This paper reviews the analysis of the threshold autoregressive, smooth threshold autoregressive, and Markov switching autoregressive models from the Bayesian perspective. For each model we start by describing a baseline model and discussing possible extensions and applications. Then we review the choice of prior, inference, tests against the linear hypothesis, and conclude with models selectio...

this paper examines regime shifts in tedpix return and volatility and the effects of positive and negative crude oil shocks and gold price fluctuations on stock market shifts behavior using markov switching egarch model with student’s t-distribution. we detect two episodes of series behavior, one relative to low mean/high variance regime namely bear state and the other to high mean/low variance...

The statistical properties of the likelihood ratio test statistic (LRTS) for autoregressive regime-switching models are addressed in this paper. This question is particularly important for estimating the number of regimes in the model. Our purpose is to extend the existing results for mixtures (Liu and Shao, 2003) and hidden Markov chains (Gassiat, 2002). First, we study the case of mixtures of...

This work is concerned with numerical methods for controlled regime-switching diffusions, and regime-switching jump diffusions. Numerical procedures based on Markov chain approximation techniques are developed. Convergence of the algorithms is derived by means of weak convergence methods. In addition, examples are also provided for demonstration purpose. 2006 Elsevier Ltd. All rights reserved.

In this paper, we examine the relationship between volatilities of energy index, crude oil, gas prices, and financial assets (Gold, Bitcoin, G7 stock indexes), especially during coronavirus crisis. The study tests presence regime changes in GARCH volatility dynamics indexes, Gold, (energy gas) by using Markov–Switching model. It estimates dynamic correlation spillover assets, multivariate MSGAR...