of long-term stock market volatility. When long-term volatility is high, stock returns are more sensitive to news, and …-linear present value framework with a two-component volatility model for the conditional variance of cash flow news and allowing for … volatility feedback. In our model, innovations to the long-term volatility component are the most important driver of discount …

This study seeks to determine whether earnings announcements pose non-diversifiable volatility risk that commands a … volatility and pay a premium to hedge this non-diversifiable risk. In particular, we find evidence of risk premiums embedded in … announcements pose non-diversifiable volatility risk. In addition, we find that volatility risk premiums are concentrated among …

. Proposed extensions include a volatility regime switching mechanism (using dummy variables and the Markov approach) and the … fifth risk factor based on realized volatility of index returns. Moreover, instead of using data for stocks of a particular …

predict future returns, there is a significant relation between volatility spreads and expected stock returns. Portfolio level … the realized-implied volatility spread that can be viewed as a proxy for volatility risk. The results also provide … evidence for a significantly positive link between expected returns and the call-put options' implied volatility spread that …

) The Volatility Puzzle. We offer resolutions of those objections within the rational finance. We do not claim that those …

expected stock return and both the maximum daily return (MAX) and the idiosyncratic volatility (IVOL) in the five largest …

We use learning in an equilibrium model to explain the puzzling predictive power of the volatility risk premium (VRP …