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Artykuły w czasopismach na temat „Markov Switching”

Autor: Grafiati

Data publikacji: 4 czerwca 2021

Data aktualizacji: 25 lipca 2025

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1

Liu, Ji-Chun. "INTEGRATED MARKOV-SWITCHING GARCH PROCESS." Econometric Theory 25, no. 5 (2009): 1277–88. http://dx.doi.org/10.1017/s0266466608090506.

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This paper investigates stationarity of the so-called integrated Markov-switching generalized autoregressive conditionally heteroskedastic (GARCH) process, which is an important subclass of the Markov-switching GARCH process introduced by Francq, Roussignol, and Zakoïan (2001, Journal of Time Series Analysis 22,197–220) and a Markov-switching version of the integrated GARCH (IGARCH) process. We show that, like the classical IGARCH process, a stationary solution with infinite variance for the integrated Markov-switching GARCH process may exist. To this purpose, an alternative condition for the

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2

Guérin, Pierre, and Massimiliano Marcellino. "Markov-Switching MIDAS Models." Journal of Business & Economic Statistics 31, no. 1 (2013): 45–56. http://dx.doi.org/10.1080/07350015.2012.727721.

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3

Huang, Yu-Lieh. "Testing Markov switching models." Applied Economics 46, no. 17 (2014): 2047–51. http://dx.doi.org/10.1080/00036846.2014.892201.

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4

Liu, Xiaochun. "Markov switching quantile autoregression." Statistica Neerlandica 70, no. 4 (2016): 356–95. http://dx.doi.org/10.1111/stan.12091.

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5

Hou, Zhenting, Hailing Dong, and Peng Shi. "Asymptotic stability in the distribution of nonlinear stochastic systems with semi-Markovian switching." ANZIAM Journal 49, no. 2 (2007): 231–41. http://dx.doi.org/10.1017/s1446181100012803.

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abstractIn this paper, finite phase semi-Markov processes are introduced. By introducing variables and a simple transformation, every finite phase semi-Markov process can be transformed to a finite Markov chain which is called its associated Markov chain. A consequence of this is that every phase semi-Markovian switching system may be equivalently expressed as its associated Markovian switching system. Existing results for Markovian switching systems may then be applied to analyze phase semi-Markovian switching systems. In the following, we obtain asymptotic stability for the distribution of n

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6

ELLIOTT, ROBERT J., TAK KUEN SIU, and LEUNGLUNG CHAN. "OPTION PRICING FOR GARCH MODELS WITH MARKOV SWITCHING." International Journal of Theoretical and Applied Finance 09, no. 06 (2006): 825–41. http://dx.doi.org/10.1142/s0219024906003846.

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In this paper we develop a method for pricing derivatives under a Markov switching version of the Heston-Nandi GARCH (1, 1) model by using a well known tool from actuarial science, namely the Esscher transform. We suppose that the dynamics of the GARCH process switch over time according to one of the regimes described by the states of an observable Markov chain process. By augmenting the conditional Esscher transform with the observable Markov switching process, a Markov switching conditional Esscher transform (MSCET) is developed to identify a martingale measure for option valuation in the in

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7

Sun, Zhongyang, Isabelle Kemajou-Brown, and Olivier Menoukeu-Pamen. "A risk-sensitive maximum principle for a Markov regime-switching jump-diffusion system and applications." ESAIM: Control, Optimisation and Calculus of Variations 24, no. 3 (2018): 985–1013. http://dx.doi.org/10.1051/cocv/2017039.

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In this paper, we derive a general stochastic maximum principle for a risk-sensitive type optimal control problem of Markov regime-switching jump-diffusion model. The results are obtained via a logarithmic transformation and the relationship between adjoint variables and the value function. We apply the results to study both a linear-quadratic optimal control problem and a risk-sensitive benchmarked asset management problem for Markov regime-switching models. In the latter case, the optimal control is of feedback form and is given in terms of solutions to a Markov regime-switching Riccatti equ

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8

Nunian, Mohd Azizi Amin, Siti Meriam Zahari, and S. Sarifah Radiah Shariff. "Modelling foreign exchange rates: a comparison between markov-switching and markov-switching GARCH." Indonesian Journal of Electrical Engineering and Computer Science 20, no. 2 (2020): 917. http://dx.doi.org/10.11591/ijeecs.v20.i2.pp917-923.

