Time inhomogeneous multivariate Markov chains : detecting and testing multiple structural breaks occurring at unknown

Damásio, Bruno; Nicolau, João

http://hdl.handle.net/10400.5/20164

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Authors

Damásio, Bruno

Nicolau, João

Abstract(s)

Markov chains models are used in several applications and diﬀerent areas of study. Usually a Markov chain model is assumed to be homogeneous in the sense that the transition probabilities are time invariant. Yet, ignoring the inhomogeneous nature of a stochastic process by disregarding the presence of structural breaks can lead to misleading conclusions. Several methodologies are currently proposed for detecting structural breaks in a Markov chain, however, these methods have some limitations, namely they can only test directly for the presence of a single structural break. This paper proposes a new methodology for detecting and testing the presence multiple structural breaks in a Markov chain occurring at unknown dates.

Keywords

Inhomogeneous Markov chain structural breaks time-varying probabilities

URI

http://hdl.handle.net/10400.5/20164

Citation

Damásio, Bruno e Joáo Nicolau (2020). "Time inhomogeneous multivariate Markov chains : detecting and testing multiple structural breaks occurring at unknown". Instituto Superior de Economia e Gestão – REM Working paper nº 0136 – 2020