Low-volatility investing

Low-volatility investing is an investment style that buys stocks or securities with low volatility and avoids those with high volatility. This investment style exploits the low-volatility anomaly. According to financial theory risk and return should be positively related, however in practice this is not true. Low-volatility investors aim to achieve market-like returns, but with lower risk. This investment style is also referred to as minimum volatility, minimum variance, managed volatility, smart beta, defensive and conservative investing.

History

The low-volatility anomaly was already discovered in the early 1970s, yet it only became a popular investment style after the 2008 global financial crises. The first tests of the Capital Asset Pricing Model (CAPM) showed that the risk-return relation was too flat.[1][2] Two decades later, in 1992 the seminal study by Fama and French clearly showed that market beta (risk) and return were not related when controlling for firm size.[3] The three-factor model therefore added size and value as two additional factors next to traditional market beta. In the 2000s more studies followed, and investors started to take notice.[4][5][6] In the same period, asset managers such as Acadian, Robeco and Unigestion started offering this new investment style to investors. A few years later index providers such as MSCI and S&P started to create low-volatility indices.

Performance

10 portfolios of stocks sorted on volatility: US 1929-2018.

This investment style is slowly becoming accepted, as many low-volatility strategies have been able to deliver good real-life performance. Several low-volatility strategies have existed for more than 10 years. Most academic studies and most low-volatility indices are based on simulations. Some studies go back 90 years and show that low-volatility stocks beat high-volatility stocks over the very long run (see image). Since low-volatility securities tend to lag during bull markets and tend to reduce losses in bear markets, a full business cycle is needed to assess performance. Over a shorter time period like one year, Jensen’s alpha is useful to calculate performance. This performance metric corrects the performance of for market beta risk. For example, when a low-volatility strategy has a beta of 0.7 and the market is up by 10% the expected return is 7%. Lower risk should give lower return. If the actual return is 10%, then Jensen’s alpha is 3%.

Criticism

Any investment strategy might become ineffective over time if its popularity causes its advantage to be arbitraged away. That could also be the case for low-volatility investing, and some point to the high valuations of low-volatility stocks in the late 2010s.[7] Others state that low-volatility is related to the well-known value investing style. For example, after the dotcom bubble, value stocks offered protection similar to low volatility stocks. Finally, low-volatility stocks also tend to have more interest rate risk compared to other stocks.[8] 2020 is a challenging year for US low volatility stocks since they significantly lag the broad market by wide margins.[9] The criticism and discussions are found mainly in the various academic financial journals, but investors take notice and also contribute to this debate.[10][11]

See also

  • Low-volatility anomaly
  • Style investing
  • Value investing
  • Momentum investing

Further reading

A couple of books have been written about low-volatility investing:

  • Eric Falkenstein, Wiley 2011, Finding Alpha: The search for alpha when risk and return break down. ISBN 9780470445907
  • Peter Sander, McGraw-Hill 2013, All about low-volatility investing. ISBN 9780071819848.
  • Eric Falkenstein, 2016, The Missing Risk Premium: Why low-volatility investing works. ISBN 1470110970
  • Pim van Vliet, Jan de Koning, Wiley 2016, High Returns from Low Risk: A Remarkable Stock Market Paradox. ISBN 9781119351054.

References

  1. ^ Black, F., Jensen, M. C., & Scholes, M. (1972). The capital asset pricing model: Some empirical tests. Studies in the theory of capital markets81(3), 79-121.
  2. ^ Fama, E. F., & MacBeth, J. D. (1973). Risk, return, and equilibrium: Empirical tests. Journal of Political Economy81(3), 607-636.
  3. ^ Fama, E. F., & French, K. R. (1992). The cross‐section of expected stock returns. The Journal of Finance47(2), 427-465.
  4. ^ Ang, A., Hodrick, R. J., Xing, Y., & Zhang, X. (2006). The cross‐section of volatility and expected returns. The Journal of Finance61(1), 259-299.
  5. ^ Clarke, Roger, Harindra de Silva & Steven Thorley (2006), “Minimum-variance portfolios in the US equity market”, Journal of Portfolio Management, Fall 2006, Vol. 33, No. 1, pp.10–24.
  6. ^ Blitz, David; van Vliet, Pim (2007). “The Volatility Effect: Lower Risk Without Lower Return”. Journal of Portfolio Management34(1): 102–113. doi:10.3905/jpm.2007.698039. SSRN 980865.
  7. ^ “How Can “Smart Beta” Go Horribly Wrong?”. researchaffiliates.com. Retrieved 2019-07-24.
  8. ^ Baker, Malcolm; Wurgler, Jeffrey (2012). “Comovement and Predictability Relationships Between Bonds and the Cross-Section of Stocks” (PDF).
  9. ^ “Some investors tried to win by losing less-they lost anyway”. Wallstreet Journal. 18 September 2020.
  10. ^ Hamtil, Lawrence (2019-07-22). “Compendium of Low Volatility Articles”. Fortune Financial Advisors. Retrieved 2019-07-24.
  11. ^ Swedroe, Larry (2018-07-12). “Deconstructing the Low Volatility/Low Beta Anomaly”. Alpha Architect. Retrieved 2019-07-24.