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Foreign exchange rate is important as it determines a country's economic condition. It is used to carry out transfers of purchasing power between two or more countries. Volatility in exchange rates may result in difficulty in decision making especially, in financial sectors as high volatility could increase the risk in exchange rates. Thus, Markov switching model is employed in this study as it is believed to be efficient in handling not only volatilility but also nonlinearity characteristics in exchange rates. The aims of this study are to model the foreign exchange rates using two models; Ma

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9

Fuh, Cheng-Der, Kwok Wah Remus Ho, Inchi Hu, and Ren-Her Wang. "Option Pricing with Markov Switching." Journal of Data Science 10, no. 3 (2021): 483–509. http://dx.doi.org/10.6339/jds.201207_10(3).0008.

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10

Petričková, Anna. "Moments of Markov-Switching Models." Tatra Mountains Mathematical Publications 61, no. 1 (2014): 131–40. http://dx.doi.org/10.2478/tmmp-2014-0032.

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Abstract In this paper we have focused on the class of regime-switching time series models with regimes determined by unobservable variables, concretely Markov-switching models. We have derived 2nd central moment of the MSW models for two cases-state-independent and state-dependent model

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11

Chiappa, Silvia. "Explicit-Duration Markov Switching Models." Foundations and Trends® in Machine Learning 7, no. 6 (2014): 803–86. http://dx.doi.org/10.1561/2200000054.

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12

Malyutov, M. B. "Offline fitting Markov switching model." Model Assisted Statistics and Applications 14, no. 3 (2019): 193–213. http://dx.doi.org/10.3233/mas-190461.

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13

Tsionas, Efthymios G., and Subal C. Kumbhakar. "Markov switching stochastic frontier model." Econometrics Journal 7, no. 2 (2004): 398–425. http://dx.doi.org/10.1111/j.1368-423x.2004.00137.x.

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14

Serletis, Apostolos, and Libo Xu. "Markov Switching Oil Price Uncertainty." Oxford Bulletin of Economics and Statistics 81, no. 5 (2019): 1045–64. http://dx.doi.org/10.1111/obes.12300.

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15

Langrock, Roland, Thomas Kneib, Richard Glennie, and Théo Michelot. "Markov-switching generalized additive models." Statistics and Computing 27, no. 1 (2015): 259–70. http://dx.doi.org/10.1007/s11222-015-9620-3.

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16

Timmermann, Allan. "Moments of Markov switching models." Journal of Econometrics 96, no. 1 (2000): 75–111. http://dx.doi.org/10.1016/s0304-4076(99)00051-2.

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17

Yang, Haoyue, Hao Zhao, Zhuping Wang та Xuemei Zhou. "ℋ∞ leader-following consensus of multi-agent systems with channel fading under switching topologies: a semi-Markov kernel approach". Intelligence & Robotics 2, № 3 (2022): 223–43. http://dx.doi.org/10.20517/ir.2022.19.

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This paper focuses on the leader-following consensus problem of discrete-time multi-agent systems subject to channel fading under switching topologies. First, a topology switching-based channel fading model is established to describe the information fading of the communication channel among agents, which also considers the channel fading from leader to follower and from follower to follower. It is more general than models in the existing literature that only consider follower-to-follower fading. For discrete multi-agent systems, the existing literature usually adopts time series or Markov proc

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18

Tan, Zhenni, and Yuehua Wu. "On Regime Switching Models." Mathematics 13, no. 7 (2025): 1128. https://doi.org/10.3390/math13071128.

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Regime switching models have been widely studied for their ability to capture the dynamic behavior of time series data and are widely used in economic and financial data analysis. This paper reviews various regime switching models with various regime switching mechanisms, including threshold models, hidden Markov regime switching models, hidden semi-Markov regime switching models, and smooth transition models. The focus is on regime switching models for time series, studying their underlying frameworks, popular variants, and commonly used estimation methods. In addition, six different regime s

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19

Pan, Lijun, Jinde Cao, and Ahmed Alsaedi. "Stability of reaction–diffusion systems with stochastic switching." Nonlinear Analysis: Modelling and Control 24, no. 3 (2019): 315–31. http://dx.doi.org/10.15388/na.2019.3.1.

