The Exchange Rate Forecast Based On Neural Network And System Design

On July 21, 2005, the People's Bank of China announced the adjustment of the RMB exchange rate system. The contents of the reform of the RMB exchange rate mechanism were that the RMB exchange rate would no longer be pegged solely to the U.S. dollar, but accord to the actual situation of China's foreign economic development, select a number of major currencies, give them corresponding weight, form a basket of currencies It also would be based on market supply-demand relationship thus form a managed floating exchange rate.Under the new RMB exchange rate mechanism, enterprise and commercial bank will all face the risk of exchange fluctuations. The establishment and improvement of their mechanisms to avoid risks should be carried out simultaneously with the reform of the exchange rate. So, whether enterprise or bank will be required to raise their own exchange rate risk management, grasp various exchange tools to avoid risks and strengthen their ability to deal with exchange fluctuations.Exchange fluctuations are the decisive factors to generate foreign exchange risks. Forecast the direction and amplitude of the exchange rate fluctuations is the most important work to determine its risk damage, therefore, commercial bank and enterprise should prevent and manage the risk of the exchange rate. Firstly, we need to accurately predict the direction and amplitude of the exchange rate fluctuations, measure the risk damage, and then establish the corresponding strategy to manage exchange rate risk. So, as the basis and precondition for the exchange rate risk management, the precondition of the exchange rate is one of the important steps to manage the exchange rate risk. The traditional forecast method can be divided into basic analysis method according to the exchange rate model and technical analysis method according historical data of the exchange rate. The first method designed to forecast long-term trends of exchange rate movements, and the second one is better for short-term exchange rate forecast.In recent years, Model-free was used in prediction field. Artificial Neural Network-ANN is used more and more in economy system. Background research in the field of Artificial Neural Network-ANN began in the late 19th century and early 20th century. Its nature is nonlinear dynamic systems. It had strong self-learning, legend capacity, identify functions and belong to the borderline science of artificial intelligence and systems engineering Science. As a large-scale parallel processing nonlinear dynamical system, Neural Network-ANN was widely used in economic analysis, optimization, forecast and a lot of other areas in recent years. It also achieved good effect. The types of Neural Network-ANN are feed forward-type, feed back-type, random-type,and self-organization competition-type mainly. At present, the Back Propagation is the most widely used neural network model. BP-neural network is a One-way transmission of multi-layer network. Whether it is in network theory or network performance is already quite mature. Its obvious advantage is highly nonlinear mapping capabilities and flexible network structure.This paper is in the background of the new RMB exchange rate system, to research two short-term forecasts model which are based on the BP neural network. One forecast model is based on Economic factors, and another is based on the time series-self exchange rate forecasting model.This thesis is mainly divided into five chapters:Chapter 1 is primarily on the study of the exchange rate. Firstly, it introduces the meaning of foreign exchange and exchange rate, then, it briefly introduces some current exchange rate theory, and analysis factors which impact the exchange rate. Finally, it introduces the basic method of exchange rate forecasting and summarizing the current research situation of the RMB exchange forecasting.Chapter 2 introduces the neural network theory, and the modeling basis of the thesis: BP neural network. Firstly, it introduces the concept of neural networks and its research history, analyzes the basic principles of neural networks, and summarizes the study types of the neural network. And then it lists the neural network classification and some typical neural network model. Finally, it makes a detailed introduction to the BP neural network model, such as the basic principles, the detailed mathematical algorithm, the network model design, and its characteristics, advantages and disadvantages.Chapter 3 researches the short-term exchange rate forecasting by BP neural network model which was based on econometric thinking. Firstly, making a brief description of the modeling tools MATLAB7. Then according to the conclusions of the chapter 2, it selects economic variables for exchange rate forecasting. Finally, it models the sample data with BP by matlab7.0, and analysis the BP neural network models.Chapter 4 mainly researches the forecasting of daily RMB exchange rate time series with BP neural network in the period after adjustment of the exchange rate. It begins with a brief summary of the time series prediction based on neural networks research. Then it uses Eviews to analyze the statistic characteristic of the sample data. Finally, it uses BP neural network to model and forecast exchange rates, compares and analysis the network models.Chapter 5 mainly introduces the design of RMB/ dollar exchange rate forecast module. It introduces the project background, and introduces the five sub-modules of the system modules with structure and flow charts. Main work of the thesis:(1) According to the macroeconomic background of China's exchange rate system adjusted in July 2005, the thesis tried two ways to model BP neural network to forecast exchange rates. One is on the basis of economic variables and the other is on the basis of exchange rate time-series data itself.(2) Finally, the conclusion of the study is used in the design of the RMB/ dollar exchange rate forecast module, in expectation that the realization of the entire banking system simulation function expansion.What needs to be pointed out is that in order to make the study of the issue more representative, this thesis selected RMB/ dollar exchange rate to forecast. In the actual systems development, commercial banks could join the demand of its customers and make the functions more perfect.