Portfolio Choice with Path-Dependent Scenarios

Sophisticated investors rely on scenario analysis to select portfolios. We propose a new approach to scenario analysis that enables investors to consider sequential outcomes. We define scenarios not as average values but as paths for the economic variables. And we measure the likelihood of these paths on the basis of the statistical similarity of the paths to historical sequences. We also use a novel forecasting technique called “partial sample regression” to map economic outcomes onto asset class returns. This process allows investors to evaluate portfolios on the basis of the likelihood that the scenario will produce a certain pattern of returns over a specified investment horizon.Disclosure: The authors report no conflicts of interest. Editor’s Note: Submitted 28 May 2020Accepted 21 October 2020 by Stephen J. BrownThis material is for informational purposes only. The views expressed in this material are the views of the authors, are provided “as-is” at the time of first publication, are not intended for distribution to any person or entity in any jurisdiction where such distribution or use would be contrary to applicable law, and are not an offer or solicitation to buy or sell securities or any product. The views expressed do not necessarily represent the views of State Street Global Markets, State Street Corporation and its affiliates, Windham Capital Management, or GIC, Singapore’s sovereign wealth fund, GIC Private Limited, and its affiliates (collectively, “GIC”). While State Street, Windham Capital Management and GIC have collaborated for purposes of conducting research and developing this article, State Street, Windham Capital Management, and GIC are not engaged in any joint venture, affiliated in any way, or collectively providing or offering any services or products.