Scientific Beta

The latest Scientific Beta special issue of the Research Insights supplement to IPE first introduces a new approach to equity investing termed ‘smart factor investing,’ arguing that current smart beta investment approaches only provide a partial answer to the main shortcomings of capitalisation-weighted indices. It also looks at the major subject of risk allocation with smart factor indices, conducting a case study with factor exposure constraints. The supplement then describes how to ensure the investability of smart beta indices by managing turnover control and capacity constraints, and examines the robustness of smart beta strategies by defining this robustness according to two dimensions. Finally, it provides a brief overview of equity factor index offerings from major index providers.

We first introduce a new approach to equity investing termed ‘smart factor investing,’ arguing that current smart beta investment approaches only provide a partial answer to the main shortcomings of capitalisation-weighted indices. The article assesses the benefits of simultaneously addressing the two main shortcomings of cap-weighted indices – undesirable factor exposures and heavy concentration – by constructing factor indices that explicitly seek exposures to rewarded risk factors while diversifying away unrewarded risks. The results suggest that such smart factor indices lead to considerable improvements in risk-adjusted performance. These smart factor indices are not the end point for investing in equities in a smart way, but instead the starting point, ingredients to construct smart beta allocation solutions while respecting risk objectives that can be expressed in absolute or relative terms. This first article provides a panorama of solutions that have been the subject of a considerable research effort conducted by EDHEC-Risk Institute with the support of Amundi ETF & Indexing.

On the major subject of risk allocation with smart factor indices, we conduct a case study with factor exposure constraints in a second article. We show, importantly, that it is possible to perform risk parity in the long-only world – ie, to have an exposure that is equal in terms of risk factors rewarded over the long term without necessarily having pure or orthogonal factors that are impossible to obtain in the long-only space. This point is all the more important in that often, under the pretext of purity, investors choose excessively concentrated factor indices that contribute neither purity nor diversification and therefore have a fairly low risk-adjusted return. Our argument is that by using well-diversified investable proxies for each factor (the Scientific Beta smart factor indices), it is possible to implement high-performance allocation between these indices while respecting factor risk parity constraints.

Finally, again as part of our solutions for allocating to smart beta, we find that value can be added through relative equal risk contribution and relative global minimum variance at the allocation stage, for investors with a tracking error budget. As a result, extremely substantial levels of risk-adjusted outperformance (information ratios) can be achieved even in the absence of views on factor returns.

Naturally, the question that all investors pose for an innovative solution is its investability. The objective of the fourth article is to describe how to ensure the investability of smart beta indices by managing turnover control and capacity constraints. Investing in smart beta indices requires investors to have access to solutions where implementation costs and liquidity risks are thoroughly considered. A key implication is that the smart beta index turnover and capacity constraints need to be methodologically and carefully handled through the construction of the index.

The results presented in this supplement are sufficiently impressive for investors to raise the question of their robustness. We examine the robustness of smart beta strategies by defining this robustness according to two dimensions. The first – termed relative robustness – corresponds to the capacity for a smart beta index exposed to clearly identified systematic risk factors to always be exposed to the same outperformance compared to the return given by the market for that, or those, factor(s). Relative robustness can be improved by reducing all sources of unrewarded risks with the use of a consistent framework, robust parameter estimation techniques, weight constraints, and strategy-specific risk. The second dimension – which we refer to as absolute robustness – raises the question of the capacity of the smart beta index to outperform the market whatever the time period, or more specifically, whatever the market regimes or returns associated with such and such a systematic risk factor. Robustness can be achieved through allocating across several rewarded factors. Our results show that single factor indices have a high degree of relative robustness, but they are not robust in absolute terms. Multi-beta allocations, on the other hand, are highly robust in absolute terms.

To conclude this special issue, we provide a brief overview of equity factor index offerings from major index providers. Factor indices aim to provide explicit exposure to a common risk factor to harvest its long-term risk premia.