Low-volatility anomaly
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In investing and finance, the low-volatility anomaly is the observation that low-volatility securities have higher returns than high-volatility securities in most markets studied. This is an example of a stock market anomaly since it contradicts the central prediction of many financial theories that higher returns can only be achieved by taking more risk.
The capital asset pricing model (CAPM) predicts a positive and linear relation between the systematic risk exposure of a security (its beta) and its expected future return. However, the low-volatility anomaly falsifies this prediction of the CAPM by showing that higher beta stocks have historically underperformed lower beta stocks.{{Cite journal |last1=van der Grient |first1=Bart |last2=Blitz |first2=David |last3=van Vliet |first3=Pim |date=2011-07-01 |title=Is the Relation between Volatility and Expected Stock Returns Positive, Flat or Negative? |journal=SSRN |language=en |location=Rochester, NY |doi= 10.2139/ssrn.1881503|s2cid=153743404 |ssrn=1881503}} Additionally, stocks with higher idiosyncratic risk often yield lower returns compared to those with lower idiosyncratic risk.{{Cite journal|last1=Ang|first1=Andrew|last2=Hodrick|first2=Robert J.|last3=Xing|first3=Yuhang|last4=Zhang|first4=Xiaoyan|date=2006|title=The Cross-Section of Volatility and Expected Returns|journal=The Journal of Finance|language=en|volume=61|issue=1|pages=259–299|doi=10.1111/j.1540-6261.2006.00836.x|s2cid=1092843|issn=1540-6261|url=http://www.nber.org/papers/w10852.pdf|doi-access=free}} The anomaly is also document within corporate bond markets.{{Cite journal |last=Houweling |first=Patrick |last2=Muskens |first2=Frederik |date=September 2023 |title=The Past, Present, and Future of Low-Risk Corporate Bonds |url=https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4574834 |journal=SSRN |volume=Abstract 4574834}}
The low-volatility anomaly has also been referred to as the low-beta, minimum-variance, minimum volatility anomaly.
History
The CAPM was developed in the late 1960s and predicts that expected returns should be a positive and linear function of beta, and nothing else. First, the return of a stock with average beta should be the average return of stocks. Second, the intercept should be equal to the risk-free rate. Then the slope can be computed from these two points. Almost immediately these predictions were empirically challenged. Studies find that the correct slope is either less than predicted, not significantly different from zero, or even negative.{{Cite journal|last=Fama|first=Eugen|date=1973|title=Risk, return, and equilibrium: Empirical tests|journal=Journal of Political Economy|volume=81|issue=3|pages=607–636|doi=10.1086/260061|s2cid=13725978}} Economist Fischer Black (1972) proposed a theory where there is a zero-beta return which is different from the risk-free return.{{Cite journal|last=Black|first=Fischer|date=1972|title=Capital market equilibrium with restricted borrowing|journal=The Journal of Business|volume=45|issue=3|pages=444–455|doi=10.1086/295472}} This fits the data better. It still presumes, on principle, that there is higher return for higher beta. Research challenging CAPM's underlying assumptions about risk has been mounting for decades. One challenge was in 1972, when Michael C. Jensen, Fischer Black and Myron Scholes published a study showing what CAPM would look like if one could not borrow at a risk-free rate.{{Cite journal|last1=Black|first1=Fischer|last2=Jensen|first2=Michael|date=1972|title=The capital asset pricing model: Some empirical tests|journal=Studies in the Theory of Capital Markets|volume=81|issue=3|pages=79–121}} Their results indicated that the relationship between beta and realized return was flatter than predicted by CAPM. Shortly after, Robert Haugen and James Heins produced a working paper titled "On the Evidence Supporting the Existence of Risk Premiums in the Capital Market". Studying the period from 1926 to 1971, they concluded that "over the long run stock portfolios with lesser variance in monthly returns have experienced greater average returns than their 'riskier' counterparts".Haugen, Robert A., and A. James Heins, (1972) “[https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1783797 On the Evidence Supporting the Existence of Risk Premiums in the Capital Markets]”, Wisconsin Working Paper, December 1972.
