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Misspecified Markov Switching Model [PDF]

Economics Bulletin, 2009
I characterize the local power of an optimal test for a Markov Switching model under generalized alternatives. The result shows that the test still has power for the model with endogenous stochastic parameters unless they are orthogonal to the score functions.
Youngki Shin
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Moments of Markov switching models [PDF]

Journal of Econometrics, 2000
Let \(\{\varepsilon_t\}\) be i.i.d. \(N(0,1)\) random variables and \(S_t\) an unobserved stationary ergodic \(k\)-state Markov homogeneous process. The author deals with three types of Markov switching models, namely (MS I) \(y_t=\mu_{S_t} +\sigma_{S_t}\varepsilon_t\), (MS II) \(y_t=\mu_{S_t} +\varphi_1(y_{t-1}-\mu_{S_{t-1}})+\sigma_{S_t}\varepsilon_t\
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Markov-switching mixed-frequency VAR models

International Journal of Forecasting, 2015
Abstract This paper introduces regime switching parameters to the Mixed-Frequency VAR model. We begin by discussing estimation and inference for Markov-switching Mixed-Frequency VAR (MSMF-VAR) models. Next, we assess the finite sample performance of the technique in Monte-Carlo experiments.
Foroni, Claudia, Guérin, Pierre, MARCELLINO, MASSIMILIANO   +2 more
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AN N-STATE ENDOGENOUS MARKOV-SWITCHING MODEL WITH APPLICATIONS IN MACROECONOMICS AND FINANCE

Macroeconomic Dynamics, 2019
We develop an N-regime Markov-switching model in which the latent state variable driving the regime switching is endogenously determined with the model disturbance term. The models structure captures a wide variety of patterns of endogeneity and yields a
Shih-Tang Hwu, Chang‐Jin Kim, Jeremy Piger   +2 more
semanticscholar   +1 more source

Solar Irradiance Forecasting in Remote Microgrids Using Markov Switching Model

IEEE Power & Energy Society General Meeting, 2018
Photovoltaic (PV) systems integration is increasingly being used to reduce fuel consumption in diesel-based remote microgrids. However, uncertainty and low correlation of PV power availability with load reduces the benefits of PV integration.
Ayush Shakya, Semhar Michael, Christopher P. Saunders, Douglas Armstrong, Prakash Pandey, S. Chalise, R. Tonkoski   +6 more
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Adaptive Event-Triggered SMC for Stochastic Switching Systems With Semi-Markov Process and Application to Boost Converter Circuit Model

IEEE Transactions on Circuits and Systems Part 1: Regular Papers, 2021
In this article, the sliding mode control (SMC) design is studied for a class of stochastic switching systems subject to semi-Markov process via an adaptive event-triggered mechanism.
Wenhai Qi, Guangdeng Zong, W. Zheng
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Input–Output Finite-Time Asynchronous SMC for Nonlinear Semi-Markov Switching Systems With Application

IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2022
This article investigates the input–output finite-time stability (IO-FTS) for nonlinear hidden semi-Markov switching systems (S-MSSs) via the asynchronous sliding mode control (SMC) approach. Under the assumption that a detector is set up to estimate the
Wenhai Qi, Guangdeng Zong, C. Ahn
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Sliding Mode Control for Fuzzy Networked Semi-Markov Switching Models Under Cyber Attacks

IEEE Transactions on Circuits and Systems - II - Express Briefs, 2022
Sliding mode control (SMC) is investigated for nonlinear networked stochastic switching systems subject to semi-Markov parameters, in which the model is formulated based on the Takagi-Sugeno (T-S) fuzzy strategy.
Wenhai Qi, Caiyu Lv, Guangdeng Zong, C. Ahn   +3 more
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Testing Markov switching models

Applied Economics, 2014
In this article, we propose a new test for Markov switching models. Unlike the tests in the existing literature (e.g. Hansen, 1992; Garcia, 1998; Cho and White, 2007), we focus on testing the null of two regimes, instead of one single regime, in a switching framework.
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The multi-chain Markov switching model

Journal of Forecasting, 2005
In many real phenomena the behaviour of a certain variable, subject to different regimes, depends on the state of other variables or the same variable observed in other subjects, so the knowledge of the state of the latter could be important to forecast the state of the former. In this paper a particular multivariate Markov switching model is developed
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