Document Type : Research Article
Authors
- Mahdi Pourrafiee 1
- S. M. Esmaeil Pourmohammad Azizi 2
- Marzieh Mohammadi Larijani 1
- Ali Pahlevannezhad 3
1 Department of Mathematics and Computer Science, Allameh Tabataba'i University, Tehran, Iran.
2 Department of Mathematics and Computer Science, Allameh Tabataba’i University, Tehran, Iran.
3 Department of Management and Accounting, Allameh Tabataba'i University, Tehran, Iran.
Abstract
According to the rule of equality of equal prices, the price of a foreign commodity within a country depends on the price of the commodity at the origin as well as the exchange rate of that country. According to this rule, if the foreign exchange costs are insignificant, the price of a single commodity will be the same everywhere in terms of price, and ideally the purchasing power of a currency inside and outside the country will be the same. Due to the effect of the exchange rate on financial assets, study of regime change in exchange rate fluctuations is importance and Regime Switching model is the most complete and populare regime change. The aim of this research is to modeling Euro-Rial exchange rate under the model of Markov regime switching and Markov random regime switching model. In order to evaluate the achieved results, unit root test, which included the Dickey-Fuller test and the Phillips-Peron test, is used to estimates Markov regime switching and Markov random regime switching parameters in order to find the best fluctuations model.
Keywords
[2] Y. Ning, L. Zhang, Modeling dynamics of short-term international capital ows in china: A markov regime switching approach, The North American Journal of Economics and Finance 44 (2018) 193{203.
[3] S. Papadamou, T. Markopoulos, Interest rate pass through in a markov-switching vector autoregression model: Evidence from greek retail bank interest rates, The Journal of Economic Asymmetries 17 (2018) 48{60.
[4] J.-T. Wu, Markov regimes switching with monetary fundamental-based exchange rate model, Asia Paci c management review 20 (2) (2015) 79{89.
[5] S. M. E. P. Azizi, A. Neisy, Mathematic modelling and optimization of bank asset and liability by using fractional goal programing approach, International Journal of Modeling and Optimization 7 (2) (2017) 85.
[6] G. C. Aye, T. Chang, R. Gupta, Is gold an in ation-hedge? evidence from an interrupted markov-switching cointegration model, Resources Policy 48 (2016) 77{84.
[8] B. M. Lucey, F. A. O'Connor, Do bubbles occur in the gold price? an investigation of gold lease rates and markov switching models, Borsa Istanbul Review 13 (3) (2013) 53{63.
[9] S. M. E. P. M. Azizi, A. Neisy, A new approach in geometric brownian motion model, in: International workshop on Mathematics and Decision Science, Springer, 2016, pp. 336{342.
[10] H.-Y. Lee, S.-L. Chen, Why use markov-switching models in exchange rate prediction, Economic Modelling 23 (4) (2006) 662{668.
[11] R. Mohamadinejad, J. Biazar, A. Neisy, Spread option pricing using two jump diffusion interest rates, UNIVERSITY POLITEHNICA OF BUCHAREST SCIENTIFIC BULLETIN-SERIES A-APPLIED MATHEMATICS AND PHYSICS 82 (1) (2020) 171{182.
[12] M. Karimnejad Esfahani, A. Neisy, S. De Marchi, An rbf approach for oil futures pricing under the jump-diffusion model, Journal of Mathematical Modeling (2020) 1{12.
[13] A. H. Nafei, W. Yuan, H. Nasseri, Group Multi-Attribute Decision Making Based on Interval Neutrosophic Sets, Vol. 28, In nite Study, 2019.
[14] A. Z. Baharumshah, S.-V. Soon, M. E. Wohar, Markov-switching analysis of exchange rate pass-through: Perspective from asian countries, International Review of Economics & Finance 51 (2017) 245{257.
[15] H. Fahmy, Regime switching in commodity prices, Ph.D. thesis, Concordia University (2011).
[16] J. D. Hamilton, Speci cation testing in markov-switching time-series models Journal of econometrics 70 (1) (1996) 127{157.
[17] P. Shahrestani, M. Rafei, The impact of oil price shocks on tehran stock exchange returns: Application of the markov switching vector autoregressive models, Resources Policy 65 (2020) 101579.
[18] J. Gonzalo, J.-Y. Pitarakis, et al., Estimation and inference in threshold typeregime switching models, Handbook of Research Methods and Applications in Empirical Macroeconomics, edited by Nigar Hashimzade and Michael A. Thornton (2013) 189{205.
[19] W. Dai, A. Serletis, On the markov switching welfare cost of in ation, Journal of Economic Dynamics and Control 108 (2019) 103748.
[20] H. Tong, Threshold models in time series analysis30 years on, Statistics and its Interface 4 (2) (2011) 107{118.
[21] D. V. Paliouras, Comparing regime-switching models in time series: Logistic mixtures vs. markov switching, Ph.D. thesis (2007).
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