Note(s): This table displays detailed statistics for portfolios arranged by expected entropy and IV. Each month, from January 1988 to June 2019, we calculate the $Et[IEi,t+T]$ estimates using a 60-day formation period as detailed in Equations (11) and (12). $IVP,t$ is computed using a 30-day period as per Equation (8), allowing for comparison with Ang et al.’s (2006, 2009) IV analysis. Panel A shows the outcomes of sorting stocks into portfolios at each month’s end based on $Et[IEi,t+T]$⁠. Within each $Et[IEi,t+T]$ quintile, stocks are further divided into $IVi,t$ quintiles, and we calculate the value-weighted return for these 25 portfolios in the subsequent month (t+1). We then compute the value-weighted average across each of the five $Et[IEi,t+T]$ quintiles to account for the impact of expected IE. Panel B reverses the roles of $Et[IEi,t+T]$ and $IVi,t$ creating portfolios ranked by $Et[IEi,t+T]$ to control for the effects of $IVi,t$⁠. This panel also offers descriptive statistics for the five conditionally ranked portfolios, where Portfolio 1 contains stocks with the lowest $IVi,t$ (Panel A) or $Et[IEi,t+T]$ (Panel B), and Portfolio 5 includes those with the highest risk. Column 1 presents the average value-weighted returns of these portfolios over time. Columns 2 to 4 detail the standard deviation, skewness, and total entropy of the portfolio returns. Columns 5 to 7 provide the value-weighted cross-sectional averages of $IVi,t$⁠, $IEi,t+T$⁠, and $Sizei,t$ within each portfolio. Columns 8 and 9 show the alphas and Newey and West (1987) t-statistics (in parentheses) for the CAPM and Fama-French (1993) three-factor models. The symbols *, **, and *** indicate statistical significance at the 1%, 5%, and 10% levels, respectively

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