Aggregation of Information About the Cross Section of Stock Returns: A Latent Variable Approach

• 成果类型: Article
• 署名作者: Light, Nathaniel; Maslov, Denys; Rytchkov, Oleg
• 署名单位: American University of Sharjah; Pennsylvania Commonwealth System of Higher Education (PCSHE); Temple University
• 刊物名称: REVIEW OF FINANCIAL STUDIES
• ISSN/ISSBN: 0893-9454
• DOI: 10.1093/rfs/hhw102
• 发表日期: 2017
• 页码: 1339
• 关键词: asset pricing-models; corporate-investment; COSTLY ARBITRAGE; COMMON-STOCKS; market value; Cash flows; RISK; regression; anomalies; volatility

摘要

We propose a new approach for estimating expected returns on individual stocks from a large number of firm characteristics. We treat expected returns as latent variables and apply the partial least squares (PLS) estimator that filters them out from the characteristics under an assumption that the characteristics are linked to expected returns through one or few common latent factors. The estimates of expected returns constructed by our approach from 26 firm characteristics generate a wide cross-sectional dispersion of realized returns and outperform estimates obtained by alternative techniques. Our results also provide evidence of commonality in asset pricing anomalies.