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A Novel Stock Price Forecasting Method Using the Dynamic Neural Network

机译：动态神经网络的股价预测新方法

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With the rapid development of economic and people's investment requirements, stock has been an important part in modern society. In order to forecast the stock market, the most important issue is to analyze the stock market investment. Influence factors of the stock market include four aspects, that is, (1) Domestic economic and policy, (2) International environment, 3) Stock features, and 4) Technical judgement. To forecast stock price, we construct a dynamic neural network (named as NARX) model. NARX neural network means the nonlinear autoregressive with exogenous input, and NARX neural network is able to analyze the structure of nonlinear systems and time series based system. Finally, we choose two stocks to make performance evaluation, which are 1) Poly Real Estate (600048) and 2) Industrial and Commercial Bank of China (601398). Experimental results demonstrate that the proposed algorithm can forecast stock price with high accuracy.
机译：随着经济的快速发展和人们的投资需求，股票已成为现代社会的重要组成部分。为了预测股票市场，最重要的问题是分析股票市场投资。股票市场的影响因素包括四个方面：（1）国内经济和政策;（2）国际环境;（3）股票特征;（4）技术判断。为了预测股票价格，我们构建了一个动态神经网络（称为NARX）模型。 NARX神经网络意味着具有外部输入的非线性自回归，而NARX神经网络能够分析非线性系统和基于时间序列的系统的结构。最后，我们选择两只股票进行绩效评估，分别是1）保利房地产（600048）和2）中国工商银行（601398）。实验结果表明，该算法能够准确预测股票价格。

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