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 …

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

This paper provides a data-driven analysis of the volatility risk premium, using tools from high-frequency finance and … Big Data analytics. We argue that the volatility risk premium, loosely defined as the difference between realized and … implied volatility, can best be understood when viewed as a systematically priced bias. We first use ultra …

We investigate the pricing of volatility risks in currency markets. First, we show that pricing ability of volatility … risk is concentrated in some of its components. Diffusive volatility dominates jump volatility in pricing carry trade … returns, while jump volatility is important in jointly explaining carry trade and momentum returns. Both short-run and long …

predictability of excess returns on long-term bonds. Modeling this requires sufficient volatility and persistence in the price of … innovations in the level factor to explain the volatility of long-term bond returns. The model also implies that excess bond …

predictability of excess returns on long-term bonds. Modeling this requires sufficient volatility and persistence in the price of … innovations in the level factor to explain the volatility of long-term bond returns. The model also implies that excess bond …

This paper documents law of one price violations in equity volatility markets. While tightly linked by no …

This paper documents law of one price violations in equity volatility markets. While tightly linked by no …