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E-Commerce Letters 2024
基于机器学习的股票价格预测研究
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Abstract:
股票价格预测可以提供有关未来市场走势的信息，对投资者而言具有十分重要的影响，将机器学习引入股票价格预测中，有助于投资者制定更明智的投资决策。基于此，本文随机选取了一只股票——中国银行在2018年11月16日~2023年11月15日期间的数据作为样本，通过ARIMA模型、支持向量机(SVM)模型、LSTM模型对其股价走势进行预测，最后得出基于LSTM模型的深度神经网络模型具有较好的预测精度。
Stock price prediction can provide information about the future market trend, which has a very important impact on investors. Introducing machine learning into stock price prediction can help investors make more intelligent investment decisions. Based on this, this paper randomly selects the data of a stock—Bank of China from November 16, 2018 to November 15, 2023 as a sample, and predicts its stock price trend through ARIMA model, support vector machine (SVM) model and LSTM model. Finally, it is concluded that the deep neural network model based on LSTM model has better prediction accuracy.
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