A factor model for the cross-section of country equity risk premia

Abstract

We employ instrumented principal component analysis (IPCA) to provide a new factor model for the cross-section of country equity risk premia. Using data from 71 equity markets, we identify latent factors and condition betas on a comprehensive set of accounting and market characteristics from the finance literature. A four-factor conditional asset pricing model best captures the variation in country returns, beating prominent factor models. IPCA’s superior performance stems primarily from its enhanced ability to predict emerging market returns while also generalizing well to developed markets. Among the global “signal zoo”, size, momentum, volatility, political risk, and valuation are the most important predictors of return differences.