Thought Leadership

Optimal blending of smart beta and multi-factor portfolios

There has been extraordinary growth in the use of smart beta funds by institutional investors, both large and small.


Many investors have allocated away from traditional index and active equity funds into multiple smart beta funds based on ideas, such as value, small (size), momentum, quality, and low volatility. They have gone on to combine these smart beta ideas in single multi-factor funds that are claimed to improve efficiency.

It is unlikely, however, that the cumulative exposures of these complex multi-factor investments (collectively known as advanced beta) is truly understood. This is a major problem, given that one of the important potential benefits of smart beta investing is enhanced transparency of expo¬sures and risks. Investors need guidance on how to construct an overall port¬folio that improves the likelihood of attaining better investment outcomes.

The good news is that standard approaches to investment performance analysis and portfolio construction can be adapted to integrate multiple smart beta approaches with other assets. The first step is to understand the underlying exposures of each smart beta strategy and their correlations to other strategies. In this it is important to be explicit about expectations for the performance of each strategy, recognizing that an analyst’s judgment is always required.
Finally, proce¬dures for portfolio construction, built from standard methods, can be used to optimize expected utility for the investor, based on our estimates and judgments.

We have expanded on this approach in a paper for The Journal of Portfolio Management written by Ashley Lester, Head of Multi-Asset Research at Schroders, and Fred Dopfel, Professor at Barowsky School of Business at Dominican University, California. We believe this analysis leaves us better equipped to answer the following questions:

  • How do we discern whether a new smart beta fund may be a valuable addition to the portfolio?
  • When does a multi-factor strategy add value beyond a portfolio of simple factors?
  • What is an efficient portfolio of smart betas and advanced betas?
  • When should smart beta and multi-factor portfolios be combined with traditional indexes?
  • How does the investment policy affect the best allocation to advanced beta?

Our approach is to begin with a framework to assess the potential value-add of advanced beta candidates and to establish forward-looking assumptions. This provides the essential information needed to understand the risk and benefits of combining exposures. Next, we define an objective function that leads to the principles for optimal combinations of smart betas and advanced betas. Finally, we introduce a case study to demonstrate how the methodology can be applied to attain better portfolios.

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Optimal blending of smart beta and multi-factor portfolios


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Optimal blending of smart beta and multi-factor portfolios


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