The volatility effect across size buckets: evidence from the Indian stock market
-
Author(s)Shilpa PeswaniLink to ORCID Index: https://orcid.org/0000-0002-8418-1536
,
Mayank JoshipuraLink to ORCID Index: https://orcid.org/0000-0001-7711-6229
-
DOIhttp://dx.doi.org/10.21511/imfi.16(3).2019.07
-
Article InfoVolume 16 2019, Issue #3, pp. 62-75
- Cited by
- 945 Views
-
171 Downloads
This work is licensed under a
Creative Commons Attribution 4.0 International License
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.
- Keywords
-
JEL Classification (Paper profile tab)G11, G12, G14, G15
-
References25
-
Tables17
-
Figures4
-
- Figure 1. Indian mutual fund industry – assets under management
- Figure 2. Comparison of returns from Nifty Low-Volatility 50 Index and Nifty 50 Index
- Figure 3A. Descriptive statistics – no. of stocks
- Figure 3B. Descriptive statistics – total market capitalization
-
- Table 1. Risk and return of volatility ranked portfolios
- Table 2. CAPM style alpha, three-factor alpha and four-factor alpha of volatility ranked portfolios
- Table 3. Three-factor and four-factor regression coefficients of volatility extreme portfolios
- Table 4. Excess returns of independent sort portfolios on size and volatility
- Table 5. Ex-post beta ratio of quintile portfolios independently sorted on size and volatility
- Table 6. Sharpe ratio of quintile portfolios independently sorted on size and volatility
- Table 7. CAPM style alpha of quintile portfolios independently sorted on size and volatility
- Table 8. Three factor alpha of quintile portfolios independently sorted on size and volatility
- Table 9. Four factor alpha of quintile portfolios independently sorted on size and volatility
- Table 10. Regression coefficient analysis of three-factor (Fama-French) alpha of portfolios independently sorted on size and volatility with their corresponding t-value
- Table 11. Regression coefficient analysis of three-factor (Fama-French) alpha of portfolios independently sorted on size and volatility with their corresponding t-value
- Table 12. Risk and return of dependent portfolios sorted on volatility and controlled for size
- Table 13. CAPM style alpha, three-factor and four-factor alpha of volatility ranked portfolios controlled for size
- Table 14. Three-factor and four-factor regression coefficients dependent portfolios ranked on volatility and controlled for size
- Table 15. Risk and return of large-cap, mid-cap and small-cap stocks sorted on historical volatility
- Table 16. CAPM style alpha, three-factor alpha and four-factor alpha of volatility ranked portfolios within various size buckets
- Table 17. Three-factor and four-factor regression coefficients of volatility ranked portfolios of largecap, mid-cap and small-cap stocks
-
- Agarwalla, S. K. (2013). Four factor model in Indian equities market (Working Paper W.P. No.2013-09-05). Indian Institute of Management, Ahmedabad.
- Ang, A., Hodrick, R., Xing, Y., & Zhang, X. (2006). The Cross Section of Volatility and Expected Return. Journal of Finance, 61(1), 259-299.
- Baker, M., Bradley, B., & Wurgler, J. (2011). Benchmarks as Limits to Arbitrage: Understanding the Low-Volatility Anomaly. Financial Analysts Journal, 67(1), 40-54.
- Baker, N., & Haugen, R. (2012). Low Risk Stocks Outperform within All Observable Markets of the World. Journal of Portfolio Management, 17(3), 35-40.
- Bali, T. G., Cakici, N., & Whitelaw, R. (2011). Maxing out: Stocks as lotteries and the cross-section of expected returns. Journal of Financial Economics, 99(2), 427-446.
- Bali, T., & Cakici, N. (2008). Idiosyncratic volatility and the cross section of expected returns. Journal of Financial and Quantitative Analysis, 43(1), 29-58.
- Black, F., Jensen, M., & Scholes, M. (1972). The Capital Asset Pricing Model: Some Empirical Tests. In Studies in the Theory of Capital Markets, edited by M. C. Jensen. New York: Praeger.
- Blitz, D., & Vliet, P. (2007). The Volatility Effect: Lower Risk Without Lower Return. Journal of Portfolio Management, 34(Fall), 102-113.
- Blitz, D., Pang, J., & Vliet, P. (2013). The Volatility Effect in Emerging Markets. Emerging Markets Review, 16, 31-45.
- Carhart, M. (1997). On persistence in mutual fund performance. The Journal of Finance, 52(1), 57-82.
- Carvalho, R., Lu, X., & Moulin, P. (2012). Demystifying Equity Risk-Based Strategies: A Simple Alpha plus Beta Description. Journal of Portfolio Management, 8(3), 56-70.
- Centre for Monitoring Indian Economy (2018, December). Prowess Database.
- Clarke, R., De Silva, H., & Thorley, S. (2006). Minimum-Variance Portfolio in the U.S. Equity Market. The Journal of Portfolio Management, 33(1), 10-24.
- Fama, E., & French, K. (1992). The Cross-section of Expected Stock Returns. Journal of Finance, 47(2), 427-465.
- Frazzini, A., & Pedersen, L. (2014). Betting Against Beta. Journal of Financial Economics, 111(1), 1-25.
- Haugen, R. A., & Baker, N. L. (1991). The Efficient Market Inefficiency of Capitalization weighted Stock Portfolios. Journal of Portfolio Management, 17(3), 35-40.
- Haugen, R., & Baker, N. (1996). Commonality in the Determinants of Expected Returns. Journal of Financial Economics, 41(3), 401-439.
- Haugen, R., & Heins, A. (1975). Risk and the Rate of Return on Financial Assets: Some Old Wine in New Bottles. Journal of Financial and Quantitative Analysis, 10(5), 775-784.
- Hong, H., & Sraer, D. (2012). Speculative Betas (NBER working paper).
- Joshipura, M., & Peswani, S. (2017). Returns to Low Risk Investment Strategy. Applied Finance Letters, 6(1), 2-15.
- Joshipura, M., & Peswani, S. (2018). The Volatility Effect in Value and Growth Stocks: Evidence from India. NMIMS Management Review.
- Martellini, L. (2008). Toward the Design of Better Equity Benchmarks: Rehabilitating the Tangency Portfolio from Modern Portfolio Theory. Journal of Portfolio Management, 34(4), 34-41.
- Reserve Bank of India (2018, December). Financial Market’and sub-heading ‘Government Securities Market.
- Scherer, B. (2011). A Note on the Returns from Minimum Variance Investing. Journal of Empirical Finance, 18(4), 652-660.
- Shah, R. (2011). Understanding Low Volatility Strategies: Minimum Variance. Dimensional Fund Advisor.
