically significant risk-adjusted returns. The long-short portfolios across the study deliver exceptionally high and statistically significant returns accompanied by negative beta. The low-volatility effect is not restricted to small or illiquid stocks. The effect delivers the highest risk-adjusted returns for the portfolio consisting of largecap stocks. Though the returns of the portfolio comprising of large-cap LV stocks are lower than the returns of the portfolio comprising of small-cap LV stocks, its Sharpe ratio is higher because of less risky nature of large-cap stocks as compared to small-cap stocks. The LV portfolio majorly comprises of large-cap, growth and winner stocks. But within size buckets, large-cap and mid-cap low LV picks growth and winner stocks, while small-cap LV picks value stocks.

Day Of The Week Effect: Empirical Evidence From Indian Stock Market

Paradigm ◽  
2004 ◽  
Vol 8 (2) ◽  
pp. 9-13 ◽  
Author(s):  
Mohit Gupta ◽  
Navdeep Aggarwal
Keyword(s):  
Stock Market ◽  
Empirical Evidence ◽  
Day Of The Week ◽  
Indian Stock Market

scholarly journals RISK-RETURN TRADEOFFS IN INDIAN STOCK MARKET: EVIDENCE FROM GARCH MODEL APPROACH

2021 ◽  
pp. 556-566
Author(s):  
Riteshbhai Patel
Keyword(s):  
High Risk ◽  
Stock Market ◽  
Garch Model ◽  
Sample Period ◽  
Asymmetric Volatility ◽  
Empirical Results ◽  
Daily Return ◽  
Risk Return ◽  
Indian Stock Market ◽  
Model Approach

The objective is to examine the risk-return tradeoff in the Indian stock market. The sample period of study is from January 4, 2000 to December 31, 2020. The empirical results shows existence of risk-return tradeoff in the BSE. A positive risk-return tradeoff is found for monthly & annual return series. The market has weak risk-return relationship in daily return series. The CGARCH (1,1) captures the asymmetric volatility effect for all the different frequency based returns. The study has implications for the investors. The riskreturn relationship is stronger and significant in longer duration of investment. The market gives higher return when there is a high risk.

scholarly journals The performance of the Indian stock market during COVID-19

2020 ◽  
Vol 17 (3) ◽  
pp. 133-147
Author(s):  
Rashmi Chaudhary ◽  
Priti Bakhshi ◽  
Hemendra Gupta
Keyword(s):  
Standard Deviation ◽  
Stock Market ◽  
Stock Exchange ◽  
Health Care Information ◽  
Crisis Period ◽  
Daily Data ◽  
Composite Indices ◽  
Health Care Information Technology ◽  
Indian Stock Market ◽  
The Impact

The current empirical study attempts to analyze the impact of COVID-19 on the performance of the Indian stock market concerning two composite indices (BSE 500 and BSE Sensex) and eight sectoral indices of Bombay Stock Exchange (BSE) (Auto, Bankex, Consumer Durables, Capital Goods, Fast Moving Consumer Goods, Health Care, Information Technology, and Realty) of India, and compare the composite indices of India with three global indexes S&P 500, Nikkei 225, and FTSE 100. The daily data from January 2019 to May 2020 have been considered in this study. GLS regression has been applied to assess the impact of COVID-19 on the multiple measures of volatility, namely standard deviation, skewness, and kurtosis of all indices. All indices’ key findings show lower mean daily return than specific, negative returns in the crisis period compared to the pre-crisis period. The standard deviation of all the indices has gone up, the skewness has become negative, and the kurtosis values are exceptionally large. The relation between indices has increased during the crisis period. The Indian stock market depicts roughly the same standard deviation as the global markets but has higher negative skewness and higher positive kurtosis of returns, making the market seem more volatile.

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