Markov-switching models are attractive for analysing time series that exhibit different stochastic processes along different periods, and where the regime-switching is controlled by an unobservable Markovian process. Model flexibility can be enhanced considering regime-specific distributions, whose distributional parameters may be modelled using smooth functions of covariates. Here, we propose a two-state Markov-switching model using full Bayesian inference and accounting for extreme value modelling. The proposal is illustrated by analysing energy prices.

A Bayesian Markov-Switching for Smooth Modelling of Extreme Value Distributions

Gioia, Vincenzo
Primo
;
Di Credico, Gioia
Secondo
;
Pauli, Francesco
Ultimo
2024-01-01

Abstract

Markov-switching models are attractive for analysing time series that exhibit different stochastic processes along different periods, and where the regime-switching is controlled by an unobservable Markovian process. Model flexibility can be enhanced considering regime-specific distributions, whose distributional parameters may be modelled using smooth functions of covariates. Here, we propose a two-state Markov-switching model using full Bayesian inference and accounting for extreme value modelling. The proposal is illustrated by analysing energy prices.
2024
9783031657221
9783031657238
9783031657252
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11368/3087558
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