Bayesian inference of multiple structural change models with asymmetric GARCH errors

DOI10.1007/s10260-020-00549-zzbMath1480.62173OpenAlexW3107164011MaRDI QIDQ2062347

Cathy W. S. Chen, Bonny Lee

Publication date: 27 December 2021

Published in: Statistical Methods and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10260-020-00549-z

zbMATH Keywords

Markov chain Monte Carlo methodsstructural changebreakpointsdeviance information criterion (DIC)segmented modelskew student-t distribution

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to actuarial sciences and financial mathematics (62P05) Bayesian inference (62F15)

Cites Work

• Unnamed Item
• Testing and dating of structural changes in practice
• Estimation and comparison of multiple change-point models
• Generalized autoregressive conditional heteroscedasticity
• Detection of structural breaks in a time-varying heteroskedastic regression model
• Stochastic change-point ARX-GARCH models and their applications to econometric time series
• Conditional Heteroskedasticity in Asset Returns: A New Approach
• Forecasting Time Series Subject to Multiple Structural Breaks
• Bayesian methods for change-point detection in long-range dependent processes
• Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation
• Use of Cumulative Sums of Squares for Retrospective Detection of Changes of Variance
• Autoregressive Conditional Density Estimation
• Bayesian Measures of Model Complexity and Fit
• On-Line Inference for Multiple Changepoint Problems
• Equation of State Calculations by Fast Computing Machines
• Monte Carlo sampling methods using Markov chains and their applications
• Structural Break Estimation for Nonstationary Time Series Models

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