This paper examines the predictive power of trading volume for Chinese equity premium. High (low) trading volume significantly predicts subsequent high (low) equity premium in Chinese stock market in- and out-of-sample. The predictability of trading volume remains significant after controlling for a large number of China economic variables. The predictive power of trading volume is economically important from an asset allocation perspective. Overall, our study suggests that trading volume should be used in conjunction with economic variables to further enhance the Chinese equity premium predictability.

The evidence on the relation between idiosyncratic risk and future market return is at odds with the theory in Merton (1987). We argue that this is because conventional idiosyncratic risk measures are too noisy that consequently camou?age the true pricing relation suggested by the theory in empirical tests. To reduce the noise, we employ a random portfolio approach to construct an alternative aggregate idiosyncratic risk measure. Due to a high correlation between the noise components of the conventional idiosyncratic risk measure and our portfolio idiosyncratic risk measure, we include both measures simultaneously in a predictive regression, in which the conventional idiosyncratic risk measure helps to further reduce the noise in our portfolio idiosyncratic risk measure. We ?nd that both variables are signi?cant and jointly predict returns on the market with an adjusted R2 of 2%. Our results are very robust to all conventional control variables, sample periods, the size deciles.

The evidence on the relation between idiosyncratic risk and future market return is at odds with the theory in Merton (1987). We argue that this is because conventional idiosyncratic risk measures are too noisy that consequently camou?age the true pricing relation suggested by the theory in empirical tests. To reduce the noise, we employ a random portfolio approach to construct an alternative aggregate idiosyncratic risk measure. Due to a high correlation between the noise components of the conventional idiosyncratic risk measure and our portfolio idiosyncratic risk measure, we include both measures simultaneously in a predictive regression, in which the conventional idiosyncratic risk measure helps to further reduce the noise in our portfolio idiosyncratic risk measure. We ?nd that both variables are signi?cant and jointly predict returns on the market with an adjusted R2 of 2%. Our results are very robust to all conventional control variables, sample periods, the size deciles

We analyze a general equilibrium exchange economy with a continuum of agents who have ``catching up with the Joneses'' preferences and differ only with respect to the curvature of their utility functions. While individual risk aversion does not change over time, dynamic re-distribution of wealth among the agents leads to countercyclical time variation in the Sharpe ratio of stock returns. We show that the level of stock prices is negatively related to both the conditional return volatility and the risk premium, as observed empirically. Therefore, our model also produces the correct sign for the slope coefficients in long-horizon predictive regressions. For comparison, otherwise similar representative agent economies with the same type of preferences exhibit counter-factual behavior of conditional moments of returns, i.e., a constant Sharpe ratio and procyclical risk premium and return volatility.