Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/83327
Authors: 
Witzany, Jiří
Year of Publication: 
2011
Series/Report no.: 
IES Working Paper 35/2011
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.
Subjects: 
jump-diffusion
stochastic volatility
MCMC
Value at Risk
Monte Carlo
JEL: 
C11
C15
G1
Document Type: 
Working Paper
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