Scientific Beta

The latest Scientific Beta special issue of the Research Insights supplement to IPE first seeks to provide an effective response to the traditional criticism of cap-weighted indices through smart factor risk allocation. It also discusses smart factor indices, presenting an analysis using US long-term track records and looking at their performance in other developed economies and in the global developed stock universe. The supplement then analyses the potential benefit of combining factor tilts, and examines the extreme risk of cap-weighted and smart beta indices. Finally, it looks at factor investing in the equity space.

In our first article, we seek to provide an effective response to the traditional criticism of cap-weighted indices, which are both poorly diversified, because they are highly concentrated in a small number of large-cap stocks, and exposed to poorly-rewarded risk factors such as large and growth stocks. EDHEC-Risk Institute’s research on the concept of smart factor risk allocation involves offering both the ingredients and allocation methods to benefit from the diversification offered by smart beta weighting schemes, which reduce the unrewarded or specific risks, and to make an efficient allocation to systematic or rewarded risk factors.

We then discuss smart factor indices. We construct smart factor indices by using diversified multi-strategy weighting on characteristics-based half universes – small size, high momentum, low volatility, and value. In this way, investors can i) manage systematic risks through explicit stock selection; and ii) diversify away strategy-specific risk by combining different strategies. The smart factor indices that result from this framework show pronounced improvements in risk-adjusted performance compared to cap-weighted factor-tilted indices. Such smart factor indices thus provide suitable building blocks for the implementation of static or dynamic factor allocation decisions.

Having analysed smart factor indices using US long-term track records, we look at the performance of smart factor indices in other developed economies and in the global developed stock universe. Our results thus complement the long-term US data analysis and provide an assessment of the performance consistency of the smart factor indexing approach when applying the methodology to different stock universes.

We then analyse the potential benefit of combining factor tilts. Combinations of tilts to different factors may be of interest for two reasons. First, multi-factor allocations are expected to result in improved risk-adjusted performance. Second, investors may benefit from allocating across factors in terms of implementation. Some of the trades necessary to pursue exposure to different factors may actually cancel each other out.

Looking at the extreme risk of cap-weighted and smart beta indices, we ask whether smart beta strategies, which produce better performance and sometimes lower volatility, are more exposed to extreme risk. Our conclusion is that extreme risk across strategies is primarily driven by average volatility or average tracking error, depending on whether we consider absolute or relative returns. It therefore seems essential for long-term investors to focus on volatility or tracking error management on a strategy level.

Finally, we look at factor investing in the equity space. In order to avoid the pitfalls of non-persistent factor premia and achieve robust performance, we suggest that investors keep the following checks in mind. First, they should require a sound economic rationale for the existence of a premium. Second, due to the risks of data-mining, investors would be well advised to stick to simple factor definitions that are widely used in the literature rather than rely on complex and proprietary factor definitions.