MODELING THE EURO/DOLLAR EXCHANGE RATE USING EXTREME VALUE THEORY

Objective: This study examines the application of Extreme Value Theory (EVT) in economics to understand and manage rare, high-impact events that affect financial markets and economic stability. Theoretical framework: EVT provides a statistical foundation for modeling extreme variations in financial data, making it an essential tool for risk assessment and economic decision-making. By estimating the probability of extreme fluctuations, EVT enhances the understanding of financial risk exposure. Method: We analyze daily Eurodollar exchange rate data from January 1, 1999, to March 22, 2024, obtained from Yahoo Finance, totaling approximately 6,580 observations. The monthly maximum values were extracted and modeled using the Generalized Extreme Value (GEV) distribution. Results and Discussion: The"Return Level Plot" derived from the GEV model highlights potential changes in extreme values of the Eurodollar exchange rate over time. The findings provide valuable insights into financial risk exposure and potential economic fluctuations. The estimated parameters for the GEV distribution are: location parameter (1.15), scale parameter (0.15), and shape parameter (-0.27). To ensure the robustness of results, the Kolmogorov-Smirnov test was applied, confirming the goodness-of-fit of the GEV model. Research Implications: This study contributes to financial risk management by offering a methodological approach to modeling extreme exchange rate fluctuations. It assists policymakers and financial analysts in preparing for and mitigating risks associated with extreme currency movements. Originality/value: This research provides empirical evidence supporting the use of EVT in financial market analysis. It emphasizes the relevance of EVT in risk management and economic decision-making by demonstrating its effectiveness in modeling extreme variations in exchange rates.