‘Smart Beta’ Looks Like Expensive Beta

June 08, 2015


Factors Are Explainers Of Variance, Not Predictors Of Value

Researchers seeking to explain fund performance have identified up to 300 factors that can independently explain historical investment risks of a portfolio. In effect, each of these is a dimension that an individual investment is assessed on, like price-to-earnings ratio.


A fund is then assessed in terms of its exposure to these factors, and its performance deviation from a passively managed equal factor portfolio.


While factors help explain why a given fund performed a certain way, factors are not necessarily good predictors of future performance. Nor are they necessarily a compensated risk premium, a key difference discussed in a recent Vanguard white paper.


There are many risks you could take on that don’t have a positive expected risk premia. Lotteries, casinos and currency risk are good examples. Just because they explain variance doesn’t mean they’re attractive.


They’re All Factors, Anyway

So it’s important to understand that a market-cap portfolio is a factor portfolio. It just takes on the market allocations of each factor. Investing in “smart” beta portfolios means the manager overweights some factors and underweights others. Some of these may be static overweights, while others may be dynamic, depending on the market cycle.


However, while the jury is still out on whether actual implementations successfully produce alpha, most evidence implies they don’t.


Implementation Issues

A real investment fund is different from the theoretical ideal of an index. For investments where the precision of managing to the index matters, and the expected alpha of the fund is small, implementation costs can swamp alpha.


Proponents of smart beta claim they are simply applying the teachings of financial economists who have found return predictors other than market beta. While we don’t quibble with their findings, it’s another issue entirely whether those predictors continue to hold in such a way that they can be used to generate outperformance in a fund after fees, taxes and implementation.


Issue 1: Is smart beta just an expensive way of getting high beta?

Consider the below graph that compares a long-running smart-beta fund RSP, which equal-weights stocks in the S&P 500 versus an S&P 500 Index tracker. 



Is it fair to say RSP has outperformed? Its cumulative returns are definitely higher. But its declines are also steeper. By equal-weighting stocks, the fund has overweighted (in a very simple manner) to smaller-cap stocks relative to market cap. This is often a simple way of taking on more risk, with a similar outcome to using leverage.


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