This paper studies the predictive power of expected volatility in the cross-section of expected stock returns. Evidence indicates that total and idiosyncratic volatility levels and volatility innovations have predictive power in the cross-section of expected excess stock returns. The results...

This paper examines the use of survey-based measures in volatility forecasting. We argue that the dispersion of individual mean return forecasts bridges the gap between individual volatilities and aggregate volatility. We use data coming from a repeated survey to capture volatility and mean...

This paper empirically estimates a heterogeneous agents model using S&P 500 data. While previous studies on heterogeneous agents models typically resort to simulation techniques, our empirical results indicate that the market is populated with fundamentalists, chartists, and noise traders. In...

The current paper proposes a conditional volatility model with time varying coefficients based on a multinomial switching mechanism. By giving more weight to either the persistence or shock term in a GARCH model, conditional on their relative ability to forecast a benchmark volatility measure,...