Expected Stock Returns Worldwide: A Log-Linear Present-Value Approach

• 成果类型: Article
• 署名作者: Chattopadhyay, Akash; Lyle, Matthew R.; Wang, Charles C. Y.
• 署名单位: University of Toronto; Northwestern University; Harvard University
• 刊物名称: ACCOUNTING REVIEW
• ISSN/ISSBN: 0001-4826
• DOI: 10.2308/TAR-2018-0289
• 发表日期: 2022
• 页码: 107-133
• 关键词: IMPLIED COST; earnings management; cross-section; RISK; TRANSPARENCY; determinants; INFORMATION; models; GROWTH; LEVEL

摘要

This study provides the first large-scale study of the performance of expected-return proxies (ERPs) internationally. Analyst-forecast-based ICCs are sparsely populated and not robustly associated with future returns. Earnings-model-forecast-based ICCs are well-populated, but are unreliable outside the U.S. We adapt and extend the log-linear and present-value (LPV) framework-combining an accounting valuation anchor, its expected growth, and market prices-for estimating ERPs internationally, and implement a correction for the use of stale accounting data. An LPV ERP anchored on the book value of equity is positively associated with future returns in 26 of 29 equity markets, and largely subsumes the predictive ability of a broad set of firm characteristics previously shown to be associated with expected returns.