The Application Research Of Genetic Programming In Exchange Rate Market Prediction

Forecast is necessarily an important link in scientific management and premise before policy-making and layout. It is necessary to forecast and analyze evolution trend of some system. Data forecast is a process that discovers knowledge from mass data and information. It plays an important role in decision making and actions as guidance. Forecasting exchange rates is an important financial problem that is receiving increasing attention especially because of its difficulty and practical applications.The economists worked hard to research the change of exchange rate market, hope to find some rules. The exchange rate market is a complicated nonlinear system infected by many factors in the same time,the accurate prediction of the exchange rate price is very difficult. Using the rules of nonlinear deterministic system to study the stock price shows more and more vitality. Along with the development of nonlinear theory and artificial intelligence, wavelet analysis and wavelet network become cogent tools for financial market analysis and forecasting.The genetic algorithm is a kind of searching method which simulates the natural evolution. It is simple and easy to implement, especially it do not need the special field knowledge, so it has been using in very broad fields. Now the genetic algorithm has got a lot of fruits and more scholars begin to pay attention to it.The genetic algorithm is still a new technology being in the development. Despite its success in so many domains, its theoretical groundwork is weak. There are still lots of problems to study and develop.Genetic Programming (GP) and Gene Expression Programming (GEP) is a new member in the family of Genetic Algorithm (GA). It is different from traditional GA in expressing and processing of individual and form of result. We apply Gene Expression Programming to carry out modeling. The application shows that the model set up by GEP is superior to the models set up by common neural networks analysis and simple Genetic Programming.Based on the features of exchange rate objects, this paper have researched the method to predicting the exchange rate by GA,GP,GEP algorithm and got satisfying result.The main contrition of this work includes:1. Describing the basic concept and diagram of data prediction;2. Researching and analyzing the features of exchange rate market and exchange rate data3. Analyzing the features of genetic algorithm, based on the theory of artificial neural network and construct the modeling system of economy prediction, then giving experiments for exchange rate base on GA-NN model;4. Analyzing the structure and features of Genetic Programming (GP), then apply the sample of exchange rate;5. Researching Genetic Expression Programming (GEP) and its application in exchange rate market.6 Giving experiments for exchange rate market based on GEP model, analyze the experiment results, compare it with neural networks. The experiments show that the precision of this mode is much higher than traditional method than neural networks.7. Analyzing the features of genetic algorithm especially GP, GEP algorithm, and compare them.This paper is organized as follows: Section 1 introduces the background of this research, Evolutionary Computation,genetic theories and applications of prediction modeling, basic concept and diagram of data prediction and features of exchange rate market; Section 2 introduces the fundamental idea and concepts of Gene algorithm, analyze its feature and application; Section3 introduces the application of GA in neural networks optimization,then apply the exchange rate sample to test the GA-NN forecasting model; Section 4 introduces the fundamental idea, flow of algorithm and other concepts of Genetic Programming (GP), analyze its application in exchange rate market, Section 5 analyze Gene Expression Programming (GEP) model, and provide a GEP model based on exchange rate market, then apply the model and compare it with other models such as artificial neural networks . Section 6 gives the conclusion and future work.Based on predecessors'research fruit in this paper, and throwing them into the practice, and does one's best to supply valid measure for exchange rate market forecasting based on Genetic programming, and making great efforts in the interest of spreading the Evolutionary computation and genetic programming technique. Then we will use the technique in wider range, analyzing other factors and find a better method to predicting.