because they lead to a generalization of the Black-Scholes formula for derivative pricing. In place of the standard assumption …

private information influences aggregate volatility. The maximal aggregate volatility is attained in a noise free information …, as in Lucas [14]. For any given variance of aggregate shocks, the upper bound on aggregate volatility is linearly …

volatility directly implies the forecastability of long-horizon returns. …

A recent literature shows how an increase in volatility reduces leverage. However, in order to explain pro …-cyclical leverage it assumes that bad news increases volatility, that is, it assumes an inverse relationship between first and second … volatility. We show that, in a model with endogenous leverage and heterogeneous beliefs, agents have the incentive to invest …

the total volatility function in a continuous-time jump diffusion model. …

structure determines aggregate volatility. We show that the maximal aggregate volatility is attained in a noise free information … the common component, as in Lucas (1972). The upper bound on aggregate volatility is linearly increasing in the variance …

A recent literature shows how an increase in volatility reduces leverage. However, in order to explain pro …-cyclical leverage it assumes that bad news increases volatility, that is, it assumes an inverse relationship between first and second … volatility. We show that, in a model with endogenous leverage and heterogeneous beliefs, agents have the incentive to invest …