February 14, 2012
Digging deeper into the results
Further calculations can better isolate the positive effects of low-beta and low-volatility and help investors choose among the various ETF alternatives.
Because the low-volatility and low-beta equity portfolios have lower risk than the parent indices from which they are built, their performance benefit is not entirely apparent. What we really want to see is the degree of outperformance between the low-beta or low-volatility strategies and the baseline indices when the risks are the same. To make this comparison, we can use hypothetical leverage to assign each of the strategies the same risk level.
If we were to use leverage to bring the risk of the portfolio of the top-40 holdings of SPLV to a level equal to that of the S&P 500, for example, the additional expected return of the leveraged portfolio is projected to be 2.1% per year. This calculation shows up as Risk-Equivalent Excess Return in the table below.
Projected risk and return of top 40 fund holdings
Presenting the data this way aims to make it even easier to see that the QPP results are consistent with what Baker et al. found: There is a persistent performance advantage from low-beta and low-volatility portfolios, and this advantage is stronger for low-beta portfolios than for low-volatility portfolios. While Risk-Equivalent Excess Return provides a consistent way to see these advantages of the low-beta and low-volatility effects, the calculation using leverage is not to suggest that advisors will, or should, use leverage. Rather, it is to show the expected outperformance of low-beta and low-volatility strategies on a consistent basis.
These data also answer an important question most investors will have: How to choose among the various ETF options? Specifically, they suggest that the best way to exploit the low-volatility and low-beta anomalies is to use SPLV. The S&P low volatility strategy has a number of benefits, including simplicity in construction and expected lower turnover. The portfolio of top holdings also has the lowest overall beta with respect to the S&P 500. Another attractive ETF is the low-beta Russell 2000 fund (SLBT). While the more complex methodology and higher potential turnover in this fund are a concern, the high risk-equivalent return benefit for this fund and its low beta are encouraging signs that this fund will be able to reliably exploit the low-beta anomaly going forward.
The real deal
Not only do my Monte Carlo simulations support the findings of Baker et al., they actually take them a step further – the data suggest that one need not even assume low-beta and low-volatility stocks will be underpriced on an individual basis going forward. The advantage the QPP simulation discerns results directly from the portfolio effects of diversification.
This anomaly is real, and there’s real reason to believe it’s not going away. Baker et al. and other researchers have increasingly mounted a persuasive case that the outperformance of low-beta stocks is both a real and persistent phenomenon, and their proposed mechanism comprehensively explains why it is likely to remain viable in the future.
The ETFs that now exploit these anomalies are the real deal as well. The low-beta stocks, and to a lesser-extent their low-volatility counterparts, that make up these ETFs should outperform, on a risk-adjusted basis, the S&P 500, Russell 1000 and Russell 2000 indices.
Investors and their advisors are typically not constrained by needing to track a specific equity benchmark, and there’s no reason they shouldn’t exploit that powerful built-in advantage. The new ETFs in this space provide the simplest, lowest-cost way to do so. But some attention must be paid to aggregate risk targets. The S&P Low Volatility Index, after all, still has lower expected return than the S&P 500.
Those who substitute the S&P Low Volatility ETF for an allocation to the S&P500 can, however, adjust the total portfolio risk levels to maintain risk targets by adding higher allocations to other risky asset classes, such as emerging markets, REITs, technology stocks, or commodities. An even easier alternative: If an equity allocation’s risk is reduced (by substituting low-beta or low-volatility ETFs in place of market-cap weighted index funds), compensate by simply increasing the allocation to equities as a percentage of the total portfolio.
In the end, there’s little excuse not to embrace this approach. Both historical analysis and forward-looking simulations support the viability of this powerful effect, and the underlying mechanisms proposed by Baker et al. provide further confidence that low-beta and low-volatility equity portfolios will continue to provide substantial benefits. Faced with this preponderance of evidence, even the most hardened skeptic should be asking – isn’t it time I exploited “the greatest anomaly in finance”?
Display article as PDF for printing.
Would you like to send this article to a friend?
Remember, if you have a question or comment, send it to .
