%0 Journal Article
%T Applying genetic programming to analyze moving average and long & mid-term trends of stock prices<br>遗传程序设计分析股价移动平均及中长期走势*
%A ZHAO Er-bo
%A MA Huan
%A HAN Zhan-gang
%A <br>赵尔波
%A 马欢
%A 韩战钢
%J 计算机应用研究
%D 2010
%I 
%X This paper employed genetic programming (GP) to analyze stock price. The task tried to find out how far it could go if used only one element, which was the price, to predict the stock market, based on the understanding that it was impossible to distinguish all the interactions between various elements in the stock market. Our work proposed two multi-scale approaches trying to predict stock prices. One was to use GP to form empirical formulas to predict the moving average lines of stock prices; the other was to use GP to do long & mid-term predictions on pre-processed data. The aim was to find empirical laws for specific enterprises stock prices based on previous stock price data. Simulations show that the method to predict the moving average and long & mid-term trends of stock prices is effective.
%K genetic programming
%K fitness function
%K moving average
%K FFT filtering<br>遗传程序设计
%K 适应性函数值
%K 移动平均线
%K FFT滤波
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=1871161F1948240C204245EF27EB7491&yid=140ECF96957D60B2&vid=DB817633AA4F79B9&iid=B31275AF3241DB2D&sid=EA6B8E599015449E&eid=31EF1FA369BC6521&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=12