MCMC Algorithm and Simulation of a Class of Jump VaR Estimation
- Resource Type
- Conference
- Authors
- Wang, Jingyong; Xue, Lida
- Source
- 2010 International Conference on E-Product E-Service and E-Entertainment E-Product E-Service and E-Entertainment (ICEEE), 2010 International Conference on. :1-4 Nov, 2010
- Subject
- Computing and Processing
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Biological system modeling
Estimation
Density functional theory
Bayesian methods
Markov processes
Approximation methods
- Language
This paper develops a class of jump stochastic volatility threshold model of VaR Estimation from a Bayesian viewpoint. Bayesian inferences of the unknown parameters are obtained with respect to a subjective prior distribution via Markov chain Monte Carlo(MCMC) method, MCMC algorithm and the value at risk(VaR) predictive are also developed. Based on simulation, if the jump is not Considered, the value at risk is overestimated. The precision of value at risk estimation is increased.