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A Technical Analysis System Based On Neural Networks And Genetic Algorithm

Posted on:2004-12-29Degree:MasterType:Thesis
Country:ChinaCandidate:Y XiaFull Text:PDF
GTID:2156360122467256Subject:Management Science and Engineering
Abstract/Summary:PDF Full Text Request
Technical analysis, as one of the most important parts of financial analysis, gets more and more piers with the development of information technology. In these decades, critics from academics and supports from analysts make technical analysis got not only wide concerns but also rapid progress. Since Chinese stock market opened in 1991, interests and researches on technical analysis grow rapidly and investors pay more and more attention on this area.In this paper, we introduce core researches about market efficiency, technical analysis efficiency and related concepts. After a wide theoretic research and an empirical research on Chinese stock market, we get the conclusion that technical analysis could make extra return in Chinese stock market.Based on this conclusion, we proposed a systematic and automatic model to predict technical indicators using neural networks which was optimized by genetic algorithm. In this model, back propagation algorithm based on forward networks was conducted to learn information of historical data and to train the network weights. In order to override the well-known limitation of back propagation algorithm, such as local grade problem, we suggest genetic algorithm, a global optimization algorithm, to optimize the weights set. The different parts of this model were modularized and combined as a prediction system.We apply this method to Shanghai Index, Shenzhen Index and a random selected stock's moving average index from Jan, 1999 to Apr. 2003 to test the accuracy of prediction. The accuracy is higher than 70% in this research.By comparing the return of moving average, predicted by neural networks, rule to simple moving average rule and buy and hold strategy, our trading system shows good performance. It could beat both the simple technical analysis method and the buy and hold strategy.
Keywords/Search Tags:Technical Analysis, Market Efficiency, Neural Networks, Genetic Algorithm, Empirical Research
PDF Full Text Request
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