Real Effective Exchange Rate Forecast Based On International Benchmark Oil Price Information

As an important financial indicator,the exchange rate occupies an important position in the national economic system.The process of economic globalization is gradually accelerating,trade exchanges between countries have gradually deepened,and the role of exchange rates has been increasingly reflected.Exchange rate changes have a direct regulating effect on a country's import and export trade.In the field of exchange rate research,exchange rate prediction is an important part.Achieving accurate exchange rate forecasts has a significant impact on the construction of international trade and currency markets.However,due to the volatility of the exchange rate series,achieving accurate exchange rate predictions is still a challenging issue.In previous studies,researchers tend to conduct prediction research on individual variables of the real exchange rate and ignore the impact of other relevant economic factors on the real exchange rate,which leads to unsatisfactory prediction accuracy.And in the analysis of other related economic indicators and exchange rates,researchers have ignored the direct influence of other economic variables on exchange rate forecasts.Based on the above analysis,this article explores the impact of other economic variables on the exchange rate from two perspectives.At present,oil price shock is often cited as the main factor in explaining the behavior of real exchange rates in the literature.The fluctuation of international crude oil prices has a significant impact on the economies of various countries.Oil occupies an essential position in the energy system and is even called"industrial blood".Since the Second World War,the impact of fluctuations in international oil prices in the international economy has become more and more significant.Large fluctuations in oil prices have had a huge impact on the stable development of the global economy.For net oil importers and net exporters,changes in global oil prices will directly affect their economic progress and stability.China is a typical oil-importing country.Since the reform and opening up,China's industrialization has been accelerating.Energy demand and the external dependence of oil are increasing.The impact of changes in international oil prices on China's economic development is increasing.Russia is among the world's largest oil producers,second only to Saudi Arabia and the second largest oil producer in the world.Changes in international oil prices have greatly affected Russia's oil exports and its economic development.Therefore,in order to explore the direct impact of oil prices on the real effective exchange rate forecast,this paper selects two typical countries(China as an oil importing country and Russia as an oil-exporting country)to study the impact of international oil price shocks on the real effective exchange rate.The three major international benchmark crude oil prices(Brent crude oil price,Dubai crude oil price,WTI crude oil price)and the real exchange rate of RMB and Ruble are used for analysis.Founded on the theory of exchange rate determination,we used qualitative and quantitative research technologies,taking the real effective exchange rate of RMB and Ruble as examples.And this paper studies the influence of the changes of three international benchmark crude oil prices on the forecast of the real effective exchange rate of oil importing and oil exporting countries.The correlation between the three international benchmark oil prices and the real exchange rate is discussed by the hybrid copula function.In the analysis we use several typical neural networks to construct the oil price-exchange rate bivariate exchange rate model.The empirical results show that the bivariate prediction model has more advantages than the univariate model in terms of prediction accuracy,generalization ability,and prediction ability.DM test and prediction validity test also further confirm the performance of the bivariate exchange rate prediction model.The results of experiments and discussions show that the bivariate exchange rate prediction model has excellent prediction performance and shows that the continuous fluctuation of oil prices has a significant impact on the exchange rate and oil price information provides effective help for the actual exchange rate prediction.This article analyzes the interaction between oil prices and the real effective exchange rate from the following two main aspects:(1)Based on the hybrid copula function,the correlation between the two variables of oil price and real effective exchange rate is discussed.(2)By adding the dimension of the oil price to the univariate exchange rate prediction model,a bivariate exchange rate prediction model is established,and the effect of oil price on the actual exchange rate prediction is verified by an example.Compared with other research methods,the main contributions and innovations of this research are as follows:(1)Using the data preprocessing strategy,based on the signal decomposition and integration strategy,reduce the high frequency noise in the original signal.The original data sequence is decomposed and reconstructed to reduce high frequency noise signals,which can decrease the impact of randomness and effectively improve prediction accuracy.(2)The Copula function is utilized to discuss the correlation between the two variables,oil price and real exchange rate.A hybrid Copula function model is established.Three different Copula functions of Gumbel,Clayton,and Frank are combined using optimization algorithms to build a hybrid Copula function model.(3)In the exchange rate prediction,a dimension of oil price information is in addition to construct a bivariate prediction model.The oil price variable is utilized to assist the prediction of the actual exchange rate,which can better reflect the change law of the exchange rate and produce a good prediction result.It is proved by example that the oil price information has a positive impact on the prediction of the actual exchange rate.(4)In this study,a scientific and effective evaluation system is established to evaluate the prediction performance of the prediction model.A number of comparative experiments were performed,with 6 predictive indicators and two predictive performance test indicators to ensure that the predictive performance of the model was effectively evaluated.