基于时间序列和社会情绪分析的深度神经网络股票趋势预测

Dr. P. Ravichandran, Dr. J. Dafni Rose, K. Vijayakumar
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引用次数: 8

摘要

在本文中,我们提出了一种预测股票价格趋势的方法,通过分析Twitter等社交媒体中出现的相关词汇,并对股票多年来的表现进行时间序列分析。我们获得训练数据,并使用神经网络分别针对股票价格本身的归一化值进行训练,并将这些单独方法的输出作为另一个独立神经网络的训练数据,以一定的精度预测股票未来定价的趋势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Stock Trend Prediction using Deep Neural Networks in Time Series and Social Sentiment Analysis
In this paper, we propose an approach towards predicting the trend of stock price values by analyzing the relevant words occurring in social media like Twitter and by performing a time series analysis of the performance of the stock over the years. We obtain training data and train them separately against normalized values of stock prices themselves using neural networks and obtain the desired results by using the outputs of these separate approaches as the training data for another separate neural network that predicts the trend in the stock’s future pricing along with the values with a certain degree of accuracy.
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