Thematic Research: Forecasting Factor Returns

Posted on May 14, 2019

Authors: Geoff Duncombe, Mike Nigro, Bradley Kay

Abstract: The authors propose a methodology using historical data to quantify the return premia for major asset-class based factors.

The paper introduces a handful of innovations intended to improve the accuracy of our long-term return forecasts. Specifically, we:

  • Use new asset class return proxies to extend our analysis much further back than the daily return histories of most modern indices.
  • Separate the most heterogeneous of the prior paper’s factors, Commodities, into six sector-based factors for which the long-term premia are individually estimated.
  • Apply (what we believe to be) common sense adjustments to long-term histories — slightly overweighting recent returns and applying empirically-based shrinkage across the observed historical Sharpe ratios to generate our forward-looking estimates of each factor’s premium.
Download PDF — 1.86 MB

This article is not an endorsement by Two Sigma of the papers discussed, their viewpoints or the companies discussed. The views expressed above reflect those of the authors and are not necessarily the views of Two Sigma Investments, LP or any of its affiliates (collectively, “Two Sigma”). The information presented above is only for informational and educational purposes and is not an offer to sell or the solicitation of an offer to buy any securities or other instruments. Additionally, the above information is not intended to provide, and should not be relied upon for investment, accounting, legal or tax advice. Two Sigma makes no representations, express or implied, regarding the accuracy or completeness of this information, and the reader accepts all risks in relying on the above information for any purpose whatsoever. Click here for other important disclaimers and disclosures.