Academic literature on the topic 'Markov-switching regression model'

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Journal articles on the topic "Markov-switching regression model"

1

Qazi, Atika, Ram Gopal Raj, and Celestine O. Eledo. "PATTERN PREDICTION OF CRUDE OIL USING REGRESSION MODERATED WITH MARKOV SWITCHING MODEL." Malaysian Journal of Computer Science 32, no. 2 (2019): 149–62. http://dx.doi.org/10.22452/mjcs.vol32no2.5.

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Xaba,, Diteboho, Ntebogang Dinah Moroke,, and Ishmael Rapoo. "Modeling Stock Market Returns of BRICS with a Markov-Switching Dynamic Regression Model." Journal of Economics and Behavioral Studies 11, no. 3(J) (2019): 10–22. http://dx.doi.org/10.22610/jebs.v11i3(j).2865.

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This article adopted a Markov-switching dynamic regression (MS-DR) model to estimate appropriate models for BRICS countries. The preliminary analysis was done using data from 01/1997 to 01/2017 and to study the movement of 5 stock market returns series. The study further determined if stock market returns exhibit nonlinear relationship or not. The purpose of the study is to measure the switch in returns between two regimes for the five stock market returns, and, secondly, to measure the duration of each regime for all the stock market returns under examination. The results proved the MS-DR mod
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Bojanic, Antonio N. "A Markov-Switching Model of Inflation in Bolivia." Economies 9, no. 1 (2021): 37. http://dx.doi.org/10.3390/economies9010037.

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The Bolivian inflation process is analyzed utilizing a time-varying univariate and multivariate Markov-switching model (TMS). With monthly data and, beginning in the late 1930s, inflation is accurately described by a univariate TMS. The intercept for the high-inflation regime is significantly higher than for the low-inflation regime and the actual inflation rate mirrors the smoothing probabilities of the Markov process. Additionally, the predicted duration of each regime closely fits the periods when the country experienced low and inordinate high inflation rates. From a long-run perspective a
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Nobrega, Wellington Charles Lacerda, Cássio da Nóbrega Besarria, and Felipe Araújo De Oliveira. "Unemployment rate and wage growth in Brazil: evidence from a Markov-switching model." Economia Aplicada 24, no. 2 (2020): 171–94. http://dx.doi.org/10.11606/1980-5330/ea151926.

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This paper has the purpose to investigate the relationship between unemployment rate and wage growth for the Brazilian economy from 2000to 2016, by means of a Markov-switching regression model. The empirical approach is based on the New-Keynesian Phillips Curve developed by Galí (2011). The estimation results suggest the existence of two well definedregimes, one characterized by the non-validation of the Phillips Curve, while in the other the trade-off between unemployment and wageinflation is validated, with the economic cycle being a key factor in regime switching.
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5

Li, M., and S. Yen. "Re-examining covariance risk dynamics in international stock markets using quantile regression analysis." Acta Oeconomica 61, no. 1 (2011): 33–59. http://dx.doi.org/10.1556/aoecon.61.2011.1.3.

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This investigation is one of the first to adopt quantile regression (QR) technique to examine covariance risk dynamics in international stock markets. Feasibility of the proposed model is demonstrated in G7 stock markets. Additionally, two conventional random-coefficient frameworks, including time-varying betas derived from GARCH models and state-varying betas implied by Markov-switching models, are employed and subjected to comparative analysis. The empirical findings of this work are consistent with the following notions. First, the beta smile (beta skew) curve for the Italian, U.S. and U.K.
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Yamaka, Woraphon, Xuefeng Zhang, and Paravee Maneejuk. "Analyzing the Influence of Transportations on Chinese Inbound Tourism: Markov Switching Penalized Regression Approaches." Mathematics 9, no. 5 (2021): 515. http://dx.doi.org/10.3390/math9050515.

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This study investigates the nonlinear impact of various modes of transportation (air, road, railway, and maritime) on the number of foreign visitors to China originating from major source countries. Our nonlinear tourism demand equations are determined through the Markov-switching regression (MSR) model, thereby, capturing the possible structural changes in Chinese tourism demand. Due to many variables and the limitations from the small number of observations confronted in this empirical study, we may face multicollinearity and endogeneity bias. Therefore, we introduce the two penalized maximu
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Zahro, Maratus, and Rika Rahayu. "Nilai Transaksi E-Money di Indonesia dengan Menggunakan Metode Markov Switching Model." Owner 5, no. 2 (2021): 644–52. http://dx.doi.org/10.33395/owner.v5i2.392.

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The purpose of the research is to examine and analyze the interest rates, inflation rates, stock returns, and holiday conditions on the values of e-money transactions based on two conditions, before and after the issuance of Bank Indonesia regulations. The research data used in this study is the monthly statistical data of the Bank Indonesia payment system for the period 2008-2018. While, the research was the quantitative using the Markov Regime Switching Model and hypothesis testing using time series regression. The research results showed that there was a significant effect between the infla
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Dombrovskii, Vladimir V., and Tatiana Yu Pashinskaya. "Optimal predictive control strategies for systems with random parameters described by multidimensional Markov switching regression model." Vestnik Tomskogo gosudarstvennogo universiteta. Upravlenie, vychislitel'naya tekhnika i informatika, no. 48 (September 1, 2019): 4–12. http://dx.doi.org/10.17223/19988605/48/1.

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9

Samitas, Aristeidis, and Aggelos Armenatzoglou. "Regression tree model versus Markov regime switching: a comparison for electricity spot price modelling and forecasting." Operational Research 14, no. 3 (2014): 319–40. http://dx.doi.org/10.1007/s12351-014-0149-6.

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10

Makatjane, Katleho, and Diteboho Xaba. "An early warning system for inflation using Markov-Switching and logistic models approach." Risk Governance and Control: Financial Markets and Institutions 6, no. 4 (2016): 30–39. http://dx.doi.org/10.22495/rcgv6i4art5.

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With the adoption of the inflation targeting by the South African Reserve Bank (SARB) in 2000, the average inflation radically went down. Earlier 2000, the inflation rate was recorded at 8.8% that is January 1999; then a year later went down to 2.65%. What’s more, this paper builds up an early warning system (EWS) model for predicting the event of high inflation in South Africa. Periods of high and low inflation were distinguished by utilizing Markov-switching model. Utilizing the results of regime classification, logistic regression models were then assessed with the goal of measuring the lik
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