We develop a preference-based equilibrium asset pricing model that explains low-frequency conditional volatility. Similar to Barberis, Huang, and Santos (2001), agents in our model care about wealth changes, experience loss aversion, and keep a mental scorecard that affects their level of risk aversion. A new feature of our model is that when perturbed by unexpected returns, investors become temporarily more sensitive to news. Gradually investors become accustomed to the new level of wealth, restoring prior levels of risk aversion and news sensitivity. The state-dependent sensitivity to news creates the type of volatility clustering found in low-frequency stock returns. We find empirical support for our model's predictions that relate the scorecard to conditional volatility and skewness.

We develop a preference-based equilibrium asset pricing model that explains low-frequency conditional volatility. Similar to Barberis, Huang, and Santos (2001), agents in our model care about wealth changes, experience loss aversion, and keep a mental scorecard that affects their level of risk aversion. A new feature of our model is that when perturbed by unexpected returns, investors become temporarily more sensitive to news. Gradually investors become accustomed to the new level of wealth, restoring prior levels of risk aversion and news sensitivity. The state-dependent sensitivity to news creates the type of volatility clustering found in low-frequency stock returns. We find empirical support for our model's predictions that relate the scorecard to conditional volatility and skewness.