Low-risk effect: evidence, explanations and approaches to enhancing the performance of low-risk investment strategies
-
DOIhttp://dx.doi.org/10.21511/imfi.17(2).2020.11
-
Article InfoVolume 17 2020, Issue #2, pp. 128-145
- Cited by
- 1339 Views
-
288 Downloads
This work is licensed under a
Creative Commons Attribution 4.0 International License
The authors offer evidence for low-risk effect from the Indian stock market using the top-500 liquid stocks listed on the National Stock Exchange (NSE) of India for the period from January 2004 to December 2018. Finance theory predicts a positive risk-return relationship. However, empirical studies show that low-risk stocks outperform high-risk stocks on a risk-adjusted basis, and it is called low-risk anomaly or low-risk effect. Persistence of such an anomaly is one of the biggest mysteries in modern finance. The authors find strong evidence in favor of a low-risk effect with a flat (negative) risk-return relationship based on the simple average (compounded) returns. It is documented that low-risk effect is independent of size, value, and momentum effects, and it is robust after controlling for variables like liquidity and ticket-size of stocks. It is further documented that low-risk effect is a combination of stock and sector level effects, and it cannot be captured fully by concentrated sector exposure. By integrating the momentum effect with the low-volatility effect, the performance of a low-risk investment strategy can be improved both in absolute and risk-adjusted terms. The paper contributed to the body of knowledge by offering evidence for: a) robustness of low-risk effect for liquidity and ticket-size of stocks and sector exposure, b) how one can benefit from combining momentum and low-volatility effects to create a long-only investment strategy that offers higher risk-adjusted and absolute returns than plain vanilla, long-only, low-risk investment strategy.
- Keywords
-
JEL Classification (Paper profile tab)G11, G12, G14
-
References45
-
Tables6
-
Figures1
-
- Figure 1. Time-varying sector exposure of long-only low-risk portfolios
-
- Table 1. Main results (annualized) for quintile portfolios based on historical volatility
- Table 2. Three-factor (Fama-French) and four-factor (Fama-French-Carhart) style regression analysis for risk quintile portfolios
- Table 3. Double-sorted results
- Table 4. Performance of low-risk and high-risk portfolios controlling for sector effect (macro effect)
- Table 5. Performance statistics of momentum blended risk-quintile portfolios
- Table 6. Sector exposure statistics and one-way turnover for low-risk investment strategies
-
- Agarwal, V., Jiang, L., & Wen, Q. (2018). Why Do Mutual Funds Hold Lottery Stocks? (Research Paper No. 3164692). Georgetown McDonough School of Business.
- Alighanbari, M., Doole, S., & Shankar, D. (2016). Designing Low-Volatility Strategies. The Journal of Index Investing, 7(3), 21-33.
- Ang, A., Hodrick, R. J., Xing, Y., & Zhang, X. (2006). The cross-section of volatility and expected returns. The Journal of Finance, 61(1), 259-299.
- Ang, A., Hodrick, R. J., Xing, Y., & Zhang, X. (2009). High idiosyncratic volatility and low returns: International and further U.S. evidence. Journal of Financial Economics, 91(1), 1-23.
- Asness, C. S., Frazzini, A., & Pedersen, L. H. (2014). Low-Risk Investing without Industry Bets. Financial Analysts Journal, 70(4), 24-41.
- Asness, C., Ilmanen, R., Israel, A., & Moskowitz, T. (2015). Investing with Style. Journal of Investment Management, 13(1), 27-63.
- Baker, M., Bradley, B., & Taliaferro, R. (2014). The Low-Risk Anomaly: A Decomposition into Micro and Macro Effects. Financial Analysts Journal, 70(2), 43-58.
- Baker, M., Bradley, B., & Wurgler, J. (2011). Benchmarks as Limits to Arbitrage: Understanding the Low-Volatility Anomaly. Financial Analysts Journal, 67(1), 40-54.
- Bali, T. G., & Cakici, N. (2008). Idiosyncratic Volatility and the Cross Section of Expected Returns. Journal of Financial and Quantitative Analysis, 43(1), 29-58.
- Bali, T. G., Cakici, N., & Whitelaw, R. F. (2011). Maxing out: Stocks as lotteries and the cross-section of expected returns. Journal of Financial Economics, 99(2), 427-446.
- Barber, B. M., & Odean, T. (2008). All that glitters: The effect of attention and news on the buying behavior of individual and institutional investors. Review of Financial Studies, 21(2), 785-818.
- Beveratos, A., Bouchaud, J. P., Ciliberti, S., Laloux, L., Lempérière, Y., Potters, M., & Simon, G. (2017). Deconstructing the low-vol anomaly. The Journal of Portfolio Management, 44(1), 91-103.
- Black, F. (1972). Capital Market Equilibrium with Restricted Borrowing. The Journal of Business, 45(3), 444-455.
