Bayesian Estimation for the Markov-Modulated Diffusion Risk Model


Por: Baltazar-Larios F., Esparza L.J.R.

Publicada: 1 ene 2019
Categoría: Mathematics (miscellaneous)

Resumen:
We consider the Markov-modulated diffusion risk model in which the claim inter-arrivals, claim sizes, premiums, and volatility diffusion process are influenced by an underlying Markov jump process. We propose a method for obtaining the maximum likelihood estimators of its parameters using a Markov chain Monte Carlo algorithm. We present simulation studies to estimate the ruin probability in finite time using the estimators obtained with the method proposed in this paper. © 2019, Springer Nature Switzerland AG.

Filiaciones:
Baltazar-Larios F.:
 Facultad de Ciencias, Universidad Nacional Autónoma de México, A.P. 20-726, Mexico City, 01000 CDMX, Mexico

Esparza L.J.R.:
 Catedra CONACyT, Universidad Autonoma Chapingo, Texcoco, Mexico
ISSN: 21941009
Editorial
Springer New York LLC, 233 SPRING STREET, NEW YORK, NY 10013, UNITED STATES, Estados Unidos America
Tipo de documento: Conference Paper
Volumen: 301 Número:
Páginas: 15-31