Evidence
The low-volatility anomaly has been documented in the United States over an extended 90-year period. Volatility-sorted portfolios containing deep historical evidence since 1929 are available in an [https://www.paradoxinvesting.com/ online data library].{{Cite book|title=High returns from low risk: a remarkable stock market paradox|last1=Van Vliet|first1=Pim|last2=de Koning|first2=Jan|publisher=Wiley|year=2017|isbn=9781119351054|doi=10.1002/9781119357186}} The picture contains portfolio data for US stocks sorted on past volatility and grouped into ten portfolios. The portfolio of stocks with the lowest volatility has a higher return compared to the portfolio of stocks with the highest volatility. A visual illustration of the anomaly, since the relation between risk and return should be positive. Data for the related low-beta anomaly is also [https://www.aqr.com/Insights/Datasets/Betting-Against-Beta-Equity-Factors-Monthly online available]. The evidence of the anomaly has been mounting due to numerous studies by both academics and practitioners which confirm the presence of the anomaly throughout the forty years since its initial discovery in the early 1970s. The low-volatility anomaly is found across sectors, but also within every sector.{{Citation |last1=De Carvalho |first1=Raul Leote |title=11 - Low-Risk Anomaly Everywhere: Evidence from Equity Sectors |date=2015-01-01 |url=https://www.sciencedirect.com/science/article/pii/B9781785480089500113 |work=Risk-Based and Factor Investing |pages=265–289 |editor-last=Jurczenko |editor-first=Emmanuel |access-date=2023-08-18 |publisher=Elsevier |isbn=978-1-78548-008-9 |last2=Zakaria |first2=Majdouline |last3=Lu |first3=Xiao |last4=Moulin |first4=Pierre}} There are multiple examples.{{refn|{{multiref||||{{Cite journal |last1=Ang |first1=Andrew |last2=Hodrick |first2=Robert J. |last3=Xing |first3=Yuhang |last4=Zhang |first4=Xiaoyan |date= 2006|title=The Cross-Section of Volatility and Expected Returns |url=https://onlinelibrary.wiley.com/doi/10.1111/j.1540-6261.2006.00836.x |journal=The Journal of Finance |language=en |volume=61 |issue=1 |pages=259–299 |doi=10.1111/j.1540-6261.2006.00836.x |issn=0022-1082}}||}}}} Besides evidence for the US stock market, there is also evidence for international stock markets. Similar results are found in global equity markets.{{refn|{{multiref|Blitz, David C., and Pim van Vliet. (2007), The Volatility Effect: Lower Risk without Lower Return, Journal of Portfolio Management, vol. 34, No. 1, Fall 2007, pp. 102–113.
