Add to ORKGWe develop a Markov-switching GARCH model (MS-GARCH) wherein the conditional mean and variance switch in time from one GARCH process to another. The switching is governed by a hidden Markov chain. We provide sufficient conditions for geometric ergodicity and existence of moments of the process. Because of path dependence, maximum likelihood estimation is not feasible. By enlarging the parameter space to include the state variables, Bayesian estimation using a Gibbs sampling algorithm is feasible. We illustrate the model on SP500 daily returns
summary:In this paper, we propose an extension of a periodic $GARCH$ ($PGARCH$) model to a Markov-sw...
The regime-switching GARCH model combines the idea of Markov switching and GARCH model, which also e...
GARCH volatility models with fixed parameters are too restrictive for long time series due to breaks...
We develop a Markov-switching GARCH model (MS-GARCH) wherein the conditional mean and variance switc...
We develop univariate regime-switching GARCH (RS-GARCH) models wherein the conditional variance swit...
Generalized Auto-regressive Conditional Heteroskedastic (GARCH) models with fixed parameters are typ...
GARCH volatility models with fixed parameters are too restrictive for long time series due to breaks...
This paper describes briefly about GARCH with regime switching (SW-GARCH) following Markov Chain pro...
This paper is devoted to show duality in the estimation of Markov Switching (MS) GARCH processes. It...
This paper introduces four models of conditional heteroskedasticity that contain markov switching pa...
Regime Switching models, especially Markov switching models, are regarded as a promising way to capt...
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...
GARCH option pricing models have the advantage of a well-established econometric foundation. However...
AbstractThis paper analyzes the probabilistic structure of Markov-switching GARCH(p,q) models, in wh...
summary:In this paper, we propose an extension of a periodic $GARCH$ ($PGARCH$) model to a Markov-sw...
The regime-switching GARCH model combines the idea of Markov switching and GARCH model, which also e...
GARCH volatility models with fixed parameters are too restrictive for long time series due to breaks...
We develop a Markov-switching GARCH model (MS-GARCH) wherein the conditional mean and variance switc...
We develop univariate regime-switching GARCH (RS-GARCH) models wherein the conditional variance swit...
Generalized Auto-regressive Conditional Heteroskedastic (GARCH) models with fixed parameters are typ...
GARCH volatility models with fixed parameters are too restrictive for long time series due to breaks...
This paper describes briefly about GARCH with regime switching (SW-GARCH) following Markov Chain pro...
This paper is devoted to show duality in the estimation of Markov Switching (MS) GARCH processes. It...
This paper introduces four models of conditional heteroskedasticity that contain markov switching pa...
Regime Switching models, especially Markov switching models, are regarded as a promising way to capt...
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...
GARCH option pricing models have the advantage of a well-established econometric foundation. However...
AbstractThis paper analyzes the probabilistic structure of Markov-switching GARCH(p,q) models, in wh...
summary:In this paper, we propose an extension of a periodic $GARCH$ ($PGARCH$) model to a Markov-sw...
The regime-switching GARCH model combines the idea of Markov switching and GARCH model, which also e...
GARCH volatility models with fixed parameters are too restrictive for long time series due to breaks...