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.