- Black, F. (1993). Beta and Return. The Journal of Portfolio Management, 20(1), 8-18.
- Blitz, D. (2016). The Value of Low Volatility. The Journal of Portfolio Management, 42(3), 94-100.
- Blitz, D. C., & Vliet, P. (2007). The volatility effect. The Journal of Portfolio Management, 34(1), 102-113.
- Blitz, D., & Vliet, P. (2018). The Conservative Formula: Quantitative Investing Made Easy. The Journal of Portfolio Management, 44(7), 24-38.
- Blitz, D., Pang, J., & Vliet, P. (2013). The volatility effect in emerging markets. Emerging Markets Review, 16(1), 31-45.
- Brennan, M. J., Cheng, X., & Li, F. (2012). Agency and Institutional Investment. European Financial Management, 18(1), 1-27.
- Carhart, M. M. (1997). On persistence in mutual fund performance. The Journal of Finance, 52(1), 57-82.
- Centre for Monitoring Indian Economy (CMIE). (n.d.). Fama French and Momentum Factors: Data Library for Indian Market.
- Choueifaty, Y., & Coignard, Y. (2008). Toward maximum diversification. The Journal of Portfolio Management, 35(1), 40-51.
- Chow, T., Hsu, J. C., Kuo, L., & Li, F. (2014). A Study of Low-Volatility Portfolio Construction Methods. The Journal of Portfolio Management, 40(4), 89-105.
- Clarke, R., de Silva, H., & Thorley, S. (2006). Minimum-variance portfolios in the U.S. equity market. The Journal of Portfolio Management, 33(1), 10-24.
- Dempsey, M. (2015). The Capital Asset Pricing Model. In Stock Markets, Investments and Corporate Behavior (pp. 11-30).
- Exchange Traded Funds (ETF). (n.d.). Official website.
- Fama, E. F., & French, K. R. (1992). The Cross-Section of Expected Stock Returns. The Journal of Finance, 47(2), 427.
- Fama, E. F., & MacBeth, J. D. (1973). Risk, Return, and Equilibrium: Empirical Tests. Journal of Political Economy, 81(3), 607-636.
- Frazzini, A., & Pedersen, L. H. (2014). Betting against beta. Journal of Financial Economics, 111(1), 1-25.
- Fu, F. (2009). Idiosyncratic risk and the cross-section of expected stock returns. Journal of Financial Economics, 91(1), 24-37.
- Garcia-Feijóo, L., Kochard, L., Sullivan, R. N., & Wang, P. (2015). Low-Volatility Cycles: The Influence of Valuation and Momentum on Low-Volatility Portfolios. Financial Analysts Journal, 71(3), 47-60.
- Hsu, J. C., Kudoh, H., & Yamada, T. (2013). When Sell-Side Analysts Meet High-Volatility Stocks: An Alternative Explanation for the Low-Volatility Puzzle. Journal of Investment Management, 11(2), 28-46.
- Jobson, J. D., & Korkie, B. M. (1981). Performance Hypothesis Testing with the Sharpe and Treynor Measures. The Journal of Finance, 36(4), 889-908.
- Joshipura, M., & Joshipura, N. (2016). The Volatility Effect: Evidence from India. Applied Finance Letters, 5(1), 12-27.
- Leote de Carvalho, R., Lu, X., & Moulin, P. (2012). Demystifying Equity Risk–Based Strategies: A Simple Alpha plus Beta Description. The Journal of Portfolio Management, 38(3), 56-70.
- Markowitz, H. (1952). Portfolio Selection. The Journal of Finance, 7(1), 77-91.
- Martellini, L. (2008). Toward the Design of Better Equity Benchmarks. The Journal of Portfolio Management, 34(4), 34-41.
- Memmel, C. (2003). Performance Hypothesis Testing with the Sharpe Ratio. Finance Letters, 1(1), 21-23.
- Miller, E. M. (1977). Risk, Uncertainty, and Divergence of Opinion. The Journal of Finance, 32(4), 1151-1168.
- Pensions & Investments (P&I) (n.d.). Official website.
- Peswani, S., & Joshipura, M. (2019). The volatility effect across size buckets: evidence from the Indian stock market. Investment Management and Financial Innovations, 16(3), 62-75.
- Scherer, B. (2011). A note on the returns from minimum variance investing. Journal of Empirical Finance, 18(4), 652-660.
- Sharpe, W. F. (1964). Capital Asset Prices: A Theory of Market Equilibrium under Conditions of Risk. The Journal of Finance, 19(3), 425-442.
- Soe, A. M. (2012). Low-Volatility Portfolio Construction: Ranking Versus Optimization. The Journal of Index Investing, 3(3), 63-73.
- van Vliet, P. (2018). Low Volatility Needs Little Trading. The Journal of Portfolio Management, 44(3), 33-42.