Bayesian analysis of stochastic volatility models

Journal of Business and Economic Statistics

Volumn 20, Issue 1, 2002, Pages 69-87

  Jacquier, Eric ^a   Polson, Nicholas G ^a   Rossi, Peter E ^a  

^a The Samuel Curtis Johnson Graduate School of Management   (United States)

Author keywords

Bayesian inference; Markov chain Monte Carlo; Method of moments; Nonlinear filtering; Quasi maximum likelihood; Stochastic volatility

Indexed keywords

EID: 0035995705     PISSN: 07350015     EISSN: None     Source Type: Journal    
DOI: 10.1198/073500102753410408     Document Type: Article

References (39)

1. Heteroskedasticity and autocorrelation consistent covariance matrix estimation
2. Generalized autoregressive conditional heteroskedasticity
3. ARCH modeling in finance
4. A Monte Carlo approach to non-normal and nonlinear state-space modelling
5. A subordinated stochastic process model with finite variances for speculative prices
6. Stochastic volatility in asset prices: Estimation with simulated maximum likelihood
7. On fitting a recalcitrant series: The pound/dollar exchange rates, 1974-83
8. Stock prices and volume
9. Sampling-based approaches to calculating marginal densities
10. Stochastic relaxation, gibbs distributions and the Bayesian restoration of images
11. Evaluating the accuracy of sampling-based approaches to the calculation of posterior moments
12. Large sample properties of generalized method of moments estimators
13. Multivariate stochastic variance models
14. Chaos and nonlinear dynamics: Applications to financial markets
15. The pricing of options on assets with stochastic volatilities
16. An exact likelihood analysis of the multinomial probit model
17. Bayesian inference and prediction for mean and variance shifts in autoregressive time series
18. Pricing foreign currency options with stochastic volatility
19. Conditional heteroskedasticity in asset returns: A new approach
20. Quasi-maximum likelihood estimation of stochastic variance models
21. Fitting nonlinear time series models with applications to stochastic variance models
22. The calculation of posterior distributions by data augmentation
23. The price variability-volume relationship on speculative markets
24. Options values under stochastic volatility: Theory and empirical evidence