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Based on my experience with low (or minimum) volatility research and actually running low-volatile equity portfolios for our clients I’ve summarized ten important things which potential investors should know about minimum volatility investing.
1. The minimum volatility portfolio (MVP) exists only theoretically. In practice, the MVP can only be determined historically (ex post) for a specific sample and return frequency. Therefore different MVPs co-exist, all aiming to reduce and minimize future volatility (ex ante). In general most MVPs have high average exposures to low-volatile stocks and to low-beta stocks.
2. MVPs achieve risk reduction of about 33%. Risk reduction varies between 20% to 45% across historical samples and economic regimes. Interestingly, risk reduction is higher when market volatility is higher. Since equity risk is the most important risk factor for most portfolios, MVPs provide a huge opportunity for significant downside risk reduction. This is achievable while maintaining full exposure to the equity risk premium in the long run.
3. MVPs are a relatively new phenomenon, but the first documented alphas were found in low-beta stocks as early as the 1970s. This low-beta anomaly was discovered many years before the valuation and momentum effects were documented, and just a few years after the Capital Asset Pricing Model (CAPM) was developed.
4. MVPs' alpha is not the result of a magic formula, but is instead driven by persistent behavioral effects causing markets to be inefficient. Explanations given in the growing literature for a structural alpha in low-risk stocks are: (1) a focus on tracking error instead of total risk by an increasing number of market participants. From this perspective low-risk stocks are high-risk and therefore unattractive. (2) Many investors are unwilling or not allowed to apply leverage in their portfolios. All else being equal, more balance sheet leverage leads to a higher expected equity return, and hence return-seeking investors tend to prefer stocks with high risk. (3) The lottery-ticket effect. A large number of risk-seeking investors buy volatile stocks to get rich quickly. (4) Attention bias. Stocks of companies which are in the news generate attention. This notice most often motivates investors to buy instead of to sell, since most investors own only a limited number of stocks and cannot easily sell a stock they do not own. (5) The winner's curse. With asymmetric information, the highest bidding buyer often pays more for a stock than its true intrinsic value. The winner's curse applies more to high-volatile stocks than to low-volatile stocks.
5. An MVP can be constructed based on varying degrees of dependence on estimated correlations with common risk factors. The approaches vary between sorting stocks on total return volatility (no correlation dependence) and estimating for each stock the joint sensitivity to ten or more risk factors (full correlation dependence). In practice hybrid approaches are commonplace. Either by limiting the number of risk factors and/or by putting limits on the estimated betas. This is done in order to avoid the “maximizing errors” problem, which tends to produce inefficient portfolios which require a lot of turnover. Academic research suggests that both approaches tend to produce similar levels of risk reduction, with slightly better results for the approach with a low dependence on estimated correlations. Mutual fund data suggests that the currently available low volatility products are all successful in significantly reducing downside risk.
6. MVPs can also outperform during bull markets. A common misconception is to think that MVPs' low-beta is a perfect prediction of future return. Thus if markets are expected to go up, MVPs will underperform. In other words, the Capital Asset Pricing Model holds true. If this were the case, however, then MVPs would not contain alpha in the first place. This reasoning would further imply that every investor with a bullish view on equities in general should not buy into MVPs, but prefer only high-beta cyclical stocks and every investor with a more bearish view should abandon equities altogether.
7. MVPs generate huge tracking errors of 6-12% when compared to traditional market-capitalization weighted indices. But for other investment solutions which aim to reduce downside risk, such as put options, CPPIs or managed volatility, nobody calculates the tracking errors. To stretch this argument to the extreme, consider a stock which generates a certain 10% each year. For this stock the tracking error is equal to equity volatility of about 20%, but who would care?
8. MVPs exhibit time-varying style exposures. MVPs had a value bias in 2006-2007, but turned to growth in 2008- 2009. On average, value stocks tend to have lower risk, but since risk of value stocks tends to increase during recessions, MVPs are sometimes tilted to growth stocks, especially around economic bad times. One could also say that value has a time-varying beta, which rises during bad times, such as recessions, and declines during good times.
9. MVPs tend to have somewhat higher correlation with bonds. Typically when bond yields go down, low volatility stocks tend to outperform. This feature is particularly interesting for pension funds aiming to stabilize their coverage ratios. Since a falling bond yield tends to decrease the coverage ratio, MVP could be used as an indirect hedge.
10. The alpha of a MVP is very difficult to arbitrage away, in contrast to better known alphas such as valuation and momentum. To catch the alpha in the low-volatile segment of the stock market, either the market capitalization benchmark should be completely abolished and ignored, or the Strategic Asset Allocation (SAA) framework should be adjusted and include a separate style allocation to MVPs. In contrast to other alphas, the effect is also strong within large-cap stocks, stable across regions and has become stronger over the last few decades. I therefore believe that low volatility is a strong and significant anomaly that will continue to generate returns for a long time to come.
1 For evidence see Black, Jensen & Scholes (1972) and Fama MacBeth (1973) during the pre-1969 period and Fama and French (1992) and Haugen and Baker (1991) during the 1963-1990 period. More recently, Clarke et al (2006) and Ang et al (2006) and Blitz and Van Vliet (2007) provide further evidence, also for non-US markets.
2 Examples are Acadian Asset Management, Analytics Investors, Robeco Asset Management, State Street, Unigestion.