## Abstract This article introduces a new model to capture simultaneously the mean and variance asymmetries in time series. Threshold nonβlinearity is incorporated into the mean and variance specifications of a stochastic volatility model. Bayesian methods are adopted for parameter estimation. Fore
A threshold factor multivariate stochastic volatility model
β Scribed by Mike K. P. So; C. Y. Choi
- Publisher
- John Wiley and Sons
- Year
- 2009
- Tongue
- English
- Weight
- 280 KB
- Volume
- 28
- Category
- Article
- ISSN
- 0277-6693
- DOI
- 10.1002/for.1123
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β¦ Synopsis
Abstract
A new multivariate stochastic volatility model is developed in this paper. The main feature of this model is to allow threshold asymmetry in a factor covariance structure. The new model provides a parsimonious characterization of volatility and correlation asymmetry in response to market news. Statistical inferences are drawn from Markov chain Monte Carlo methods. We introduce news impact analysis to analyze volatility asymmetry with a factor structure. This analysis helps us to study different responses of volatility to historical market information in a multivariate volatility framework. Our model is successful when applied to an extensive empirical study of twenty stocks.βCopyright Β© 2009 John Wiley & Sons, Ltd.
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