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A sset allocators increasingly consider factor premiums next to traditional asset class risk premiums. Such an approach is known as "factor investing" and typically focuses on capturing factor premiums that have been extensively documented in the literature, such as the value, momentum, and low volatility premiums. Studies advocating factor investing include Ang, Goetzmann, and Schaefer [2009], Bender et al. [2010], Blitz [2012, 2015], and Ang [2014]. In theory, the benefits of factor investing are largest for long-short factor portfolios, which capture pure factor premiums and have a low correlation with asset class risk premiums; see, for example, Ilmanen and Kizer [2012]. In practice, however, factor investing is typically implemented using long-only strategies, which are designed to capture a factor premium on top of an asset class risk premium. A popular way to do so is by replicating the performance of smart beta indices, which use mechanical rules to deviate from the capitalization-weighted market index. These rules tend to result, either explicitly or implicitly, in systematic tilts toward certain factors. Chow et al. [2011] empirically showed that the added value of popular smart beta indices can be attributed entirely to exposures to established factor premiums.
This article investigates how smart beta indices can be used to implement a factor investing strategy. As a starting point, we use the theoretical framework of Blitz [2012], who argued to allocate strategically to value, momentum, and low volatility equity factor portfolios, and Blitz [2015], who also found some added value for the two new factors in Fama and French's [2015] five-factor model--profitability and investment. The factor portfolios considered by Blitz [2012, 2015] are long-only and restricted to the large-cap segment of the market, in order to ensure that they can be implemented on a large scale. The portfolios are considered on a value-weighted as well as on an equal-weighted basis, with the latter showing the best results. We use a returns-based style analysis approach to investigate whether, and to what extent, smart beta indices are able to capture the theoretical returns of these factor portfolios.
The main finding is that factor investing with popular smart beta indices is not as straightforward as one might think. Smart beta strategies typically seem to target one particular academic factor, but it turns...