Low-Volatility Reflections David Blitz, Ph.D.

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David Blitz, Ph.D. For professional investors 1

Agenda > The academic debate: can low-vol be explained by other factors? > The practical side: designing the optimal low-vol strategy > Generic low-vol indices: concerns and pitfalls 2

Low volatility is not explained by value An inconvenient truth? > Value seems to explain US low-vol after 1963 My response: > Not before 1963. > Not after 1984. > Not in the small-cap segment of the market. > Not outside of the US. In short, hardly ever. Source: The Value of Low Volatility, by David Blitz (Journal of Portfolio Management, 2016) 3

Low volatility is not explained by profitability The criticism (Fama & French; Novy-Marx): > Asset pricing models that include a profitability factor resolve the low-vol anomaly My response: > If that were true, high (low) beta portfolios should have high (low) returns, as long as we control appropriately for profitability > Fama-MacBeth output can be interpreted as returns on portfolios with unit exposure to one factor, while being (ex ante) neutral towards other factors > We find that market beta is unpriced in the crosssection, whether we control for profitability or not Source: The Profitability of Low Volatility, by David Blitz & Milan Vidojevic (working paper, 2016) 4

Low volatility is not explained by interest rate risk The criticism: > Low-vol stocks are bond-like stocks (Baker & Wurgler, 2012) > This feature explains 20-80% of the alpha (Driessen, Kuiper & Beilo, 2016) My take: > Excess bond beta times bond risk premium explains just 20% of the alpha > They only get to 80% by assuming that beta in the cross-section is rewarded like the CAPM predicts, forcing the mispricing to end up in the bond factor 5

Agenda > The academic debate: can low-vol be explained by other factors? > The practical side: designing the optimal low-vol strategy > Generic low-vol indices: concerns and pitfalls 6

Low-volatility strategy design 1. What should be the objective? A. Minimizing volatility B. Maximizing risk-adjusted return 2. Should you also include low-correlation stocks with high volatility? A. Yes, if these help to minimize volatility at the portfolio level B. No, because the alpha is in low-vol stocks, and not in low-correlation stocks 3. Should you also incorporate other factors, such as value and momentum? A. No, keep it pure B. Yes, select low-vol stocks that are also attractive on other proven factors 7

Low-volatility strategy design (cntd.) 4. Should you constrain country and sector weights? A. Yes, tightly, like in the MSCI Minimum Volatility indices B. Yes, but not so tightly C. No, not at all, like in the S&P Low Volatility indices 5. How much turnover do you need to efficiently capture the low-vol premium? A. 20% B. 50% C. 100% 8

Low-volatility strategy design (cntd.) 6. Does the optimal low-vol portfolio have a small/mid-cap bias? A. No, because small/mid-caps typically have higher volatility B. Yes, because there are plenty of small/mid-caps with low volatility, and because the opportunity set provided by large-caps is limited 7. Is the optimal low-vol portfolio base-currency dependent? A. Yes, optimize using open currencies (and the resulting home-market bias makes sense) B. No, create base-currency agnostic low-vol portfolios (and manage FX risk separately, e.g. with a hedge overlay) 9

Agenda > The academic debate: can low-vol be explained by other factors? > The practical side: designing the optimal low-vol strategy > Generic low-vol indices: concerns and pitfalls 10

Low-vol indices ETFs on low-vol indices are growing rapidly > AuM over 35 bln nowadays Concerns with low-vol indices > Methodological choices (see previous section) > Inefficient use of available liquidity, by trading just twice a year > Vulnerable to overcrowding: how many investors are buying the same stocks? > Vulnerable to predatory trading: we find evidence of price pressure on stocks entering and leaving the index around rebalancing days 11

Return of stocks entering MSCI MinVol indices Source: Price Response to Factor Index Decompositions, by Joop Huij and Georgi Kyosev (working paper, 2016). Results are calculated for MSCI Minimum Volatility USD indexes, returns are in USD. The graphs show the average cumulative outperformance and abnormal volume of new over all constituents in the MSCI Minimum Volatility indexes during Sep-2010 Dec-2015. AD is announcement day, ED is effective day 12

Outlook coming years > Many academics will remain skeptical with regard to the low-vol anomaly > A lot more money is going to flow into low-vol strategies > Low-vol can deliver alpha despite elevated valuations > There is interest rate risk present in low vol, but this is a tail risk > Realization that active low-vol strategies can have higher capacity than passive low-vol indices > Sooner or later there will be a shake-out, which only managers with superior strategies and committed clients will survive 13