Modeling and Predicting the Egyptian Pound's Exchange Rate Per the American Dollar on a Short-Term Scale by Using ARIMA – Probability Distributions

Ghareeb A. Marei *

Faculty of Computers and Information System, Egyptian Chinese University, Cairo, Egypt.

Hassan Ismail Faris Aly

Higher Institute for Computers & Information Technology, El Shorouk, Cairo, Egypt.

Mohammed Ahmed Farouk

Higher Institute for Computers & Information Technology, El Shorouk, Cairo, Egypt.

*Author to whom correspondence should be addressed.


Abstract

A time series is an ordered sequence of data points that are chronologically indexed. By evaluating the values in a time series both presently and retrospectively, it is possible to predict the future values of most time series with a reasonable degree of accuracy. In this paper modeling of Egyptian pound exchange rate per US dollar in the short term by using the ARIMA model and many probability distributions. The ARIMA  is the best ARIMA  that assumed in this study in modeling the data set of the exchange rate of the pound in Egypt per US dollar and the Burr probability distribution is the best probability distribution in modeling the same data set.

Keywords: Exchange rate, ARIMA model, probability distributions


How to Cite

Marei , Ghareeb A., Hassan Ismail Faris Aly, and Mohammed Ahmed Farouk. 2024. “Modeling and Predicting the Egyptian Pound’s Exchange Rate Per the American Dollar on a Short-Term Scale by Using ARIMA – Probability Distributions”. Asian Journal of Probability and Statistics 26 (1):1-12. https://doi.org/10.9734/ajpas/2024/v26i1576.

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