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In this paper, we investigate the stability for reaction systems with stochastic switching. Two types of switched models are considered: (i) Markov switching and (ii) independent and identically distributed switching. By means of the ergodic property of Markov chain, Dynkin formula and Fubini theorem, together with the Lyapunov direct method, some sufficient conditions are obtained to ensure that the zero solution of reaction–diffusion systems with Markov switching is almost surely exponential stable or exponentially stable in the mean square. By using Theorem 7.3 in [R. Durrett, Probability:

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20

Anh, Nguyen Bao, and Yiqiang Q. Zhao. "Half Century of Gold Price: Regime-Switching and Forecasting Framework." International Journal of Financial Research 12, no. 3 (2021): 1. http://dx.doi.org/10.5430/ijfr.v12n3p1.

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This paper studies the history of gold price in the international context using Markov-switching models. The literature surrounding the Markov-switching model is reviewed from the earliest iterations of Hamilton to recent developments. We show applicability of Markov stochastic process in forecasting commodity prices; in particular, the gold spot price. The research imposes the features of Markov regime-switching models, considering gold as a financial asset to offer a comprehensive methodology for forecasting commodity price. The paper discovers that applying Markov regime-switching could sig

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21

Anh, Nguyen Bao, and Yiqiang Q. Zhao. "Half Century of Gold Price: Regime-Switching and Forecasting Framework." International Journal of Financial Research 12, no. 3 (2021): 1. http://dx.doi.org/10.5430/ijfr.v12n3p1.

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This paper studies the history of gold price in the international context using Markov-switching models. The literature surrounding the Markov-switching model is reviewed from the earliest iterations of Hamilton to recent developments. We show applicability of Markov stochastic process in forecasting commodity prices; in particular, the gold spot price. The research imposes the features of Markov regime-switching models, considering gold as a financial asset to offer a comprehensive methodology for forecasting commodity price. The paper discovers that applying Markov regime-switching could sig

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22

Wu, Huiming, and Sicong Guo. "Switching Control of Closed-Loop Supply Chain Systems with Markov Jump Parameters." Applied Sciences 13, no. 11 (2023): 6798. http://dx.doi.org/10.3390/app13116798.

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The switching system model of a closed-loop supply chain with Markov jump parameters is established. The system is modeled as a switching system with Markov jump parameters, taking into account the uncertainties of the process and the inventory decay factors. The Markov switching idea is applied to the controller design and performance analysis of the system to effectively suppress the bullwhip effect while ensuring the stability of the closed-loop supply chain system. Simulation examples are presented to illustrate the validity of the results obtained.

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23

Ji, Hankang, Yuanyuan Li, Xueying Ding, and Jianquan Lu. "Stability analysis of Boolean networks with Markov jump disturbances and their application in apoptosis networks." Electronic Research Archive 30, no. 9 (2022): 3422–34. http://dx.doi.org/10.3934/era.2022174.

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<abstract><p>In this paper, the finite-time stability (FTS) of switched Boolean networks (SBNs) with Markov jump disturbances under the conditions of arbitrary switching signals is studied. By using the tool of the semi-tensor product, the equivalent linear-like form of SBNs with Markov jump disturbances is first established. Next, to facilitate investigation, we convert the addressed system into an augmented Markov jump Boolean network (MJBN), and propose the definition of the switching set reachability of MJBNs. A necessary and sufficient criterion is developed for the FTS of SBN

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24

Zhang, Mengzhe, and Leunglung Chan. "Saddlepoint Method for Pricing European Options under Markov-Switching Heston’s Stochastic Volatility Model." Journal of Risk and Financial Management 15, no. 9 (2022): 396. http://dx.doi.org/10.3390/jrfm15090396.

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This paper evaluates the prices of European-style options when dynamics of the underlying asset is assumed to follow a Markov-switching Heston’s stochastic volatility model. Under this framework, the expected return and the long-term mean of the variance of the underlying asset rely on states of the economy modeled by a continuous-time Markov chain. There is evidence that the Markov-switching Heston’s stochastic volatility model performs well in capturing major events affecting price dynamics. However, due to the nature of the model, analytic solutions for the prices of options or other financ

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25

Johannesson, Pär. "Rainflow Cycles for Switching Processes with Markov Structure." Probability in the Engineering and Informational Sciences 12, no. 2 (1998): 143–75. http://dx.doi.org/10.1017/s026996480000512x.

