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Low-risk equity investment – From theory to practice

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  • Alessandro Russo

    (Bocconi University)

Abstract

Financial theory assumes that higher risk is compensated on average by higher returns. However, the outperformance of low-volatility stocks during the last 50 years has been among the most puzzling anomalies in equity markets. At the same time, low-risk investing has recently gained a remarkable interest, due to its documented performance coupled with the unprecedented volatility experienced during the last global financial crisis. The section ‘Literature Review’ of our study discusses how researchers have been documenting such anomaly and explaining (since the early nineties) this phenomenon with theories referring to leverage constraints, behavioral bias, delegated portfolio, benchmarking and the utility function of fund managers. Recognizing that most of the available empirical research focuses on the US equity market, section ‘Empirical Evidence in the International Arena’ is dedicated to some additional tests that we have run on the persistency and significance of the anomaly in the international arena: We find that the relationship between risk-adjusted returns and risk is negative indeed, and that the relationship holds regardless of the risk measure employed for tests (Beta or volatility). In section ‘Can Skewness And Convexity Explain the Low-Risk Anomaly?’, we investigate two possible explanations of the anomaly related to the distribution of equity returns, namely skewness and convexity. We find that high-risk stocks exhibit higher skewness and higher convexity than low-risk stocks. These results may effectively explain the anomaly because, if the price paid for stocks with higher-than-average skewness and convexity is inflated, their subsequent returns are consequently lower-than-average, at least in risk-adjusted terms. In the last section of our research, we discuss two popular risk-based smart beta strategies (minimum variance and risk parity) proving that both of them benefit from the low-risk anomaly via a significant and systematic bias toward low-risk stocks. We ultimately discuss some best practices of implementing the minimum-variance process, and provide an effective and parsimonious portfolio construction rule for the risk parity process.

Suggested Citation

  • Alessandro Russo, 2016. "Low-risk equity investment – From theory to practice," Journal of Asset Management, Palgrave Macmillan, vol. 17(4), pages 264-279, July.
  • Handle: RePEc:pal:assmgt:v:17:y:2016:i:4:d:10.1057_jam.2016.13
    DOI: 10.1057/jam.2016.13
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    References listed on IDEAS

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    1. Frazzini, Andrea & Pedersen, Lasse Heje, 2014. "Betting against beta," Journal of Financial Economics, Elsevier, vol. 111(1), pages 1-25.
    2. Andrew Ang & Robert J. Hodrick & Yuhang Xing & Xiaoyan Zhang, 2006. "The Cross‐Section of Volatility and Expected Returns," Journal of Finance, American Finance Association, vol. 61(1), pages 259-299, February.
    3. Fama, Eugene F & MacBeth, James D, 1973. "Risk, Return, and Equilibrium: Empirical Tests," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 607-636, May-June.
    4. Shefrin, Hersh & Statman, Meir, 2000. "Behavioral Portfolio Theory," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 35(2), pages 127-151, June.
    5. Kraus, Alan & Litzenberger, Robert H, 1976. "Skewness Preference and the Valuation of Risk Assets," Journal of Finance, American Finance Association, vol. 31(4), pages 1085-1100, September.
    6. Fama, Eugene F & French, Kenneth R, 1992. "The Cross-Section of Expected Stock Returns," Journal of Finance, American Finance Association, vol. 47(2), pages 427-465, June.
    7. repec:dau:papers:123456789/4688 is not listed on IDEAS
    8. Chunhachinda, Pornchai & Dandapani, Krishnan & Hamid, Shahid & Prakash, Arun J., 1997. "Portfolio selection and skewness: Evidence from international stock markets," Journal of Banking & Finance, Elsevier, vol. 21(2), pages 143-167, February.
    9. Piotroski, JD, 2000. "Value investing: The use of historical financial statement information to separate winners from losers," Journal of Accounting Research, Wiley Blackwell, vol. 38, pages 1-41.
    10. William F. Sharpe, 1964. "Capital Asset Prices: A Theory Of Market Equilibrium Under Conditions Of Risk," Journal of Finance, American Finance Association, vol. 19(3), pages 425-442, September.
    11. Blitz, D.C. & van Vliet, P., 2007. "The Volatility Effect: Lower Risk without Lower Return," ERIM Report Series Research in Management ERS-2007-044-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
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    Cited by:

    1. Lauren Stagnol, 2016. "The Risk Parity Principle applied on a Corporate Bond Index using Duration Times Spread," Working Papers hal-04141582, HAL.
    2. David Blitz & Matthias X. Hanauer & Pim Vliet, 2021. "The Volatility Effect in China," Journal of Asset Management, Palgrave Macmillan, vol. 22(5), pages 338-349, September.

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