The goal of this article is an exact Bayesian analysis of the Heston (1993) stochastic volatility model. We carefully … study the effect different parameterizations of the latent volatility process and the parameters of the volatility process …

Implied volatility skew and smile are ubiquitous phenomena in the financial derivative market especially after the … Black Monday 1987 crash. Various stochastic volatility models have been proposed to capture volatility skew and smile in … derivative pricing and hedging. Almost 30 years after the advent of the first type of stochastic volatility model calibrating …

This paper proposes the sample path generation method for the stochastic volatility version of the CGMY process. We …

We introduce a new method to price American-style options on underlying investments governed by stochastic volatility … (SV) models. The method does not require the volatility process to be observed. Instead, it exploits the fact that the … distributions of volatility, given observed data. By constructing statistics summarizing information about these conditional …

Based on the fact that realized measures of volatility are affected by measurement errors, we introduce a new family of … discrete-time stochastic volatility models having two measurement equations relating both observed returns and realized … realized measures in inflating the latent volatility persistence - the crucial parameter in pricing Standard and Poor's 500 …

We formulate a bivariate stochastic volatility jump-diffusion model with correlated jumps and volatilities. An MCMC … stock (PX index) returns. Four bivariate models with and without jumps and/or stochastic volatility are compared using the … deviance information criterion (DIC) confirming importance of incorporation of jumps and stochastic volatility into the model …