Factor based equity indices
There has been research analysing the common return drivers within broad equity universes for quite some time. Chen, Roll and Ross (1986) and Fama and French (1993) find that asset returns could be attributed to a few underlying explicit factors such as macroeconomic factors or firm attributes / style factors. These factors represent sources of systematic risk and return. The currently available sector indices or style indices are constructed by the selection of stocks following certain criteria, for instance, industry classification of a stock, or defining criteria for growth and value such as price-to-book ratios of a stock. These dimensions are the ones that have been traditionally used by equity analysts and investment managers. More recently, index providers have started designing indices that reflect not the traditional categories, but rather the factors that have been put forward in empirical finance research as being the most relevant common return drivers. In particular, it has been proposed to achieve a high level of exposure to a particular factor, such as size, value, momentum, volatility, etc., while at the same time, very low exposure to all other factors, through factor-based indices.[1] These indices thus aim at providing relatively precisely defined exposure to factors that may explain differences in stock returns.
A frequently cited motivation for such factor-based portfolios is that excess returns of actively managed portfolios often can be linked, to a large degree, to exposure to such factors. For instance, by analysing the active management fund performance, Ang et al. (2009) find that even for active returns, a significant part is linked to the systematic factors. Hence, they suggest embedding the concepts of factor models to the benchmark construction. In such way, it is easy to identify the source of return and the exposure to risk. Moreover, recently, Melas et al. (2010) present alternative methods to construct factor index tracking portfolios.
Such factor-based indices could provide investors with clearly defined exposures (since the exposure to other factors is very low but not zero). Therefore they may offer the ease to identify the source of risk and prevent the exposure to unexpected risk.
Nevertheless, there is also an open question toward the ways to use these indices. In particular, if investors want to make choices of allocation across different equity factor indices, investors require a view on the risk premium for each factor, which is difficult to estimate. Perhaps, more fundamentally, the usual factor indices correspond to standard factors found to matter in the cross section of stock returns. However, most of these factors are purely empirical in nature – they do not necessarily have an economic explanation. For example, Liew and Vassalou (2000) have shown that unlike some factors which can be understood as predictors of economic growth, the momentum factor, whose importance is strongly confirmed in many data sets, cannot be linked to such an economic explanation of its importance. This implies that momentum may not be related to such intuitive economic risk factors. In addition, there is often a criticism that such factors may have come up as a result of data mining. For instance, Black (1993a, 1993b) argues that Fama/French results were likely an example of data mining. Since there are many studies published before on the possible explanatory variables for stock returns, Fama and French chose three of them which have the highest explanatory power. Cochrane (2001) has pointed out that most empirical studies fish for factors, but such factors are not necessarily backed by sound economic theory.
Thus, while factor-based indices may be an alternative to implement factor tilts through active managers, there are some questions with respect to how they should best be used in practice, as estimation of factor risk premia and economic interpretations of such factors are difficult questions.
[1] The examples of factor-based indices are MSCI Barra Factor Index and Russell Axioma Factor Indexes.
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