个股走势

个股走势模式分类的RBF神经网络方法

RBF neural network method for pattern classification of share tendency

并根据市场公开数据，利用统计分析软件SPSS来验证主力资金进出对沪深股指、板块指数以及个股走势的主导作用。同时对资金流向分析法在实践运用中的适用性问题进行了总结。

At the same time using the statistical software SPSS to validate the effect of Shanghai and Shenzhen stock index , sector index and individual stock movements from the main fund .

探讨了径向基函数神经网络在个股走势模式分类中的应用问题。

In this paper , we discuss the application of radial basis function neural network to pattern classification of stock changing tendency .

虽然高盛承认，回购并不总是个股走势强于大盘的可靠指标，2009年3月以来有新回购计划的股票在宣布回购前后，股价走势确实强于标准普尔指数。

While Goldman admits that buybacks are not always a reliable indicator of stock outperformance , since March 2009 , stocks with new repurchase agreements have outperformed the S & P around the announcement of the buybacks .

透过盘中的股指及个股走势，研判出多空双方力量的强弱，决定了其对股票的炒作节奏的把握，也是其是否盈利或盈利高低的要害。

Through dish medium point to reach go situation , grind those who sentence many empty bilateral force is strong weak , decided its are right the acclaims rhythm assurance of the stock , also be its whether the key of gain or gain discretion .

本文，采用标准支持向量机，对上证180指数和上证综合指数，以及一些个股的走势和价格进行了预测，效果基本令人满意。

This paper applies the standard Support Vector Machine to two SSE indices and some stock to make prediction ;

不要习惯只看个股或大盘的走势图，要打开大盘或个股30分钟线的各项技术指标走势。

Get rid of your habit of watching only the trend graphics of the stocks and the whole market , what you'better keep watching is technical indicators of30-minute line of the stocks or the market .

提出一个基宽度可调的RBF神经网络学习算法，并将它应用于个股走势模式的分类问题。

This paper presents a learning algorithm for a RBF neural network with adjustable radial basis width and discusses its application in the classification problem of share tendency patterns .