Risk-return trade-off, information diffusion, and U.S. stock market predictability

Recent academic literature in finance documents both risk-return trade-off and gradual information diffusion (ID). Motivated by these two financial theories, this paper proposes the ARCH-M model augmented by an ID indicator to forecast the U.S. stock market returns. Empirical studies performed on the monthly S&P500 index show that our approach is useful in both statistical and economic sense. Further analysis shows that the ID provides complementary information to risk-return trade-off effect. Our findings confirm that financial theories are valuable for stock return forecasting.