Evaluating Expert Decision Systems for Exchange Rate Insurance

Susana Álvarez-Díez, J. Samuel Baixauli-Soler and Anna Kondratenko
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Susana Álvarez-Díez: Faculty of Economics and Business, University of Murcia, Spain
J. Samuel Baixauli-Soler: Faculty of Economics and Business, University of Murcia, Spain
Anna Kondratenko: Faculty of Economics and Business, University of Murcia, Spain

International Journal of Business Analytics (IJBAN), 2025, vol. 12, issue 1, 1-25

Abstract: Global trade volumes which set new records yearly indicate growth of commercial operations among an increasing number of companies. This expansion inevitably brings with it the challenge of managing exchange rate risks. As a standard practice, international payments are made within a specified period agreed to in a commercial contract leading to the elevated risks of the exchange rate exposure. To avoid that, many companies decide to use hedging instruments. This paper aims to reduce the extra expenses of hedging by designing an expert decision system. The expert decision system facilitates daily recommendations to a company on the decision of exchange rate hedging. The contribution of this research is twofold. First, it applies the latest machine learning techniques and obtains 79% accuracy in predicting the following day's exchange rate trend. Second, it designs an expert decision system that helps a company reduce its foreign exchange rate exposure managing. The results of backtesting on real data prove the efficiency of the expert decision system.

Date: 2025
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