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The concept of rainflow cycles is often used in fatigue of materials for analyzing load processes. Methods are developed for computation of the rainflow matrix for a random load that is changing properties over time due to changes of the system dynamics; for example, for a random vehicle load it could reflect different driving conditions. The random load is modeled by a switching process with Markov regime; that is, the random load changes properties according to a hidden (not observed) Markov chain.An algorithm is developed for a switching process where each part of the load is modeled by a M

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26

Liu, Kai, Xiaowu Mu, and Jumei Wei. "Stochastic Stability of Discrete-Time Switched Systems with a Random Switching Signal." Mathematical Problems in Engineering 2015 (2015): 1–9. http://dx.doi.org/10.1155/2015/191458.

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Necessary and sufficient condition for stochastic stability of discrete-time linear switched system with a random switching signal is considered in this paper, assuming that the switching signal allows fixed dwell time before a Markov switch occurs. It is shown that the stochastic stability of the system is equivalent to that of an auxiliary system with state transformations at switching time, whose switching signal is a Markov chain. The stochastic stability is studied using a stochastic Lyapunov approach. The effectiveness of the proposed approach is demonstrated by a numerical example.

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27

Djafri, Houria, and Soumia Kharfouchi. "Unilateral 2D Markov-switching autoregressive model." International Journal of Mathematics in Operational Research 18, no. 4 (2021): 433. http://dx.doi.org/10.1504/ijmor.2021.114208.

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28

Bohl,, Martin T., Arne C. Klein,, and Pierre L. Siklos. "A Markov Switching Approach to Herding." Credit and Capital Markets – Kredit und Kapital 49, no. 2 (2016): 193–220. http://dx.doi.org/10.3790/ccm.49.2.193.

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29

Boot, Tom, and Andreas Pick. "Optimal Forecasts from Markov Switching Models." Journal of Business & Economic Statistics 36, no. 4 (2017): 628–42. http://dx.doi.org/10.1080/07350015.2016.1219264.

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30

Guérin, Pierre, Danilo Leiva-Leon, and Massimiliano Marcellino. "Markov-Switching Three-Pass Regression Filter." Journal of Business & Economic Statistics 38, no. 2 (2018): 285–302. http://dx.doi.org/10.1080/07350015.2018.1497508.

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31

Cheung, Yin-Wong, and Ulf G. Erlandsson. "Exchange Rates and Markov Switching Dynamics." Journal of Business & Economic Statistics 23, no. 3 (2005): 314–20. http://dx.doi.org/10.1198/073500104000000488.

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32

Cheng, J. "A transitional Markov switching autoregressive model." Communications in Statistics - Theory and Methods 45, no. 10 (2016): 2785–800. http://dx.doi.org/10.1080/03610926.2014.894065.

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33

Breunig, Robert, Serinah Najarian, and Adrian Pagan. "Specification Testing of Markov Switching Models*." Oxford Bulletin of Economics and Statistics 65, s1 (2003): 703–25. http://dx.doi.org/10.1046/j.0305-9049.2003.00093.x.

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34

Murray, Christian J., Alex Nikolsko-Rzhevskyy, and David H. Papell. "MARKOV SWITCHING AND THE TAYLOR PRINCIPLE." Macroeconomic Dynamics 19, no. 4 (2014): 913–30. http://dx.doi.org/10.1017/s1365100513000667.

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Early research on the Taylor rule typically divided the data exogenously into pre-Volcker and Volcker–Greenspan subsamples. We contribute to the recent trend of endogenizing changes in monetary policy by estimating a real-time forward-looking Taylor rule with endogenous Markov switching coefficients and variance. The response of the interest rate to inflation is regime-dependent, with the pre- and post-Volcker samples containing monetary regimes where the Fed did and did not follow the Taylor principle. Although the Fed consistently adhered to the Taylor principle before 1973 and after 1984, i

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35

Chauvet, Marcelle, Chinhui Juhn, and Simon Potter. "Markov switching in disaggregate unemployment rates." Empirical Economics 27, no. 2 (2002): 205–32. http://dx.doi.org/10.1007/s001810100101.

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36

Kim, Chang-Jin. "Dynamic linear models with Markov-switching." Journal of Econometrics 60, no. 1-2 (1994): 1–22. http://dx.doi.org/10.1016/0304-4076(94)90036-1.

