利用机器学习技术预测股票市场

J. Guntaka, Velangi Joseph Karunakar Reddy Gade, RamPrakash Yallavula, A.Dinesh Kumar, P. Sagar
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引用次数: 0

摘要

证券交易已成为当今金融界最重要的事件之一。股票市场的现状对全球经济有重大影响。各行各业的人,无论是商业背景的还是学术背景的,都被吸引到股票市场,并取得了巨大的成功。股票市场的非线性特性使其研究成为当今世界最重要和最热门的课题之一。人们根据他们的预测或早期研究的知识选择在股票市场进行投资。在预测方面,人们经常寻找能够降低风险和最大化收益的工具或策略;因此,股票价格预测在竞争激烈的股票市场中占有重要地位。采用基础分析和技术分析等传统方法似乎并不能保证预测的一致性和准确性。因此,机器学习技术已经成为股票市场预测的最新趋势,由于对早期价值的训练,机器学习技术基于当前市场价值进行预测。为了预测当前股票市场的趋势,本文重点研究了机器学习、分析和LSTM(长短期记忆)技术。
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Stock Market Prediction using Machine Learning Technique
The stock exchange has grown to be one of most important events in today's financial world. The current state of the stock market has a significant impact on the global economy. People from many walks of life, whether they come from business or academic backgrounds, have been drawn to the stock market with great success. The stock market's nonlinear character has made research on it among the most important and popular topics worldwide. People choose to make investments in the stock market based on their predictions or knowledge from earlier studies. In terms of forecasting, people frequently seek out instruments or strategies that would reduce their risks and maximize their earnings; as a result, stock price forecasting assumes a significant position in the always competitive stock market industry. Adopting conventional methods like fundamental and technical analysis doesn't seem to guarantee the predictability's consistency and accuracy. As a result, machine learning technologies have emerged as the most recent trend in stock market forecasting, with predictions based on current market values because of training on earlier values. In order to forecast the present trend of the stock market, this article focuses upon Machine Leaning, Analysis and LSTM (Long Short Term Memory) technology.
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