DocumentCode
536489
Title
MCMC Algorithm and Simulation of a Class of Jump VaR Estimation
Author
Wang, Jingyong ; Xue, Lida
Author_Institution
Econ. & Trade Dept., TongLing Univ., Tongling, China
fYear
2010
fDate
7-9 Nov. 2010
Firstpage
1
Lastpage
4
Abstract
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.
Keywords
Markov processes; Monte Carlo methods; belief networks; financial management; risk management; stochastic programming; Bayesian inference; MCMC Algorithm; Markov chain Monte Carlo method; VaR Estimation; jump stochastic volatility threshold model; value at risk; Approximation methods; Bayesian methods; Biological system modeling; Density functional theory; Estimation; Markov processes;
fLanguage
English
Publisher
ieee
Conference_Titel
E-Product E-Service and E-Entertainment (ICEEE), 2010 International Conference on
Conference_Location
Henan
Print_ISBN
978-1-4244-7159-1
Type
conf
DOI
10.1109/ICEEE.2010.5660186
Filename
5660186
Link To Document