Time‐Varying Transition Probabilities for Markov Regime Switching Models

DOI10.1111/jtsa.12211zbMath1369.62211OpenAlexW3121709681MaRDI QIDQ5346584

Francisco Blasques, Siem Jan Koopman, André Lucas, Marco Bazzi

Publication date: 26 May 2017

Published in: Journal of Time Series Analysis (Search for Journal in Brave)

Full work available at URL: https://research.vu.nl/en/publications/178a00db-5072-4b14-9cf8-1d5b3076e976

zbMATH Keywords

hidden Markov modelstime varying parameterobservation driven models

Mathematics Subject Classification ID

Computational methods in Markov chains (60J22) Applications of statistics to economics (62P20) Markov processes: estimation; hidden Markov models (62M05)

Related Items (11)

A new class of integer-valued GARCH models for time series of bounded counts with extra-binomial variation ⋮ Maximum likelihood estimation for quantile autoregression models with Markovian switching ⋮ Dynamic clustering of multivariate panel data ⋮ Autoregressive conditional betas ⋮ A model for policy interest rates ⋮ Bayesian variable selection in non-homogeneous hidden Markov models through an evolutionary Monte Carlo method ⋮ Two classes of dynamic binomial integer-valued ARCH models ⋮ Origins of monetary policy shifts: a new approach to regime switching in DSGE models ⋮ Mixtures of Nonlinear Poisson Autoregressions ⋮ Markov switching quantile regression models with time-varying transition probabilities ⋮ Revisiting the transitional dynamics of business cycle phases with mixed-frequency data

Cites Work

• Unnamed Item
• Stationarity and ergodicity of univariate generalized autoregressive score processes
• Quasi-maximum-likelihood estimation in conditionally heteroscedastic time series: a stochastic recurrence equations approach
• Generalised residuals
• Estimating the dimension of a model
• Dynamic linear models with Markov-switching
• Generalized autoregressive conditional heteroscedasticity
• Dynamic Models for Volatility and Heavy Tails
• Kalman Filtering with Random Coefficients and Contractions
• Conditional Heteroskedasticity in Asset Returns: A New Approach
• Evaluating Specification Tests for Markov-Switching Time-Series Models
• Bias of the corrected AIC criterion for underfitted regression and time series models
• Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation
• Maximum likelihood identification of Gaussian autoregressive moving average models
• A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle
• Ergodicity of Autoregressive Processes with Markov-Switching and Consistency of the Maximum-Likelihood Estimator
• Autoregressive Conditional Duration: A New Model for Irregularly Spaced Transaction Data
• Filtering With Heavy Tails
• Information-theoretic optimality of observation-driven time series models for continuous responses
• Remarks on a Multivariate Transformation
• Business cycle asymmetries in stock returns: evidence from higher order moments and conditional densities
• Stationarity of multivariate Markov-switching ARMA models

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