Notes: This table documents summary statistics for three estimated residuals. $u^t$ refers to the OLS residuals from the simple linear model $yt=α+βxt−1+ut$⁠, where y_t is the monthly S&P 500 value-weighted log excess returns between 1980 and 2019, and $xt−1$ is one of eleven predictive variables: d/e, lty, d/y, d/p, tbl, e/p, b/m, dfy, ntis, tms, and inf. $e^t$ refers to the residuals from the AR(1) model: $xt=μ+ρxt−1+et$⁠. $v^t$ refers to the residuals of the ARMA(p, q) model with orders p and q determined by the AIC. Ljung–Box denotes a serial correlation test proposed by Ljung and Box (1978) with 12 lags. Skewness and kurtosis represent sample skewness and sample excess kurtosis of residuals. Corr(⁠$u^t,v^t$⁠) represents sample correlation coefficients between $u^t$ and $v^t$⁠. *, **, and *** indicate the rejection of the null hypothesis at 10%, 5%, and 1%, respectively.