Research On Forecasting And Value-at-risk Measurement In Foreign Exchange Markets Based On Deep Leaning

With the accelerated development of global integration and the continuous expansion of international trade,the scope of the funds for trade in international financial markets is growing.The development of Internet and high-performance computer technology have also promoted the development of cross-border trade activities,making International trade is becoming more and more frequent,and the forms are becoming more and more diversified.The exchange rate plays an increasingly important role as one of the important links of international economics and cross-border trade activities.After the reform of the RMB exchange rate,the market-oriented characteristics of the exchange rate formation mechanism are increasing,and the exchange rate of the RMB changes more violently.In recent years,Southeast asian financial crisis,subprime crisis,the euro crisis have a serious negative impact on the foreign exchange market,the international exchange rate of major currencies is still complex and unpredictable,the risk of foreign exchange market continues to increase,exchange rate forecast and risk measurement into exchange rate research field One of the important research.At the same time,it is very important to strengthen the accuracy of exchange rate forecast in foreign exchange market and the risk management of exchange rate to multinational enterprises in China.The deep learning model has a good performance in image recognition,speech recognition,classification,data mining and so on,and has high performance in dealing with nonlinear problems.The historical data of the exchange rate also has a very complex linear and non-linear relationship,the current classic models can not be a good description of which the relationship between the intrinsic description and feature extraction,Therefore,it is a new attempt to describe the complex intrinsic function of exchange rate market historical data by applying the depth learning model to the field of financial forecasting.Aiming at the problem of accurate forecasting of exchange rate movements and more accurate estimation of exchange rate risk,this paper proposes a model of exchange rate forecast and risk measurement based on deep learning theory.Firstly,this paper introduces the research status of the deep learning model in image recognition and speech recognition in recent years,and then proposes a new exchange rate forecasting model in foreign exchange market based on the deep learning model.Then,a new risk management model of integrated VaR is proposed based on the theory of risk measurement.This model combines the depth learning model with the ARMA-GARCH model to construct the VaR model.And exchange rate data of seven mainstream foreign exchange markets is used in the empirical study,the model proposed in this study has good accuracy and reliability.