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Pricing bivariate option under GARCH-GH model with dynamic copula: application for Chinese market

Guegan, Dominique; Zhang, Jing - HAL - 2009

is used for innovations. As the association between the underlying assets may vary over time, the dynamic copula approach …-GH model with time-varying copula differ substantially from the prices implied by the GARCH-Gaussian dynamic copula model …

Persistent link: https://www.econbiz.de/10010738494

Pricing bivariate option under GARCH processes with time-varying copula

Zhang, Jing; Guegan, Dominique - HAL - 2008

Heteroskedastic (GARCH) process. As the association between the underlying assets may vary over time, the dynamic copula with time …-varying parameter offers a better alternative to any static model for dependence structure and even to the dynamic copula model … Shanghai and Shenzhen Stock Composite Indexes. Results show that the option prices obtained by the time-varying copula model …

Persistent link: https://www.econbiz.de/10010738655

Pricing bivariate option under GARCH processes with time-varying copula

Zhang, Jing; Guegan, Dominique - HAL - 2008

Heteroskedastic (GARCH) process. As the association between the underlying assets may vary over time, the dynamic copula with time …-varying parameter offers a better alternative to any static model for dependence structure and even to the dynamic copula model … Shanghai and Shenzhen stock composite indexes. Results show that the option prices obtained by the time-varying copula model …

Persistent link: https://www.econbiz.de/10010750766

Pricing bivariate option under GARCH-GH model with dynamic copula : application for Chinese market

Guegan, Dominique; Zhang, Jing - HAL - 2007

Persistent link: https://www.econbiz.de/10010750828

Assessing Dependence Changes in the Asian Financial Market Returns Using Plots Based on Nonparametric Measures

Silvapulle, Param; Zhang, Xibin - Department of Econometrics and Business Statistics, … - 2006

parametric copula can capture the dependence in the Singapore, Malaysia and Hong Kong markets for both pre- and post …

Persistent link: https://www.econbiz.de/10005087582

Bayesian semiparametric GARCH models

Zhang, Xibin; King, Maxwell L. - Department of Econometrics and Business Statistics, … - 2011

This paper aims to investigate a Bayesian sampling approach to parameter estimation in the semiparametric GARCH model with an unknown conditional error density, which we approximate by a mixture of Gaussian densities centered at individual errors and scaled by a common standard deviation. This...

Persistent link: https://www.econbiz.de/10009366291

Bayesian estimation of bandwidths for a nonparametric regression model with a flexible error density

Zhang, Xibin; King, Maxwell L.; Shang, Han Lin - Department of Econometrics and Business Statistics, … - 2011

We approximate the error density of a nonparametric regression model by a mixture of Gaussian densities with means being the individual error realizations and variance a constant parameter. We investigate the construction of a likelihood and posterior for bandwidth parameters under this...

Persistent link: https://www.econbiz.de/10009275517

Bayesian bandwidth selection for a nonparametric regession model with mixed types of regressors

Zhang, Xibin; King, Maxwell L.; Shang, Han Lin - Department of Econometrics and Business Statistics, … - 2013

We propose a sampling approach to bandwidth estimation for a nonparametric regression model with continuous and discrete types of regressors and unknown error density. The unknown error density is approximated by a location-mixture of Gaussian densities with means being the individual errors,...

Persistent link: https://www.econbiz.de/10010860408

Gaussian kernel GARCH models

Zhang, Xibin; King, Maxwell L. - Department of Econometrics and Business Statistics, … - 2013

This paper aims to investigate a Bayesian sampling approach to parameter estimation in the GARCH model with an unknown conditional error density, which we approximate by a mixture of Gaussian densities centered at individual errors and scaled by a common standard deviation. This mixture density...

Persistent link: https://www.econbiz.de/10010860418

A sampling algorithm for bandwidth estimation in a nonparametric regression model with a flexible error density

Zhang, Xibin; King, Maxwell L.; Shang, Han Lin - Department of Econometrics and Business Statistics, … - 2013

We propose to approximate the unknown error density of a nonparametric regression model by a mixture of Gaussian densities with means being the individual error realizations and variance a constant parameter. This mixture density has the form of a kernel density estimator of error realizations....

Persistent link: https://www.econbiz.de/10011141016