论文名称：Certainty of uncertainty for asset pricing

作者：Jiang, FW ; Kang, J; 孟令超

刊名：JOURNAL OF EMPIRICAL FINANCE

发表时间：2024.09

Uncertainty is known to be crucial in assetpricing, yet evidence from a comprehensive analysis of various uncertainty measures remains sparse. By machine learning, we construct a novel economic uncertainty index derived from a heterogeneous range ofuncertainty measures and investigate its predictability of stock returns. Our composite uncertainty index exhibits robust inand out-of-sample predictability of stock market returns over the one- to 12-month horizon. The predictive power stems from the volatility-orthogonal components of individual uncertainty measures and becomes more pronounced during high uncertainty and high sentiment periods. The predictability of our economic uncertainty index aligns with theoretical frameworks linking uncertainty to future investment, cash flows, and market expectations.