SSRN: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=980865|||Blitz, David, Pang, Juan and Van Vliet, Pim, “The Volatility Effect in Emerging Markets” (April 10, 2012). Available at SSRN: http://ssrn.com/abstract=2050863.|Baker, Nardin and Haugen, Robert A., “Low Risk Stocks Outperform within All Observable Markets of the World” (April 27, 2012). Available at SSRN: http://ssrn.com/abstract=2055431|{{cite web|url=http://www.sagepointfinancial.com/sites/sagepointfinancial.com/files/SPF-2-EC-0514-P.pdf|title=Low Risk, High Return? - May 2014 - SagePoint Financial|publisher=SagePoint Financial|url-status=dead|archive-url=https://web.archive.org/web/20150504004103/http://www.sagepointfinancial.com/sites/sagepointfinancial.com/files/SPF-2-EC-0514-P.pdf|archive-date=May 4, 2015}}|{{cite web|url=http://portfolioist.com/2011/07/12/why-low-beta-stocks-are-worth-a-look/|title=Why Low Beta Stocks Are Worth a Look |publisher=Portfolio Investing Blog: Portfolioist|url-status=dead|archive-url=https://web.archive.org/web/20140606062618/http://portfolioist.com/2011/07/12/why-low-beta-stocks-are-worth-a-look/|archive-date=June 6, 2014}}|{{cite web|url=http://www.investingdaily.com/11369/the-greatest-anomaly-in-finance-low-beta-stocks-outperform/|title=The Greatest Anomaly in Finance: Low-Beta Stocks Outperform|publisher=Investing Daily|url-status=dead|archive-url=https://web.archive.org/web/20140531030339/http://www.investingdaily.com/11369/the-greatest-anomaly-in-finance-low-beta-stocks-outperform/|archive-date=May 31, 2014}}}}}}{{Cite journal |last=Steyn |first=Johannes Petrus |last2=Gilbert |first2=Evan |last3=Viviers |first3=Suzette |date=2024-07-02 |title=The low-volatility effect in African frontier equity markets |url=https://www.tandfonline.com/doi/full/10.1080/10293523.2024.2361986 |journal=Investment Analysts Journal |language=en |volume=53 |issue=3 |pages=189–206 |doi=10.1080/10293523.2024.2361986 |issn=1029-3523|doi-access=free }}
Explanations
Several explanations have been put forward to explain the low-volatility anomaly. They explain why low risk securities are more in demand creating the low-volatility anomaly.
- Constraints: Investors face leverage constraints and shorting constraints. This explanation was put forward by Brennan (1971) and tested by Frazzini and Pedersen (2014).Frazzini, Andrea and Pedersen, Lasse (2014). [http://pages.stern.nyu.edu/~lpederse/papers/BettingAgainstBeta.pdf Betting against beta]. Journal of Financial Economics, 111(1), 1-25.
- Relative performance: Many investors want to consistently beat the market average, or benchmark as discussed by Blitz and van Vliet (2007) and Baker, Bradley, and Wurgler (2011).
- Agency issues: Many professional investors have misaligned interests when managing client money. Falkenstein (1996) and Karceski (2001) give evidence for mutual fund managers.
- Skewness preference: Many investors like lottery-like payoffs. Bali, Cakici and Whitelaw (2011) test the 'stocks as lotteries' hypothesis of Barberis and Huang (2008).
- Behavioral biases. Investors are often overconfident and use the representative heuristic and overpay for attention grabbing stocks.{{Cite journal|last1=Blitz|first1=David|last2=Huisman|first2=Rob|last3=Swinkels|first3=Laurens|last4=Van Vliet|first4=Pim|date=2019|title=Media Attention and the Volatility Effect|journal=Finance Research Letters|volume=forthcomin|doi=10.2139/ssrn.3403466|s2cid=198634762|hdl=1765/120091|url=http://repub.eur.nl/pub/120091|hdl-access=free}}
For an overview of all explanations put forward in the academic literature also see the survey article on this topic by Blitz, Falkenstein, and Van Vliet (2014) and Blitz, Van Vliet, and Baltussen (2019).{{Cite journal|last1=Blitz|first1=David|last2=Falkenstein|first2=Eric|last3=Van Vliet|first3=Pim|date=2014|title=Explanations for the Volatility Effect: An Overview Based on the CAPM Assumptions|url=https://papers.ssrn.com/sol3/cf_dev/AbsByAuth.cfm?per_id=113731|journal=The Journal of Portfolio Management|volume=40|issue=3|pages=61–76|doi=10.3905/jpm.2014.40.3.061|s2cid=201375041|url-access=subscription}}{{Cite journal|last1=Blitz|first1=David|last2=Van Vliet|first2=Pim|last3=Baltussen|first3=Guido|date=2019|title=The Volatility Effect Revisited|doi=10.2139/ssrn.3442749|s2cid=202931436}}
See also
References
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