Market Return Decomposition and Equity Risk Premium Predictability

Yanyan Lin, Chongfeng Wu, Guofu Zhou, and Shunwei Zhu

♦ We introduce a novel decomposition of stock market returns into a permanent component (PC), capturing long-term growth, and a temporary component (TC), reflecting short-term fluctuations. The decomposition is explicit, straightforward to estimate, and designed to correct model misspecification in traditional predictive regressions. The PC aligns with highly persistent valuation ratios, while the TC is predictable via standard regressions, further improved by shrinkage. Using 41 predictors from Goyal et al. (2024), we find 33 significant predictors of market returns, compared with only 5 in their study. Combining forecasts across predictors reaffirm equity risk premium predictability out-of-sample.

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