Add to ORKGThe Stochastic Volatility Model is used extensively in financial time series. Recent literature has shown the importance of incorporating switching regimes into the volatility models. Hence, the "Stochastic Volatility Model with changing regimes" that is discussed in this thesis. A new sampling scheme which combines the recent work of Gerlach, Carter & Kohn (1997a) and So, Lam & Li (1998) is proposed. From the simulation study, the new sampling scheme has a faster convergence rate than previous methods mentioned in So, Lam and Li (1998)
International audienceA simple method is proposed to estimate stochastic volatility models with Mark...
We study a Markov switching stochastic volatility model with heavy tail innovations in the observab...
van Norden and Schaller (1996) develop a standard regime-switching model to study stock market crash...
This article presents a new way of modeling time-varying volatility. We generalize the usual stochas...
In this paper, we introduce regime-switching in a two-factor stochastic volatility (SV) model to exp...
We address the problem of parameter estimation for diffusion driven sto-chastic volatility models th...
In this paper, we introduce regime-switching in a two-factor stochastic volatility model to explain ...
We address the problem of parameter estimation for diffusion driven stochastic volatility models thr...
We adopt a regime switching approach to study concrete financial time series with particular emphasi...
In the study we introduce an extension to a stochastic volatility in mean model (SV-M), allowing for...
In the study we introduce an extension to a stochastic volatility in mean model (SV-M), allowing for...
This paper deals with financial modeling to describe the behavior of asset returns, through consider...
This paper generalizes the basic Wishart multivariate stochastic volatility model of Philipov and Gl...
This paper is concerned with simulation-based inference in generalized models of stochastic volatili...
This paper is concerned with simulation-based inference in generalized models of stochastic volatili...
International audienceA simple method is proposed to estimate stochastic volatility models with Mark...
We study a Markov switching stochastic volatility model with heavy tail innovations in the observab...
van Norden and Schaller (1996) develop a standard regime-switching model to study stock market crash...
This article presents a new way of modeling time-varying volatility. We generalize the usual stochas...
In this paper, we introduce regime-switching in a two-factor stochastic volatility (SV) model to exp...
We address the problem of parameter estimation for diffusion driven sto-chastic volatility models th...
In this paper, we introduce regime-switching in a two-factor stochastic volatility model to explain ...
We address the problem of parameter estimation for diffusion driven stochastic volatility models thr...
We adopt a regime switching approach to study concrete financial time series with particular emphasi...
In the study we introduce an extension to a stochastic volatility in mean model (SV-M), allowing for...
In the study we introduce an extension to a stochastic volatility in mean model (SV-M), allowing for...
This paper deals with financial modeling to describe the behavior of asset returns, through consider...
This paper generalizes the basic Wishart multivariate stochastic volatility model of Philipov and Gl...
This paper is concerned with simulation-based inference in generalized models of stochastic volatili...
This paper is concerned with simulation-based inference in generalized models of stochastic volatili...
International audienceA simple method is proposed to estimate stochastic volatility models with Mark...
We study a Markov switching stochastic volatility model with heavy tail innovations in the observab...
van Norden and Schaller (1996) develop a standard regime-switching model to study stock market crash...