AMENC Noel

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A recent article by Hunstad and Dekhayser (JII, Summer 2015) introduced a novel measure of factor “purity”—the factor efficiency ratio—and concluded that the indexes analyzed “were generally unable to provide desired factor exposures without taking on substantial unintended exposures” and that indexes are not “pure” in their delivery of intended factor exposures. This note points out several questions regarding the relevance of factor efficiency ratios and similar assessments of purity of factor indexes.

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There has been significant evidence that systematic equity investment strategies (so-called smart beta strategies) outperform the cap-weighted benchmarks in the long run. These strategies are usually marketed on the basis of outperformance. However, it is important to recognize that performance analysis is typically conducted on backtests that apply the smart beta methodology to historical stock returns. Concerning actual investment decisions, a relevant question is: How robust is the outperformance? The issue of robustness, as in extreme risk and performance attribution to well-defined risk factors, is not dealt with by index providers despite investors being wary of robustness of outperformance of various smart beta strategies. This article, with the use of single- and multi-factor indices, examines the causes of, and remedies for, lack of robustness and then provides a framework to evaluate the robustness of various smart beta strategies.

1. Noel Amenc. 1. is a professor of finance at EDHEC Business School, Ceo of Eri Scientific Beta, and the Director of EDHEC-Risk Institute In Nice, France . (noel.amenc{at}edhec-risk.com) . . 2. Lionel Martellini. 1. is a professor of finance at EDHEC Business School, a senior scientific.

Alternative equity indexes are likely to outperform traditional cap-weighted indexes over the long term, research results show that such smart beta strategies are exposed to several types of risk, including systematic risk (e.g., factor tilts), specific risk (related to the assumptions and inputs of a strategy), and relative risk (i.e., the risk of potentially severe underperformance) compared to cap-weighted indexes that can last for extended periods of time. Smart beta can play an important role in institutional investors’ allocations, but only at the price of implementing a genuine risk-management process. This article discusses a new approach to smart beta investing (Smart Beta 2.0) that not only deviates from the default solution of using market capitalization as the sole criterion for weighting and constituent selection, but also analyzes and manages the risks of such deviations.

For the past thirty years, the asset management industry has focused its investments and research on the implementation of active portfolio management strategies based on stock picking and compliance with a relative risk constraint compared to a benchmark, most often represented by a market index. The economic difficulties experienced by the financial markets over the last three years and the appearance of management techniques whose performance is decoupled from that of stock market indices have led asset management professionals to rethink the added value of active management by integrating the benefits of active portfolio allocation. This research reviews the benefits of a multi-style-multiclass approach to strategic and tactical allocation. In terms of strategic allocation, it studies the consequences of decorrelating between management styles, both in the traditional and alternative universe, in order to build minimum risk portfolios, based on a minimum variance portfolio concept. With respect to tactical allocation, she explains the results of research on the econometrics of market reactions in order to set up an econometric forecasting model and a systematic tactical allocation process based on lagged variables. It supports its conclusions with a presentation of the results of research conducted in the area of performance and risk analysis of active portfolio management. In particular, the multi-factor models and style analysis, which are the cornerstone of modern portfolio theory and management, are detailed.