Key Points

  • We find slippage between the factor returns realized by mutual fund managers and the theoretical factor returns “earned” by long–short paper portfolios over the period 1991–2016.
  • The source of the slippage appears to be costs related to implementation, such as trading costs, missed trades, expenses of shorting, manager fees, stale prices, bid–ask spreads, and so forth.
  • Our research shows that over the last quarter-century the real-world return for the value and market factors is halved or worse than theoretical factor returns imply, and the momentum factor has provided no benefit whatever to the end-investor. 
  • Our core findings of a return shortfall in real-world factor investing are supported by a series of six robustness checks. 

“Why, sometimes I’ve believed as many as six impossible things before breakfast.”
—The White Queen, from Lewis Carroll’s Through the Looking Glass

This article is the first in a series of articles we will publish in 2017 that demonstrate factor tilts generally deliver far less alpha in live portfolios than they do on paper, or put another way, investment managers generally fail to capture the returns that would be expected based on their factor tilts. We break our research into four parts. In this first article we show that the factor returns realized by fund managers differ starkly from the theoretical factor returns constructed from long–short paper portfolios. Notably, the market, value, and momentum factors are far less rewarding in live fund management than their theoretical long–short paper portfolio returns. 

In our next article, we will challenge the idea that factor tilts—portfolios combining several theoretical factor portfolios—are the same as smart beta strategies. We show using Fundamental Index™, equal weight, and low-volatility strategies as illustrative examples that factor tilts cannot successfully replicate smart beta strategies. Although the factor tilts of these strategies are easy to replicate, the resulting portfolios look very different from the originals, with the replication portfolios having far higher turnover, lower performance, and smaller capacity. 

In a third article, we will show that the relative valuations of factor loadings can give us the courage to buy mutual funds when factor tilts are at their cheapest, hence, the most out of favor. Along with fees, turnover, and past performance—where low fees, low turnover, and low (yes, low!) past performance are predictive of better future returns—factor loadings can help us improve our forecasts of fund returns. We find the best predictor is prior three-year performance, but with the wrong sign: buying the losers is the winningest strategy. 

Finally, a fourth article will take a closer look at momentum, for which we find the realized alpha in live portfolios is essentially zero compared to a theoretical alpha of around 6% a year.  We show why momentum doesn’t work in live portfolios, and also show how momentum can be saved as a useful source of alpha.

In 2016, we published a series of articles that challenged the “smart beta” revolution by pointing out performance chasing in factor tilts and in smart beta strategies can be as damaging as performance chasing in other realms of asset management.1 Relative valuations are negatively correlated with subsequent returns in factors and smart beta strategies in exactly the same way we observe a value effect in stock selection and in asset allocation.

To many readers, the two most surprising revelations in our 2016 series were 1) that many factors owe much, or all, of their historical return to revaluation alpha, meaning that if the strategy has become far more expensive than in the past, its historical efficacy is exaggerated and its future efficacy may evaporate entirely; and 2) that many popular factor tilts and smart beta strategies were expensive relative to their historical norms.2 We found that the value and small-cap strategies were trading cheap relative to history, and that the momentum, gross profitability (quality), and low beta strategies were trading expensive relative to history, implying that the past returns for the former factors were understated (true efficacy was greater than it seemed) and for the latter were overstated (less powerful than they seemed).

Consequently, our findings implied that future returns for the value and small-cap factors were likely to be strong, and those for momentum, quality, and low beta were likely to be weak. This finding of weak expected performance played out in live performance far faster and far more powerfully than we could have anticipated.3 The spread, between the strategies we identified as cheapest and those we identified as most expensive, was well over 1,000 basis points (bps) in the second half of 2016.

In this article, we attempt to measure the slippage between the theoretical factor returns, derived from long–short paper portfolios, and the realized factor returns actually captured by mutual fund managers. We conduct the analysis using both US equity funds and international equity funds. Our primary focus is on US funds for which we show extensive robustness tests to quantify the impact, if any, of changes in estimation methodology or inputs on our results. We find that managers who favor high factor loadings for market beta, value, or momentum generally do not derive nearly as much incremental return relative to low beta, growth, and contrarian funds, respectively, as the factor return histories would suggest. In fact, well over half of the factor return for market beta and for value (HML) disappears, as does essentially all of the momentum factor return. We also explore the potential reasons for these impressive performance shortfalls.

Factor Returns: The Theory
Factors are used to measure manager style, to disentangle style-based performance from skill-based performance, and to build and sell quantitative investment strategies. In addition to the capital asset pricing model, or CAPM, market factor, the value, size, and momentum factors are some of the more popular factors known to academics and practitioners since at least the early 1990s. Using the most common theoretical portfolio definitions, these four factors have shown quite impressive performance: the market, value, size, and momentum factors have delivered 8.2%, 2.6%, 3.6%, and 5.7% return a year, respectively, over the last 26 years! The low beta factor (also known as the betting-against-beta, or BAB, factor) discovered in the 1970s did not garner much popularity until recently, when it delivered an eye-catching 26-year return of 10.3%.4 Other factors that have become popular over the last decade—profitability, investment, and illiquidity—also showed fabulous historical returns of 3.9%, 3.2%, and 2.1% over the past quarter-century.

Such formidable numbers might suggest factor tilts are a ready path to higher returns as well as suggesting which factors are more likely to deliver outperformance going forward, and is the theory widely advanced as fact by a vocal quant community. This theory is also a product of data mining and selection bias. While theories can help advance our understanding of a subject, they are just idealized approximations of the real world built on a foundation of core—and often wrong—simplifying assumptions. No theory can fully capture how the real world works. Worse, the real world frequently presents us with objective facts and outcomes that contradict theoretical predictions.

Factor Returns: Theory Meets Practice
What if some factor returns earned by fund managers are far smaller

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