Multi-factor models are standard tools for analysing the performance and the risk of equity portfolios. In addition to analysing the impact of common factors, equity portfolio managers are also interested in analysing the role of stock-specific attributes in explaining differences in risk and performance across assets and portfolios.
In a new publication entitled “Multi-Dimensional Risk and Performance Analysis for Equity Portfolios”, EDHEC-Risk Institute explores a novel approach to address the challenge raised by the standard investment practice of treating attributes as factors, with respect to how to perform a consistent risk and performance analysis for equity portfolios across multiple dimensions that incorporate micro attributes. This research was conducted with the support of CACEIS as part of EDHEC-Risk Institute’s research chair on “New Frontiers in Risk Assessment and Performance Reporting”.
EDHEC-Risk Institute’s study suggests a new dynamic meaningful approach, which consists in treating attributes of stocks as instrumental variables to estimate betas with respect to risk factors for explaining notably the cross-section of expected returns. In one example of implementation, the authors maintain a limited number of risk factors by considering a one-factor model, and they estimate a conditional beta that depends on the same three characteristics that define the Fama-French and Carhart factors.
In so doing, the authors introduce an alternative estimator for the conditional beta, which they name “fundamental beta” (as opposed to historical beta) because it is defined as a function of the stock’s characteristics, and they provide evidence of the usefulness of these fundamental betas for (i) parsimoniously embedding the sector dimension in multi-factor portfolio risk and performance analysis, (ii) building equity portfolios with controlled target factor exposure, and also (iii) explaining the cross-section of expected returns, by showing that a conditional CAPM based on this “fundamental” beta can capture the size, value and momentum effects as well as the Carhart model, but without the help of additional factors.
“This study introduces an approach that can be used by asset managers to implement portfolios more consistent with their active views on factor returns, or lack thereof,” said Lionel Martellini, co-author and Director of EDHEC-Risk Institute.
“Understanding risk in all its forms is key to achieving the highest risk-adjusted returns – an essential component in today’s competitive asset management environment. Through our sponsorship of the EDHEC-Risk research chair, we hoped to uncover practical advances in risk management techniques for the benefit of our clients, and welcome the outcome of this work,” said Cécile Falcon, Global Head of Business Line, Front Office Solutions, CACEIS.