The influence of international oil prices on the exchange rates of oil exporting countries: Based on the hybrid copula function

Abstract

Achieving accurate exchange rate forecasts has a significant impact in construction of international trade and currency markets. However, because of the volatility of exchange rate series, accurate exchange rate prediction is still a difficult issue. In prior studies, researchers tend to conduct prediction research on individual variables of the real exchange rate and ignore the direct influence of other relevant economic factors on the real exchange rate forecasts, which leads to unsatisfactory prediction accuracy. At present, oil price shocks are often used as the dominant factor to explain the actual exchange rate behavior, and the analysis of the relationship between the two has become a hot issue. To explore the direct impact of oil prices on the real effective exchange rate forecast, a bivariate scheme is proposed, proving the important effect of oil price variable on exchange rate forecasting. The framework of this article starts from two aspects. First, several Copula functions are used to study the relationship between the two sequences, and the basic Copula functions including Clayton, Gumbel, and Frank functions are selected, and the three Copula functions are employed to obtain a hybrid Copula function using the improved Dragonfly optimization strategy. Next, a binary forecasting framework is constructed and a data preprocessing method is added to construct a forecasting model. Finally, this article demonstrates that the bivariate scheme achieves better forecasting capabilities than the univariate forecasting frame.