Estimation of SVJD models with Bayesian Methods and Power-Variation Estimators

Methodology is proposed of how to utilize high-frequency power-variation estimators in the Bayesian estimation of Stochastic-Volatility Jump-Diffusion (SVJD) models. Realized variance is used as an additional source of... [ view full abstract ]

Methodology is proposed of how to utilize high-frequency power-variation estimators in the Bayesian estimation of Stochastic-Volatility Jump-Diffusion (SVJD) models. Realized variance is used as an additional source of information for the estimation of stochastic variances, while the Z-Estimator is used as an additional source of information for the estimation of asset price jumps. The models are estimated by a combination of a MCMC algorithm and a SIR Particle Filter. The performance of the models is evaluated on simulated times series as well as real world financial time series of the 4 major foreign exchange rates.