| 神经网络方法在股票投资中的应用 |
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| 引用本文： | 毛娜,刘前进.神经网络方法在股票投资中的应用[J].统计与信息论坛,2008,23(1):63-67. |
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| 作者姓名： | 毛娜 刘前进 |
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| 作者单位： | 1. 中国人民大学统计学院,北京,100872
2. 中国人民银行营业管理部,北京,100045 |
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| 摘 要： | 日益膨胀的股票市场信息远超出人们的处理能力，股票价格变得越来越难以预测。神经网络方法可以模拟人工智能处理海量信息。提高对股票市场的预测水平。运用中国1998-2005年股票市场数据，利用梯度下降法拟合了一个BP神经网络模型，在实证过程中重点讨论预测过程中出现的分类标准、过抽样、过度训练等问题。认为正确运用神经网络方法可以提高预测分析效果，神经网络模型可以谨慎地作为一种股票投资分析方法加以运用。
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| 关 键 词： | BP神经网络 分类标准 过抽样 |
| 文章编号： | 1007-3116(2008)01-0063-05 |
| 修稿时间： | 2007年9月14日 |
The Application of Neural Networks in Stocks Investment |
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| MAO Na,LIU Qian-jin.The Application of Neural Networks in Stocks Investment[J].Statistics & Information Tribune,2008,23(1):63-67. |
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| Authors: | MAO Na LIU Qian-jin |
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| Institution: | MAO Na, LIU Qian-jin (1. School of Statistics, Renmln University of China, Beijing 100872, China; 2. Operation and Supervision Department, People＇s Bank of China, Beijing 100045, China) |
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| Abstract: | As the barometer of economics, the stock market is affected by many factors. Further, the growing information makes it impossible to forecast the stock price. This paper investigates the usage of the neural networks in stock investment and builds a BP neural network. In the process of empirical study, the author firstly focuses on the criterion of classification, over- sampling, over- training on building models; then the aothor presents some means to deal with the problems; finally the author comes to a conclusion： as a developing method, correct neural network can help investor beat the stock market. |
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| Keywords: | BP neural network classification criterion over- sampling |
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