A factor model for the cross-section of country equity risk premia
使用工具主成分分析（IPCA）对71个股票市场的数据构建了一个四因子条件资产定价模型，该模型在解释国家股票回报差异方面优于现有模型，尤其能更好地预测新兴市场回报。
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.