Forecasting Using the Markov Chain Transition Matrix for Exchange Rate Fluctuations
DOI:
https://doi.org/10.70516/zaccsssh.v1i1.24Keywords:
Forecasting, Exchange RateAbstract
The current research is preparing an economic statistical study on exchange rate fluctuations for the period from ( 1996 to mid-2005 ) according to the well-known phrase: (The present is the past and the future is the present ). It is a modest attempt to crystallize this type of price in a scientific-statistic method by adopting the matrix of transitional probabilities in Markov chains, as these chains are among the models that are relied upon in the process of forecasting when the data are in the present time and in three cases: - High - Low - Stability. Between the past, the present and the future, the researcher was able to reach in his research to the analysis by applying the method of the greatest places, and to achieve the main purpose of this research, the researcher dealt with four chapters as follows: The first chapter dealt with the problem of research, its importance, need, purpose and determination of its terms. The second chapter reviewed the previous studies published on the subject, as well as the theoretical aspect, in which the matrix of transitional and stable possibilities, the state of stability and independence of the Markov chains, and the estimation of transitional possibilities in the greatest possible way were presented. As for the third chapter, it included the practical aspect and the field application. The data related to the research procedures were collected from the date of (17/10/2003 to 30/6/2005), in which the Iraqi currency was exchanged from the old to the currency currently in circulation, and in which the situation of the Iraqi market suggested great relative stability at the time. Finally, the fourth chapter of this research included the conclusions reached by the researcher from which it came: The market was characterized by a state of stability after the rise in the exchange rate against the dollar, which confirmed the accuracy of the results of the matrix of transitional possibilities, which was reflected on the local stock exchange, as well as the development of recommendations that can be used by the relevant parties.
References
Al-Bakr, Bassam Younis, " Planning University Education Using the Markov Chains Method," Al-Rafidain Magazine, Volume Eighteen, No. 48, 1996.
Dujaili, Lamia " Building Manpower Planning at the Public Establishment for the Distribution of Baghdad Electricity" 1997.
Al-Rubaie, Fadel Mohsen and Abdul, Salah Hamza, "Introduction to Chance Operations," Dar Al-Kitab Directorate of Printing and Publishing , Baghdad , 2005 .
Al-Ziyadi, Safaa "The use of Markov chains and programming goals in the workforce chart with application" 2003.
Al-Saidi, Asmaa " Estimating the Transitional Possibilities of Unstable Ending Markov Chains" 2002.
Al-Athari, Faris Muslim, and the agent, Ali Abdul Hussein, "Incidental Operations" University of Baghdad, Mosul University Press, 1991.
Sven, Lotfi Louise, “Operations Research: Quantitative Approach to Decision Making,” pp. 523-528.
Abdelkader, “The use of Markov chains in predicting wheat productivity in Algeria,” University of Constantine 2, Faculty of Economic Sciences, pp. 171-183, 2015.
Anderson T.W. and L.A. Comanman "Statistical Inferences about Markov Chain" The Annals of Mathematical statistics, ( 28-48-110) , 1957.
10. Henry , Neil with Retention model "A Markov Chain with variable transition probabilities" J ASA, Vol.(66), No (334)June , pp(264-267), 1971.
11. Lee,T.C. & Judge, G. G. "Estimation of Transition Probabilities in Non-stationary Finite Markove Chain" 1972.
Rausser .Gorden . and Thomas "Domain representations of futures prices as astochastic process" Jasa Vol. (67) No(337), Markov , pp (23-39) , 1972.
Bath,V.N. "Elements of Applied Stochastic Processes" John Wiley & Sons , Inc. , New York 1972.
Bhat Tachagya,G. K and Johnson, r.a. "statistical concepts and methods", New York. John Wiley & Sons.
Grimett G.R. " Probability & Random processes" 2nd Edi , Clarend press , Oxford , 1992 .
Kijma,M "Markov processes for stochactic Modeling" Chapman & Hall , London , 1997.
Lawler,G,“Introduction to Stochastic processes” Chapman & Hall,London 1997.
Lee T.C. Indge,G.G. & Zellner A. "Estimating the parameters of Markov probability Model from Aggregate time series Data",(2nd edition) North Holland publishim company , 1970.
Ogata,Y. "Maximum Liklehood Estimates in oreet Markov model for time Series and Derivation of Aic"Journal of Applid probability Vol. (17) , pp (59-72) , 1980.
Ross,S.M.,"Stochastic processes" 2nd Ed.,Jhon Wiley & Son,Inc., 1996.
R.H. Howard "Dynamic probabilistic systems" Vol (1) , New York John Wiley and Sons 1971.
Sirl , David "Markov Chains ; An Introduction / Review" the university of queensland Australia , April , p(1) , 2005. sirl@maths.uq.edu.au D www.maths.uq.edu.au/dsirl
http://crypto@mal.sbg.ac.at/nste/diss/nodetAuthor, Title. Degree, Academic Department, University, Place Published
Downloads
Published
How to Cite
Conference Proceedings Volume
Section
License
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Open Access and Copyright: ZAC Conference Series operates as an open-access proceeding, making all its articles freely available to everyone. Published content is licensed under the Creative Commons Attribution International Public License (CC BY 4.0). This license allows individuals and organizations to:
- Download, share, distribute, and print full texts of articles
- Reproduce or link to articles in any medium,
While authors retain copyright for their published work on the ZAC Conference Series website, the Conference Series actively promotes and tracks citations to increase recognition for their research.
In essence, CC-BY-4.0 encourages the widest possible dissemination and utilization of published articles as long as written permission and appropriate credit are given to the authors.