Factors That Fit the Time Series and Cross-Section of Stock Returns

• 成果类型: Article
• 署名作者: Lettau, Martin; Pelger, Markus
• 署名单位: National Bureau of Economic Research; University of California System; University of California Berkeley; Center for Economic & Policy Research (CEPR); Stanford University
• 刊物名称: REVIEW OF FINANCIAL STUDIES
• ISSN/ISSBN: 0893-9454
• DOI: 10.1093/rfs/hhaa020
• 发表日期: 2020
• 页码: 2274
• 关键词: NUMBER

摘要

We propose a new method for estimating latent asset pricing factors that fit the time series and cross-section of expected returns. Our estimator generalizes principal component analysis (PCA) by including a penalty on the pricing error in expected returns. Our approach finds weak factors with high Sharpe ratios that PCA cannot detect. We discover five factors with economic meaning that explain well the cross-section and time series of characteristic-sorted portfolio returns. The out-of-sample maximum Sharpe ratio of our factors is twice as large as with PCA with substantially smaller pricing errors. Our factors imply that a significant amount of characteristic information is redundant.