Smart beta or factor-based exchange traded funds promise to produce enhanced returns and diminish portfolio risk. It is also just as important to understand how the smart beta strategies produce their end result and identify the main drivers of return.
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"To get under the hood of a multifactor fund’s return drivers, and gauge their sensitivities, start by regressing the multifactor excess returns on the single factor excess returns, but be aware of the subtleties around this approach," Robert Bush, ETF Strategist for Deutsche Asset Management, said in a research note.
Bush argued that investors should start by regressing a fund's excess returns on a number of single factors to determine the right factors that explain the excess returns and what are the sensitivities that affect the factor.
Smart beta or strategic beta exchange traded funds are based on customized indices that screen for specific factors instead of weighting components based on market capitalization. If one selects a multi-factor smart beta ETF strategy, they may be exposed to numerous factors that could affect the outcome of their investment. Consequently, investors should carefully consider the effects of these factors on their ETF investments.
To provide a clearer picture on the effects of these factors, Bush regressed the daily excess returns of the FTSE Russell Comprehensive Factor Index, the underlying benchmark for the popular Deutsche X-trackers Russell 1000 Comprehensive Factor ETF (NYSEArca: DEUS), for the five single factors that the index incorporates, including value, size, momentum, low volatility and quality.
Through the regression, Bush provided a base line, pointing out that the proportion of variability in excess return is explained by the five factors, or overweighting company stocks based on these five factors do indeed provide what you'd hope for.
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If investors were to run a regression on fewer than five factors or be exposed to an investment with fewer than those five factors, the results may sometimes be significantly different. For example, Bush offered an analogy to basketball. If we determined that how tall a person is affected free-throw percentages, height would be considered a beta or factor, which can then be combined with number of years of experience as another factor. So by comparing the results of just height to height and experience, we would be getting different outcomes. If we add in more factors, the results would become increasingly more complex in determining the outcome.
Bush also warned that on the topic of changing betas, regression will also be sensitive to the definition of the explanatory factors - investors will be exposed to different sensitivities depending on who determines the factors and how they define them. No two smart beta index providers may offer similar or unified definitions on a factor.
The results based on differences in definition will provide results "probably directionally similar, but different," Bush said. "Unfortunately, there's no easy solution to that problem. Using the definitions of a reliable third party system is one option, as is simply regressing on the proprietary definition and being aware of the limitation."
Lastly, while absolute beta size is important, the likely values of the factors are also as significant. Investors should care about an investment's sensitivity to a factor but also care about the excess return to the factor as well.
"To round out our basketball analogy, it would be like asking your 1000 players to specify if they have played in the NBA," Bush added. "The chances are that if they answer yes, then that will have a very powerful impact on their free throw percentage (high beta), but if very few answer yes that was not a great factor to have added to your model."
Investors who are seeking to better understand their smart beta investments should carefully consider the various factors that go into their ETF strategies and keep in mind the sensitivities or slightly varying influences they may have on their overall return.
This article was provided courtesy of our partners at etftrends.com.