基于情绪分析的时间序列股票价格预测

Vrishabh Sharma, R. Khemnar, R. Kumari, B. Mohan
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引用次数: 13

摘要

股票价格预测多年来一直是一个重要的研究领域。准确的预测可以帮助投资者在买卖股票时做出正确的决定。本文旨在预测和衡量股票成本和模式,利用机器学习,内容检查和基本分析的力量,为交易者提供敏锐投机的动手工具,特别是对波动的印度股市。本文提出了一种基于情绪分析和可分解时间序列模型以及多元线性回归的股票价格分析与预测技术。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Time Series with Sentiment Analysis for Stock Price Prediction
Stock price prediction has been a major area of research for many years. Accurate predictions can help investors take correct decisions about the selling/purchase of stocks. This paper aims to predict and gauge stock costs and patterns, utilizing the power of machine learning, content examination and fundamental analysis, to give traders a hands-on tool for keen speculations particularly for the volatile Indian Stock Market. We propose a technique to analyze and predict the stock price with the help of sentiment analysis and decomposable time series model along with multivariate-linear regression.
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