Smart beta indices are a popular way of implementing a factor investing strategy. However, research suggests that this may not the best way, as the factor exposure provided by popular smart beta strategies varies greatly and they do not unlock the full potential of factor premiums.
Asset allocators increasingly consider factor premiums next to traditional asset class risk premiums. This factor investing approach focuses on factor premiums that have been extensively documented in the literature, such as the value, momentum and low-volatility premiums.
A popular way to obtain exposure to these factor premiums is to replicate the performance of smart beta indices. We have investigated how these indices can be used to implement a factor investing strategy. As a starting point we allocate strategically to value, momentum and low-volatility equity factor portfolios and, in addition, to two new factors in the Fama and French 5-factor model, profitability and investment.
We take the value, momentum, profitability and investment portfolios directly from the online data library of Kenneth French. The low-volatility strategy is not provided by Kenneth French and therefore self-constructed, following a similar methodology.
The portfolios are considered on a capitalization-weighted as well as on an equally weighted basis. A simple, equally weighted combination of value, momentum and low-volatility factor portfolios results in a Sharpe ratio of 0.49, versus 0.32 for the market cap-weighted portfolio. The Sharpe ratio can be improved further to 0.58 by using equally weighted instead of cap-weighted factor portfolios. By adding profitability and investment factor portfolios to the mix these Sharpe ratios are not improved further, but information ratios do go up, i.e. market-relative performance improves.
As for the smart beta indices, we use the Russell 1000 Value index and the MSCI Value Weighted index for the value factor. For the momentum factor we take the MSCI Momentum index. For low-volatility we take the S&P Low Volatility index. Indices that specifically target the new profitability and investment factors do not seem to be available, but instead we consider two indices that are quite popular in practice: the MSCI Quality index and the MSCI High Dividend index. For the market portfolio we use the standard index of MSCI.
Table 1 shows how cap-weighted factor portfolios are able to explain the return of smart beta indices, considering the maximum available data history for each index through December 2015. Not surprisingly, most of the performance of the Russell 1000 Value index is attributable to the Value factor portfolio, but its exposure to this portfolio is only 36%. The remaining exposure is attributed to the market portfolio (23%), the Investment factor (21%) and the Low Volatility factor (20%). This implies that the Russell 1000 Value index is not very suitable for investors seeking pure and sizable exposure to the value factor. The MSCI Value Weighted index, which uses fundamental weightings, provides more pure value exposure, but again very little, as 60% of its exposure is attributed to the market portfolio.
Table 1 also shows that a substantial part (73%) of the performance of the MSCI Momentum index is attributable to the Momentum factor portfolio. The remaining weight goes to the market portfolio. The S&P Low Volatility loads heavily on the Low Volatility factor portfolio (71%), combined with a bit of value exposure. These figures suggest that the indices are quite suitable for obtaining momentum and low-volatility factor exposure, but do not offer maximum exposure to these factors.
The MSCI Quality index turns out to load heavily on the Profitability factor portfolio (76%). However, it does not provide exposure to the other new Fama-French factor, Investment, which could be seen as another dimension of Quality. For investors specifically seeking exposure to the Investment factor, none of the smart beta indices considered here appear to be very useful. Interestingly, the MSCI High Dividend index provides a huge (83%) exposure to the Low Volatility factor portfolio, and next to that some value exposure.
Although the MSCI High Dividend index outperforms its replicating portfolio of factor strategies with over 1% per annum, the outperformance is statistically insignificant, which implies that there is insufficient evidence for added value beyond classic low-volatility and value factor exposure. The performance of the other smart beta indices is also in line with their factor replication portfolios. The one exception is the S&P Low Volatility index, which shows an economically large (over 2% per annum) and statistically significant outperformance. This outperformance disappears entirely though if we also include equally-weighted factor portfolios in the analysis, as shown in Table 2. In this case we find 84% exposure to the equally-weighted Low Volatility factor portfolio, plus another 8% exposure to the value-weighted Low Volatility factor portfolio, and a performance difference which is close to zero.
From Table 2 we can also conclude that most of the performance of the other smart beta indices is not attributable to equally weighted factor portfolios, since most of the weight still goes to the cap-weighted factor portfolios. As equally-weighted factor portfolios show a better performance than cap-weighted ones, this suggests that smart beta indices may not unlock the full potential offered by factor premiums.
The main finding of our research 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 out that the amount of exposure they provide to that factor can differ a lot. Many smart beta strategies do not offer maximum factor exposure, but still contain a significant amount of market index exposure as well, or some unexpected exposures to other factors.
Smart beta indices may not unlock the full potential of factor premiums, because in most cases they seem to be exposed to cap-weighted factor strategies, while equally-weighted factor strategies are known to generate higher returns. Altogether, these results imply that smart beta indices may be used to harvest generic factor premiums, but also that it is crucial to properly understand the characteristics of these indices in order to obtain the desired amount of exposure to each particular factor, and the intended portfolio risk-return profile.
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