Out-of-Sample Industry Return Predictability: Evidence from A Large Number of Predictors

• Main Authors: Rapach, David E., Strauss, Jack K., TU, Jun, Zhou, Guofu
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2011
• Subjects: out-of-sample return predictability; industry portfolios; conditional beta pricing model; alpha predictability; Fama-French factors; industry-rotation strategy; Finance and Financial Management; Portfolio and Security Analysis
• Online Access: https://ink.library.smu.edu.sg/lkcsb_research/1803; https://ink.library.smu.edu.sg/context/lkcsb_research/article/2802/viewcontent/TuJunOutofSampleIndustryReturn.pdf
• Institution: Singapore Management University

We uncover extensive evidence of out-of-sample return predictability for industry portfolios based on a principal component approach that incorporates information from a large number of predictors. Moreover, we find substantial differences in the degree of return predictability across industries. To understand these differences, we propose a decomposition of out-of-sample industry return predictability into beta and alpha shares, where the former corresponds to a conditional beta pricing model. A conditional version of the popular Fama-French three-factor model accounts for nearly all out-of-sample industry return predictability, with exposures to time-varying market and size risk premiums especially important for explaining differences in return predictability across industries. We also show that out-of-sample return predictability is economically important from an asset allocation perspective and can be exploited to improve portfolio performance for industry-rotation investment strategies.