Time Series Prediction In Stock-Price Index And Stock-Price Based On Gene Expression Programming

Data mining is a process that discovers knowledge from mass data and information. It plays an important role in decision making and actions as guidance. 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. The economists worked hard to research the change of the stock-market,hope to find some rules to avoid the big waving of stock-market such as stock-disaster and keep the stability of the stock-market.The stock-market is a complicated unlinear system infected by many factors in the same time,the accurate prediction of the stock-price is very difficult,the prediction of the stock-market is regarded as one of the most chanlleging applications in the time-series predicting,,it attracts far attention in the Data-Mining area. Based on the features of stock objects, this paper have researched the method to predicting the stock-index and the stock-price by GEP algorithm and got satisfying result. The main contrition of this work includes: 1. Foamally describing the basic concept and diagram of Data-Mining; 2. Analysing the features of genetic algorithm especially the GEP algorithm; 3. Researching and analyzing the features of stock-market and stock-data; 4. Building the the stock analyse model named GEP-stock based on GEP , and giving its algorithms; 5. Giving experiments for stock-index and stock-price based on the GEP-Stock model,.anylysing the experiment results,compare it with neural networks. The experiments show that the precision of new model is much higher than trandisiona method in neral networks. The thises is organized as follows: Chapter 1 intoduces the basic concepts of Data-Mining.Chapter 2 analyses the features of stock-data.Chapter 3 analyses the features of Genetic-algorithm.Chapter 4 introduces the GEP algorithm.Chapter 5 presents the GEP-STOCK model including the STOCK-GENE and the STOCK-fitness that appropriated to the special rules of stocks. Chapter 6 verifies the effectiveness of STOCK-GEP algorithm by experiments and analyses on the real stock-price index and stock-price.Chapter 7 gives conclusion and discusses prospects for the future works.