In this paper, we investigate the dynamics of age-cohort survival curves under the assumption that the instantaneous mortality intensity is driven by an affine jump-diffusion (AJD) process. Advantages of an AJD specification of mortality dynamics include the availability of closed-form...

The normal error distribution for the observations and log-volatilities in a stochastic volatility (SV) model is replaced by the Student-t distribution for robustness consideration. The model is then called the t-t SV model throughout this paper. The objectives of the paper are two-fold....

This paper generalizes the basic Wishart multivariate stochastic volatility model of Philipov and Glickman (2006) and Asai and McAleer (2009) to encompass regime switching behavior. The latent state variable is driven by a first-order Markov process. The model allows for state-dependent...

In this paper, using the MCMC method, we derive the conditional distribution of "mean variance" variable. This random variable appears in the option pricing problem under the stochastic volatility assumption. Two real data sets are considered. -- conditional distribution ; equity returns ; MCMC...

The Reversible Jump Markov Chain Monte Carlo (RJMCMC) method can enhance Bayesian DSGE estimation by sampling from a posterior distribution spanning potentially nonnested models with parameter spaces of different dimensionality. We use the method to jointly sample from an ARMA process of unknown...

In this paper we investigate whether the dynamic properties of the U.S. business cycle have changed in the last fifty years. For this purpose we develop a flexible business cycle indicator that is constructed from a moderate set of macroeconomic time series. The coincident economic indicator is...

In this paper we replace the Gaussian errors in the standard Gaussian, linear state space model with stochastic volatility processes. This is called a GSSF-SV model. We show that conventional MCMC algorithms for this type of model are ineffective, but that this problem can be removed by...

We relax the standard assumption in the dynamic stochastic general equilibrium (DSGE) literature that exogenous processes are governed by AR(1) processes and estimate ARMA (p,q) orders and parameters of exogenous processes. Methodologically, we contribute to the Bayesian DSGE literature by using...

In this paper, we assess whether key relations between US interest rates have been stable over time. This is done by estimating trivariate hybrid time-varying parameter Bayesian VAR models with stochastic volatility for the three-month Treasury bill rate, the slope of the Treasury yield curve...

This paper builds on Asai and McAleer (2009) and develops a new multivariate Dynamic Conditional Correlation (DCC) model where the parameters of the correlation dynamics and those of the log-volatility process are driven by two latent Markov chains. We outline a suitable Bayesian inference...