textabstractThe paper develops a new realized matrix-exponential GARCH (MEGARCH) model, which uses the information of returns and realized measure of co-volatility matrix simultaneously. The paper also considers an alternative multivariate asymmetric function to develop news impact curves. We consider Bayesian MCMC estimation to allow non-normal posterior distributions. For three US nancial assets, we compare the realized MEGARCH models with existing multivariate GARCH class models. The empirical results indicate that the realized MEGARCH models outperform the other models regarding in-sample and out-of-sample performance. The news impact curves based on the posterior densities provide reasonable results
Dynamic Asymmetric Multivariate GARCH (DAMGARCH) is a new model that extends the Vector ARMA-GARCH (...
Real stock market data show that the daily stock log-returns are locally stationary but not in a lon...
In this paper, we perform Bayesian inference and prediction for a GARCH model where the innovations ...
The paper develops a new realized matrix-exponential GARCH (MEGARCH) model, which uses the informat...
The paper develops a new realized matrix-exponential GARCH (MEGARCH) model, which uses the informati...
The main aim of this paper is to present a Bayesian analysis of Multivariate GARCH(l, m) (M-GARCH) m...
In this paper we use Markov chain Monte Carlo (MCMC) methods in order to estimate and compare GARCH ...
We perform the Bayesian inference of a GARCH model by the Metropolis-Hastings algorithm with an adap...
This paper proposes a new Bayesian semiparametric model that combines a multivariate GARCH (MGARCH) ...
A new multivariate time series model with time varying conditional variances and covariances is pres...
Summary A new multivariate time series model with time varying conditional variances and covariances...
Abstract The objective of this paper is to investigate the properties of GARCH (1,1) model and to pe...
Abstract: DAMGARCH extends the VARMA-GARCH model of Ling and McAleer (2003) by introducing multiple ...
This paper proposes a new kind of asymmetric GARCH where the conditional variance obeys two differen...
This article proposes Bayesian nonparametric inference for panel Markov-switching GARCH models. The ...
Dynamic Asymmetric Multivariate GARCH (DAMGARCH) is a new model that extends the Vector ARMA-GARCH (...
Real stock market data show that the daily stock log-returns are locally stationary but not in a lon...
In this paper, we perform Bayesian inference and prediction for a GARCH model where the innovations ...
The paper develops a new realized matrix-exponential GARCH (MEGARCH) model, which uses the informat...
The paper develops a new realized matrix-exponential GARCH (MEGARCH) model, which uses the informati...
The main aim of this paper is to present a Bayesian analysis of Multivariate GARCH(l, m) (M-GARCH) m...
In this paper we use Markov chain Monte Carlo (MCMC) methods in order to estimate and compare GARCH ...
We perform the Bayesian inference of a GARCH model by the Metropolis-Hastings algorithm with an adap...
This paper proposes a new Bayesian semiparametric model that combines a multivariate GARCH (MGARCH) ...
A new multivariate time series model with time varying conditional variances and covariances is pres...
Summary A new multivariate time series model with time varying conditional variances and covariances...
Abstract The objective of this paper is to investigate the properties of GARCH (1,1) model and to pe...
Abstract: DAMGARCH extends the VARMA-GARCH model of Ling and McAleer (2003) by introducing multiple ...
This paper proposes a new kind of asymmetric GARCH where the conditional variance obeys two differen...
This article proposes Bayesian nonparametric inference for panel Markov-switching GARCH models. The ...
Dynamic Asymmetric Multivariate GARCH (DAMGARCH) is a new model that extends the Vector ARMA-GARCH (...
Real stock market data show that the daily stock log-returns are locally stationary but not in a lon...
In this paper, we perform Bayesian inference and prediction for a GARCH model where the innovations ...