Regime-switching cointegration

Regime-Switching Cointegration∗

We develop methods for Bayesian inference in vector error correction models which are subject to a variety of switches in regime (e.g. Markov switches in regime or structural breaks). An important aspect of our approach is that we allow both the cointegrating vectors and the number of cointegrating relationships to change when the regime changes. We show how Bayesian model averaging or model se...

Bayesian Markov Regime-Switching Models for Cointegration

This paper introduces a Bayesian Markov regime-switching model that allows the cointegration relationship between two time series to be switched on and off over time. Unlike classical approaches for testing and modeling cointegration, the Bayesian Markov switching method allows for estimation of the regime-specific model parameters via Markov Chain Monte Carlo and generates more reliable estima...

Regime Switching Garch Models

We develop univariate regime-switching GARCH (RS-GARCH) models wherein the conditional variance switches in time from one GARCH process to another. The switching is governed by a time-varying probability, specified as a function of past information. We provide sufficient conditions for geometric ergodicity and existence of moments. Because of path dependence, maximum likelihood estimation is no...

Regime - Switching Models

Detecting Regime Switching: Analytic Power

This paper is concerned with the power of tests for regime switching. Asymptotic results are currently available only for the null distribution, and this distribution is dependent on the underlying parameter space. This paper addresses the lack of asymptotic results. The asymptotic behavior of the test statistic is determined under a full range of drifting sequences of true distributions. The r...