Forecasting Exchange Rates Using Artificial Neural Networks: An Applied Study on the Arab Republic of Egypt | ||||
| المجلة العربية للإدارة | ||||
| Articles in Press, Accepted Manuscript, Available Online from 17 November 2024 PDF (404.76 K) | ||||
| Document Type: بحوث باللغة الإنجلیزیة | ||||
| DOI: 10.21608/aja.2024.331953.1740 | ||||
 View on SCiNiTO | ||||
| Author | ||||
Marwa Mansour Nasr Kamouh  
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| Modern Academy for Computer Science and Management Technology in Maadi, Cairo - Egypt | ||||
| Abstract | ||||
| The exchange rate is considered one of the most important economic factors that affect the overall economy of any country. The importance of the exchange rate is represented in international trade, inflation, unemployment, foreign investments, and Monetary policies The study seeks to predict the exchange rate in Egypt using artificial neural networks. The prediction results show that artificial neural networks have high accuracy in predicting the exchange rate in the Arab Republic of Egypt, and the most important factors that affect the exchange rate of the Egyptian pound are: The total stock of external debt (outstanding and disbursed debt, in current US$), GDP (in constant US$), gross capital formation (% of GDP), and the current account balance (balance of payments, in current US$), Inflation, and prices paid by consumers (% annually) - United States of America. | ||||
| Keywords | ||||
| Exchange Rates; Artificial Neural Networks; Monetary Policies; Forecasting Models | ||||
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