-diffusions, and models of stochastic volatility. This paper explores the statistical properties of these models with a view to …

-dependent options and options on assets with stochastic volatility and jumps. " …

An efficient method is developed for pricing American options on combination stochastic volatility …/jump-diffusion processes when jump risk and volatility risk are systematic and nondiversifiable, thereby nesting two major option pricing … models. The parameters implicit in PHLX-traded Deutschemark options of the stochastic volatility/jump- diffusion model and …

the mean and volatility of equity returns. Our model assumes a small risk of a rare disaster that is calibrated based on … turns out to be crucial to the model's ability to explain both equity volatility and option prices. We explore different …

probability, while probabilities are derived from an estimated stochastic volatility model of the form GARCH components with …

intertemporal feedback between user adoption and token price accelerates adoption and dampens user-base volatility …

, liquidity providers lose. Since information generates volatility, and volatility co-moves across assets, liquidity providers … have a negative exposure to aggregate volatility shocks. As aggregate volatility shocks carry a very large premium in … large negative betas to aggregate volatility shocks. These betas explain their average returns with the same risk price as …

We provide evidence that agents have slow-moving beliefs about stock market volatility that lead to initial … underreaction to volatility shocks followed by delayed overreaction. These dynamics are mirrored in the VIX and variance risk … premiums which reflect investor expectations about volatility and are also supported in surveys and in firm-level option prices …