Expected Stock Returns Worldwide: A Log-Linear Present-Value Approach
This is the first large-scale study of the performance of expected-return proxies (ERPs) internationally. Analyst-forecast-based ICCs are commonly used to study how policies affect expected returns in international settings, but they are sparsely populated and not robustly associated with future returns. Earnings-model-forecast-based ICCs are well populated but are unreliable outside the United States. We provide a solution from a log-linear and present-value (LPV) framework—combining an accounting valuation anchor, its expected growth, and market prices—and adapt it to estimate ERPs in a global context. An LPV ERP anchored on the book value of equity is associated with future returns in each of the 29 equity markets we study and largely subsumes the out-of-sample predictive ability of the most common firm characteristics that have been shown to be associated with expected returns. Our findings also suggest that a firm's life-cycle stage provides useful information for ERP estimation.
Keywords: Expected Returns; discount rates; fundamental valuation; Present value; information quality; international equity markets; implied cost of capital; Investment Return; Equity; Markets; Global Range;
Citation:
Chattopadhyay, Akash, Matthew R. Lyle, and Charles C.Y. Wang. "Expected Stock Returns Worldwide: A Log-Linear Present-Value Approach." Harvard Business School Working Paper, No. 18-079, February 2018. (Revised September 2019.) View Details
