This paper presents the R package bayesGARCH which provides functions for the Bayesian estimation of the parsimonious but effective GARCH(1,1) model with Student-t innovations. The estimation procedure is fully automatic and thus avoids the time-consuming and difficult task of tuning a sampling algorithm. The usage of the package is shown in an empirical application to exchange rate log-returns
This paper proposes an up-to-date review of estimation strategies available for the Bayesian inferen...
A Bayesian estimation of a GARCH model is performed for US Dollar/Japanese Yen exchange rate by the ...
The hybrid Monte Carlo (HMC) algorithm is used for Bayesian analysis of the generalized autoregressi...
This paper presents the R package bayesGARCH which provides functions for the Bayesian estimation of...
This paper presents the R package bayesGARCH which provides functions for the Bayesian estimation of...
textabstractThis note presents the R package bayesGARCH (Ardia, 2007) which provides functions for t...
This note presents the R package bayesGARCH which provides functions for the Bayesian estimation of ...
This chapter proposes an up-to-date review of estimation strategies available for the Bayesian infer...
In this paper, we perform Bayesian inference and prediction for a GARCH model where the innovations ...
Using well-known GARCH models for density prediction of daily S&P 500 and Nikkei 225 index returns,...
Bayesian inference and prediction for a generalized autoregressive conditional heteroskedastic (GARC...
Abstract The objective of this paper is to investigate the properties of GARCH (1,1) model and to pe...
We perform the Bayesian inference of a GARCH model by the Metropolis-Hastings algorithm with an adap...
In this paper we extend the closed-form estimator for the generalized autoregressive conditional het...
AbstractUsually, the Bayesian inference of the GARCH model is preferably performed by the Markov Cha...
This paper proposes an up-to-date review of estimation strategies available for the Bayesian inferen...
A Bayesian estimation of a GARCH model is performed for US Dollar/Japanese Yen exchange rate by the ...
The hybrid Monte Carlo (HMC) algorithm is used for Bayesian analysis of the generalized autoregressi...
This paper presents the R package bayesGARCH which provides functions for the Bayesian estimation of...
This paper presents the R package bayesGARCH which provides functions for the Bayesian estimation of...
textabstractThis note presents the R package bayesGARCH (Ardia, 2007) which provides functions for t...
This note presents the R package bayesGARCH which provides functions for the Bayesian estimation of ...
This chapter proposes an up-to-date review of estimation strategies available for the Bayesian infer...
In this paper, we perform Bayesian inference and prediction for a GARCH model where the innovations ...
Using well-known GARCH models for density prediction of daily S&P 500 and Nikkei 225 index returns,...
Bayesian inference and prediction for a generalized autoregressive conditional heteroskedastic (GARC...
Abstract The objective of this paper is to investigate the properties of GARCH (1,1) model and to pe...
We perform the Bayesian inference of a GARCH model by the Metropolis-Hastings algorithm with an adap...
In this paper we extend the closed-form estimator for the generalized autoregressive conditional het...
AbstractUsually, the Bayesian inference of the GARCH model is preferably performed by the Markov Cha...
This paper proposes an up-to-date review of estimation strategies available for the Bayesian inferen...
A Bayesian estimation of a GARCH model is performed for US Dollar/Japanese Yen exchange rate by the ...
The hybrid Monte Carlo (HMC) algorithm is used for Bayesian analysis of the generalized autoregressi...