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Financial instability analysis using ANN and feature selection technique: Application to stock market price prediction

机译:使用ANN和特征选择技术的财务不稳性分析:股票市场价格预测的应用

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Nowadays, Demand of forecasting stock market price is increasing at a higher rate than the ever before as more people are getting connected to the stock business. Many criteria play more or less strong inductive role over the stock market, the trend and price always keep changing here. So, it is challenging to predict exact price value. But some Data mining and Machine learning techniques can be implemented to do this challenging task to predict stock market price and trend. In this study, Artificial Neural Network (ANN) is used along with windowing operator; which is highly efficient for working with time series data for predicting stock market price and trend. This study is done on Wal-Mart Stores Inc. (WMT) a listed company of New York Stock Exchange. Five years historical dataset (2010-2015) is used to undertake the experiments of this study. According to the result of this study Artificial Neural Network (ANN) can produce a rational result with a small error.
机译:如今,随着越来越多的人与股票企业相连,预测股票市场价格的需求越来越高。许多标准在股票市场上发挥了更多或更少的归纳作用,趋势和价格总是在这里保持不变。因此,预测确切的价格价值是挑战性的。但是,可以实施一些数据挖掘和机器学习技术,以便进行这项挑战性的任务,以预测股票市场价格和趋势。在这项研究中,人工神经网络(ANN)与窗口操作员一起使用;这对于使用时间序列数据进行高效,以预测股票市场价格和趋势。这项研究于沃尔玛商店公司(WMT)纽约证券交易所上市公司。五年历史数据集(2010-2015)用于进行本研究的实验。根据本研究的结果,人工神经网络(ANN)可以产生一个小错误的合理结果。

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