S&P Dow Jones Indices has long provided a great service to investors with its semi-annual S&P Indices Versus Active (SPIVA) scorecards. The evidence offered in these reports has shown time and again that, regardless of the asset class, the vast majority of active managers persistently fail to outperform their benchmarks, and that there is little to no persistence of performance beyond the randomly expected.
Thus, while we know that there will almost certainly be some small percentage of active mutual fund managers who will outperform in the future, being unable to use past performance as a predictive metric means there is no reliable way to identify them ahead of time.
S&P Dow Jones Indices recently produced a new study that looks not just at the returns of actively managed funds, but also at their volatility (one measure of risk). One purpose of the study was to test whether past volatility was predictive of future volatility. The following is a summary of the author’s findings:
Summary
The bottom line is that the evidence shows investors were not able to improve their returns relative to the market either by investing in higher-volatility actively managed funds (taking more risk) or by investing in low-volatility actively managed funds. In other words, the study provides further evidence that active management is a loser’s game; while it’s a game that’s possible to win, the odds of doing so (especially for taxable investors) are too low to make playing a prudent decision.
This commentary originally appeared November 2 on MutualFunds.com
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The opinions expressed by featured authors are their own and may not accurately reflect those of the BAM ALLIANCE. This article is for general information only and is not intended to serve as specific financial, accounting or tax advice.
© 2016, The BAM ALLIANCE
CAPM was the first formal asset pricing model. Market beta was its sole factor. With the 1992 publication of their paper, “The Cross-Section of Expected Stock Returns,” Eugene Fama and Kenneth French introduced a new-and-improved three-factor model, adding size and value to market beta as factors that not only provided premiums, but helped further explain the differences in returns of diversified portfolios.
But financial innovation didn’t end there. Today the literature contains more than 600 investment factors, a number so great that John Cochrane called it a “zoo of factors.” However, as my co-author Andrew Berkin and I explain in our recently released book, “Your Complete Guide to Factor-Based Investing,” only a small number of exhibits within this factor zoo are required to explain almost all the differences in returns between diversified portfolios.
To be considered worthy of investment, a factor should not only provide a premium and add explanatory power, it should also meet all of the following criteria. It should be:
Factors Aren’t In Lockstep
Academic research has provided investors with a number of factors that meet all the criteria. In addition to market beta, size and value, we can add the equity factors of momentum and profitability/quality. With this knowledge, we can build rules-based portfolios that provide us with systematic exposure to multiple unique factors, each with low correlation to the others.
This low correlation provides diversification benefits, which are important because all factors have experienced long periods of underperformance. However, importantly, they have not all experienced periods of underperformance simultaneously.
A good example of the diversification benefits that factors can provide can be seen by examining value and momentum. From 1964 through 2014, their annual correlation was -0.20. The negative correlation should be expected almost by definition. Consider that when a stock’s price increases, it gains momentum (as long as its price is rising faster than others) while at the same time becoming less “valuey” because it grows more expensive relative to earnings, book value or other fundamental metrics.
Similarly, momentum has been negatively correlated to the size factor. Another example is that profitability/quality has been negatively correlated (-0.27/-0.52) with market beta because investors favor quality in times of uncertainty.
The academic evidence has led to a great increase in interest in constructing portfolios that have exposure to multiple factors. That, in turn, leads to the question of how to best build a portfolio. Is it better to create a portfolio using individual, single-factor components (thinking of them as “building blocks”), or is it better to build a multifactor portfolio from the security level (where scoring or ranking systems are used to select securities)? It should be intuitive that the latter approach, a bottom-up one, is superior.
One reason for this is that, if you use the component approach, you will have one factor-based fund buying a stock (or group of stocks) while another factor-based fund will be selling the same stock (or group of stocks).
For example, if a stock (or an entire sector) is falling in price, it might drop to a level that would cause a value fund to buy it while a momentum fund would be selling the very same security. Investors would thus be paying two management fees and also incurring trading costs twice, without having any impact on the portfolio’s overall holdings.
In Support Of Bottom-Up Approaches
Support for factor-based investing strategies was provided by Antti Ilmanen and Jared Kizer in their 2012 paper, “The Death of Diversification Has Been Greatly Exaggerated.” The paper, which won The Journal of Portfolio Management’s award for the best paper of the year, argued that factor diversification has been more effective at reducing portfolio volatility and market directionality than asset class diversification.
Jennifer Bender and Taie Wang, authors of the 2016 study “Can the Whole Be More Than the Sum of the Parts? Bottom-Up versus Top-Down Multifactor Portfolio Construction,” which appears in a Special QES Issue of The Journal of Portfolio Management, examine which of the two approaches is more efficient.
The authors observe that the bottom-up approach would seem to be a better one because the portfolio weight of each security will depend on how well it ranks on multiple factors simultaneously, while the approach combining single-factor portfolios may miss the effects of cross-sectional interaction between the factors at the security level. The study used the equity factors of value, size, quality, low volatility and momentum, from which the authors built global portfolios from developed markets.
Lower Volatility
Bender and Wang found that the bottom-up portfolio returns were higher than any of the underlying individual component factor returns and higher than the combinations. Additionally, volatility of the bottom-up portfolio was significantly lower.
For example, over the period January 1993 through March 2015, the combination portfolio was able to return 11.14%, versus 12.13% for the bottom-up portfolio, while exhibiting higher volatility (an annual standard deviation of 14.86% versus 13.97%). As a result, the risk-adjusted return increases from 0.73% for the combination portfolio to 0.84% for the bottom-up approach.
They also found that “the bottom-up approach consistently produced better performance over the combination approach in all periods.” Bender and Wang concluded “there are, in fact, beneficial interaction effects among factors that are not captured by the combination approach. Both intuition and empirical evidence favor employing the bottom-up multifactor approach.”
Portfolios that provide exposure to multiple factors allow investors to diversify their holdings in more efficient ways than were previously available. And the theory and evidence demonstrate that the bottom-up approach is the more efficient way to construct a portfolio of factors.
This commentary originally appeared November 4 on ETF.com
By clicking on any of the links above, you acknowledge that they are solely for your convenience, and do not necessarily imply any affiliations, sponsorships, endorsements or representations whatsoever by us regarding third-party Web sites. We are not responsible for the content, availability or privacy policies of these sites, and shall not be responsible or liable for any information, opinions, advice, products or services available on or through them.
The opinions expressed by featured authors are their own and may not accurately reflect those of the BAM ALLIANCE. This article is for general information only and is not intended to serve as specific financial, accounting or tax advice.
© 2016, The BAM ALLIANCE
Larry Swedroe discusses his new book, “Your Complete Guide To Factor-Based Investing,” as well as the theory behind factor strategies and how investors can achieve their risk and return objectives through them, in a recent Q&A.
By clicking on any of the links above, you acknowledge that they are solely for your convenience, and do not necessarily imply any affiliations, sponsorships, endorsements or representations whatsoever by us regarding third-party Web sites. We are not responsible for the content, availability or privacy policies of these sites, and shall not be responsible or liable for any information, opinions, advice, products or services available on or through them.
The opinions expressed by featured authors are their own and may not accurately reflect those of the BAM ALLIANCE. This article is for general information only and is not intended to serve as specific financial, accounting or tax advice.
© 2016, The BAM ALLIANCE