Over the past decade, low volatility has become a popular investment style. Yet it still raises many questions among investors. New Robeco research paper provides a comprehensive overview on this subject.
High-risk stocks do not generate higher returns than low-risk stocks. Evidence of this phenomenon was first reported in the early 1970s, when the first empirical tests of the Capital Asset Pricing Model (CAPM) showed high-risk stocks earn lower returns than the model predicts1 and that stocks with lower variance achieve higher long-term returns than ‘riskier’ counterparts2.
But do low-risk stocks systematically beat high-risk stocks over time and across geographies? How should low-risk stocks be defined? What drives the low-risk effect? Can investors benefits from this effect in practice? How should they go about it? And then, if a growing number of investors become aware of the low-risk effect, could it end up being arbitraged away?
In a new research paper, released over a decade after the publication of their award-wining study on the volatility effect3, Robeco’s Pim van Vliet and David Blitz, together with Guido Baltussen, take a step back to review the existing academic literature on this subject and provide a comprehensive overview. They also address some of the most pressing questions regarding low-risk investing.
They argue that volatility, that is, the standard deviation of returns, is the main driver of the low-risk anomaly. In other words, the low-risk effect can be likened to a low volatility effect. What’s more, the low volatility effect proves highly persistent over time and across markets, including emerging ones. The effect is also present across sectors and market-capitalization sizes.
The low volatility effect proves highly persistent over time and across markets
The authors then move on to discuss the economic rationale supporting the existence of the low-risk effect and analyze some of the most frequently cited explanations for this phenomenon. For the purposes of this paper, they group these explanations into five main categories: constraints, relative performance objectives, agency issues, skewness preference, and behavioral biases.
Arguing that the low-volatility factor cannot be explained by other factors such as value, profitability or exposure to interest rate changes, the authors find that the published studies which specifically addressed this issue show that other well-known factors can only explain a small part at best of the low-risk effect or the performance over a very specific sub-period.
The paper examines several practical considerations that come into play when investing based on the low-risk effect. For instance, the authors investigate why investors who aim to profit from the low-risk effect typically use a long-only approach. Another important question they address concerns currency risk and how to deal with it.
Low-risk investing requires little turnover
The authors also discuss the optimal amount of turnover needed to capture the low-risk anomaly and argue that low-risk investing requires little turnover. They also stress that volatilities are more important than correlations, that low-risk indices are suboptimal and vulnerable to overcrowding, and that other factors can be efficiently integrated into a low-risk strategy.
Finally, the study looks for tangible evidence that the low-risk effect might already be in the process of being arbitraged away, in particular by investors in mutual funds, exchange-traded funds, and hedge funds. Indeed, the approach is so well-known nowadays, that many investors are concerned that it might become a victim of its own success.
After thorough analysis, however, the authors conclude that there is little evidence that the low-risk effect is being arbitraged away, as many investors are either neutrally positioned or even on the other side of the low-risk trade. Van Vliet et al. therefore reject the idea that the low-risk effect might fade or disappear, at least for now.
1See: Black, F., Jensen, M. C., and Scholes, M. (1972). The capital asset pricing model: Some empirical tests. Studies in the Theory of Capital Markets, 81(3), 79-121. See also: Miller, M. H. and Scholes, M. (1972). Rates of Return in Relation to Risk: A Reexamination of Some Recent Findings. Studies in the Theory of Capital Markets, Praeger, New York, 47-78. See also: Fama, E. F., and MacBeth, J. D. (1973). Risk, return, and equilibrium: Empirical tests. Journal of Political Economy, 81(3), 607-636.
2Haugen, R. A., and Heins, A. J. (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.
3Blitz, D., and van Vliet, P. (2007). The Volatility Effect. Journal of Portfolio Management, 34(1), 102-113.
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