Publication detail

Estimating Correlated Jumps and Stochastic Volatilities

Author(s): RNDr. Jiří Witzany Ph.D.,
Type: IES Working Papers
Year: 2011
Number: 35
Published in: IES Working Papers 35/2011
Publishing place: Prague
Keywords: jump-diffusion, stochastic volatility, MCMC, Value at Risk, Monte Carlo
JEL codes: C11, C15, G1
Suggested Citation: Witzany, J. (2011). “Estimating Correlated Jumps and Stochastic Volatilities ” IES Working Paper 35/2011. IES FSV. Charles University.
Abstract: We formulate a bivariate stochastic volatility jump-diffusion model with correlated jumps and volatilities. An MCMC Metropolis-Hastings sampling algorithm is proposed to estimate the model’s parameters and latent state variables (jumps and stochastic volatilities) given observed returns. The methodology is successfully tested on several artificially generated bivariate time series and then on the two most important Czech domestic financial market time series of the FX (CZK/EUR) and 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.
Downloadable: WP 2011_35_Witzany




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