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This article compares the reliability of a discrete-time and a continuous-time Markov chain model for estimating credit risk and for investigating loans of Chiao Tung Bank in Taiwan. The continuous-ti...
We introduce a new geometric approach that constructs a transition kernel of Markov chain. Our method always minimizes the av- erage rejection rate and even reduce it to zero in many relevant cases,...
This paper develops a matrix-variate adaptive Markov chain Monte Carlo (MCMC) methodology for Bayesian Cointegrated Vector Auto Regressions (CVAR). We replace the popular approach to sampling Bayesia...
This paper develops a matrix-variate adaptive Markov chain Monte Carlo (MCMC) methodology for Bayesian Cointegrated Vector Auto Regressions (CVAR). We replace the popular approach to sampling Bayesian...
We apply a Coupled Markov Chain approach to model rating transitions and thereby default probabilities of companies. We estimate parameters by applying a maximum likeli-hood estimation using a large s...
We perform Markov chain Monte Carlo simulations for a Bayesian inference of the GJR-GARCH model which is one of asymmetric GARCH models. The adaptive construction scheme is used for the construction ...
We propose a method to construct a proposal density for the Metropolis-Hastings algorithm in Markov Chain Monte Carlo (MCMC)simulations of the GARCH model. The proposal density is constructed adaptive...

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