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To Win with 'Smart Beta' Ask If the Price is Right

Authors: Robert D. Arnott; Noah Beck; Vitali Kalesnik;

To Win with 'Smart Beta' Ask If the Price is Right

Abstract

In our paper — “How Can ‘Smart Beta’ Go Horribly Wrong?” — we show, using U.S. data, that the relative valuation of a strategy (in comparison with its own historical norms) is correlated with the strategy’s subsequent return at a five-year horizon. The high past performance of many of the increasingly popular factor tilt and so-called smart beta2 strategies came, in large measure, from rising valuations. These excess returns are an “alpha mirage” attributable to the strategies’ becoming more expensive relative to the market. Even the statistical significance of past performance was an illusion driven by rising relative valuation levels! Today, only the value category shows some degree of relative cheapness, precisely because its recent performance has been weak. Over the past half-century, almost all of the eight factors and eight smart beta strategies we study exhibit a negative relationship between starting valuation and subsequent five-year performance. Today, valuations of many of the most popular factors and smart beta strategies are well above their historical norms, forecasting lower future returns. Our findings are robust for both factors and smart beta strategies across horizons out to five years, using both a simple price-to-book ratio and an aggregate valuation measure, in U.S., developed ex U.S., and emerging markets.

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Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
9
Average
Top 10%
Top 10%
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