An MCMC computational approach for a continuous time state-dependent regime switching diffusion process

ABSTRACT

State-dependent regime switching diffusion processes or hybrid switching diffusion (HSD) processes are hard to simulate with classical methods which leads us to adopt a Markov chain Monte Carlo (MCMC) Bayesian approach very convenient to estimate complicated models such as the HSD one. In the HSD, the diffusion component is dependent on the switching discrete hidden regimes and the transition rates of the regime switching are dependent on the diffusion observations. Since in reality phenomena are only observed in discrete times, data imputation is called for to create more observations so as to have good approximations for the density of the diffusion process. Three categories of entities will be computed in a Bayesian context: The latent imputed observations, the regime switching states, and the parameters of the models. The latent imputed data is updated at random time intervals in block using a Metropolis Hastings algorithm. The switching states are computed by an adaptation of a forward filtering backward smoothing algorithm to the HSD model. The parameters are estimated after prior specifications and conditional posterior densities formulation using Gibbs sampler or Metropolis Hastings algorithm.

Keywords:

• Hybrid switching diffusion model
• data imputation
• hidden states computation
• random time imputation
• states computation

Supplemental materiel

The supplemental materiel contains the Matlab program of the MCMC simulation of the hybrid switching process considered in the present paper.

Acknowledgment

We would like to thank the editor and the associate editor for their significant guidance. Also, we would like to thank the anonymous reviewers for orienting us toward important references and for helping in improving this work.

Disclosure statement

No potential conflict of interest was reported by the authors.

ORCID

El Houcine Hibbah  http://orcid.org/0000-0001-9319-3670

Hamid El Maroufy  http://orcid.org/0000-0001-6113-7543

Christiane Fuchs  http://orcid.org/0000-0003-3565-8315

Taib Ziad  http://orcid.org/0000-0002-5329-9793