Exchange Rates’ Change by Using Economic Data with Artificial Intelligence and Forecasting the Crisis
Autor: | Kemal Güler, Abdulkadir Tepecik |
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Rok vydání: | 2019 |
Předmět: |
Estimation
Inflation Index (economics) Variables Computer science business.industry media_common.quotation_subject 020206 networking & telecommunications 02 engineering and technology Field (computer science) Economic data Exchange rate Stock exchange 0202 electrical engineering electronic engineering information engineering General Earth and Planetary Sciences 020201 artificial intelligence & image processing Artificial intelligence business General Environmental Science media_common |
Zdroj: | Procedia Computer Science. 158:316-326 |
ISSN: | 1877-0509 |
DOI: | 10.1016/j.procs.2019.09.057 |
Popis: | Artificial neural networks have recently been widely used in the field of finance as well as in every field. Exchange rates and gold prices are vital for banks, stock exchanges and businesses. Therefore, it is important for such organizations to make accurate estimates of foreign exchange and gold exchange rates. There are many studies that can affect and predict gold prices and exchange rates in the literature review. In this study, it is aimed that the fluctuation in foreign exchange and gold exchange rate can be estimated by using artificial intelligence methods and the forecast results can be used in predicting crisis. In the study, monthly data between 2006 and 2018 were used for USDTRY exchange rate estimation. External factors that may affect the USDTRY exchange rate are added as an independent variable. BIST100 index data, US inflation data, inflation data for Turkey, Turkey American interest data and interest data were used as external factors. Monthly data between 2000 and 2018 were used to estimate gold prices. External factors that may affect gold prices are added as an independent variable. BIST100 index data, silver data, USDTRY exchange rate data and US inflation data were used as external factors. Annual data between the years 2000 and 2018 are used for the forecasting of the crisis. External factors that can trigger the crisis are added as arguments. USDTRY data rate, inflation data for Turkey, and Turkey import data rate data are used as external factors. |
Databáze: | OpenAIRE |
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