Add to ORKGWe perform Markov chain Monte Carlo simulations for a Bayesian inference of the GJR-GARCH model which is one of asymmetric GARCH models. The adaptive construction scheme is used for the construction of the proposal density in the Metropolis-Hastings algorithm and the parameters of the proposal density are determined adaptively by using the data sampled by the Markov chain Monte Carlo simulation. We study the performance of the scheme with the artificial GJR-GARCH data. We find that the adaptive construction scheme samples GJR-GARCH parameters effectively and conclude that the Metropolis-Hastings algorithm with the adaptive construction scheme is an efficient method to the Bayesian inference of the GJR-GARCH model.
This paper is concerned with improving the performance of Markov chain algorithms for Monte Carlo si...
This article considers Markov chain computational methods for incorporating uncertainty about the d...
The grouped independence Metropolis–Hastings (GIMH) and Markov chain within Metropolis (MCWM) algori...
A Bayesian estimation of a GARCH model is performed for US Dollar/Japanese Yen exchange rate by the ...
We perform the Bayesian inference of a GARCH model by the Metropolis-Hastings algorithm with an adap...
This paper describes a GAUSS program of a Markov-chain sampling algorithm for GARCH models proposed ...
In this paper we use Markov chain Monte Carlo (MCMC) methods in order to estimate and compare GARCH ...
AbstractUsually, the Bayesian inference of the GARCH model is preferably performed by the Markov Cha...
The hybrid Monte Carlo (HMC) algorithm is used for Bayesian analysis of the generalized autoregressi...
A proper choice of a proposal distribution for MCMC methods, e.g. for the Metropolis-Hastings algori...
The advantages of sequential Monte Carlo (SMC) are exploited to develop parameter estimation and mod...
Efficient simulation techniques for Bayesian inference on Markov-switching (MS) GARCH models are dev...
Efficient simulation techniques for Bayesian inference on Markov-switching (MS) GARCH models are dev...
Monte Carlo methods have become essential tools to solve complex Bayesian inference problems in diff...
Markov chain Monte Carlo (MCMC) is an important computational technique for generating samples from ...
This paper is concerned with improving the performance of Markov chain algorithms for Monte Carlo si...
This article considers Markov chain computational methods for incorporating uncertainty about the d...
The grouped independence Metropolis–Hastings (GIMH) and Markov chain within Metropolis (MCWM) algori...
A Bayesian estimation of a GARCH model is performed for US Dollar/Japanese Yen exchange rate by the ...
We perform the Bayesian inference of a GARCH model by the Metropolis-Hastings algorithm with an adap...
This paper describes a GAUSS program of a Markov-chain sampling algorithm for GARCH models proposed ...
In this paper we use Markov chain Monte Carlo (MCMC) methods in order to estimate and compare GARCH ...
AbstractUsually, the Bayesian inference of the GARCH model is preferably performed by the Markov Cha...
The hybrid Monte Carlo (HMC) algorithm is used for Bayesian analysis of the generalized autoregressi...
A proper choice of a proposal distribution for MCMC methods, e.g. for the Metropolis-Hastings algori...
The advantages of sequential Monte Carlo (SMC) are exploited to develop parameter estimation and mod...
Efficient simulation techniques for Bayesian inference on Markov-switching (MS) GARCH models are dev...
Efficient simulation techniques for Bayesian inference on Markov-switching (MS) GARCH models are dev...
Monte Carlo methods have become essential tools to solve complex Bayesian inference problems in diff...
Markov chain Monte Carlo (MCMC) is an important computational technique for generating samples from ...
This paper is concerned with improving the performance of Markov chain algorithms for Monte Carlo si...
This article considers Markov chain computational methods for incorporating uncertainty about the d...
The grouped independence Metropolis–Hastings (GIMH) and Markov chain within Metropolis (MCWM) algori...