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37

Krämer, Walter. "Long memory with Markov-Switching GARCH." Economics Letters 99, no. 2 (2008): 390–92. http://dx.doi.org/10.1016/j.econlet.2007.09.027.

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38

Taddy, Matthew A., and Athanasios Kottas. "Markov switching Dirichlet process mixture regression." Bayesian Analysis 4, no. 4 (2009): 793–816. http://dx.doi.org/10.1214/09-ba430.

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39

Otranto, Edoardo. "Adding flexibility to Markov Switching models." Statistical Modelling 16, no. 6 (2016): 477–98. http://dx.doi.org/10.1177/1471082x16672025.

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Abstract: Very often time series are subject to abrupt changes in the level, which are generally represented by Markov Switching (MS) models, assuming that the level is constant within a certain state (regime). This is not a realistic framework because in the same regime the level could change with minor jumps with respect to a change of state; this is a typical situation in many economic time series such as the Gross Domestic Product (GDP) or the volatility of financial markets. We propose to make the state flexible, introducing a very general model which provides oscillations of the level of

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40

Aliat, Billel, and Fayçal Hamdi. "On Markov-switching periodic ARMA models." Communications in Statistics - Theory and Methods 47, no. 2 (2017): 344–64. http://dx.doi.org/10.1080/03610926.2017.1303734.

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41

Billio, Monica, and Silvio Di Sanzo. "Granger-causality in Markov switching models." Journal of Applied Statistics 42, no. 5 (2015): 956–66. http://dx.doi.org/10.1080/02664763.2014.993367.

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42

Lanne, Markku, Helmut Lütkepohl, and Katarzyna Maciejowska. "Structural vector autoregressions with Markov switching." Journal of Economic Dynamics and Control 34, no. 2 (2010): 121–31. http://dx.doi.org/10.1016/j.jedc.2009.08.002.

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43

Karamé, Frédéric. "Asymmetries and Markov-switching structural VAR." Journal of Economic Dynamics and Control 53 (April 2015): 85–102. http://dx.doi.org/10.1016/j.jedc.2015.01.007.

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44

Farmer, Roger E. A., Daniel F. Waggoner, and Tao Zha. "Understanding Markov-switching rational expectations models." Journal of Economic Theory 144, no. 5 (2009): 1849–67. http://dx.doi.org/10.1016/j.jet.2009.05.004.

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45

Nikolsko-Rzhevskyy, Alex, and Ruxandra Prodan. "Markov switching and exchange rate predictability." International Journal of Forecasting 28, no. 2 (2012): 353–65. http://dx.doi.org/10.1016/j.ijforecast.2011.04.007.

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46

Foroni, Claudia, Pierre Guérin, and Massimiliano Marcellino. "Markov-switching mixed-frequency VAR models." International Journal of Forecasting 31, no. 3 (2015): 692–711. http://dx.doi.org/10.1016/j.ijforecast.2014.05.003.

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Otranto, Edoardo. "The multi-chain Markov switching model." Journal of Forecasting 24, no. 7 (2005): 523–37. http://dx.doi.org/10.1002/for.965.

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Ma, Guiyuan, Chi Chung Siu, Sheung Chi Phillip Yam, and Zeyu Zhou. "Dynamic trading with Markov liquidity switching." Automatica 155 (September 2023): 111156. http://dx.doi.org/10.1016/j.automatica.2023.111156.

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Casarin, Roberto, Radu V. Craiu, and Qing Wang. "Markov switching multiple-equation tensor regressions." Journal of Multivariate Analysis 208 (July 2025): 105427. https://doi.org/10.1016/j.jmva.2025.105427.

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Valencia-Herrera, Humberto, and Francisco López-Herrera. "Markov Switching International Capital Asset Pricing Model, an Emerging Market Case: Mexico." Journal of Emerging Market Finance 17, no. 1 (2018): 96–129. http://dx.doi.org/10.1177/0972652717748089.

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The article shows how the international capital asset pricing model (ICAPM) with Markov regime switching can model the asset returns in the emerging market of Mexico. For most assets, although significant, the international risk premium factor is not subject to regime switching, but the domestic factor is. The probabilities of regimes are correlated with the volatility of assets. A GARCH(1,1) Markov regime switching model offers better adjustment than a non-GARCH. JEL Classification: C58, F36, F65, G12, G15

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