基于LSTM递归神经网络的马来西亚富时证券KLCI市场预测

T. M. Busu, Saadi Ahmad Kamarudin, N. Ahad, Norazlina Mamat
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引用次数: 0

摘要

股市预测在金融界是至关重要的。投资者和对投资感兴趣的人在投资之前会对股票市场的未来价值感兴趣。通过使用时间序列方法,本研究对富时马来西亚证券交易所KLCI (FBM KLCI)股票市场的预测和建模做出了贡献。在本研究中,对股票市场进行预测,以确定未来的股票市场趋势。利用FBM KLCI收盘价格数据构建长短期记忆(LSTM)模型来预测股票市场。利用均方根误差(RMSE)和平均绝对误差(MAE)对模型的性能进行了评价,以选择最佳模型。研究人员使用马来西亚证券交易所的数据预测了五年的股票市场,从2016年10月20日到2021年10月20日,这已经从雅虎财经网站上取消了。通过在谷歌Colab中运行Python代码对数据进行分析。结果表明,采用递归神经网络(RNN)方法建立的LSTM模型准确率较高,对20121-10-05年股市的预测值提高了1.87%。在FBM KLCI股票市场预测中,可用于预测未来收盘股价。该结果有望为更好的利润提供准确的预测。因此,股票市场投资预测可以支持长期的经济增长,换句话说,它可以帮助经济的可持续性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Prediction of FTSE Bursa Malaysia KLCI Stock Market using LSTM Recurrent Neural Network
Stock market prediction is vital in the financial world. Investors and people interested in investing would be interested in the future value of the stock market before they invest in it. By using the method of time series, this research gives a contribution to forecast and modelling the FTSE Bursa Malaysia KLCI (FBM KLCI) stock market. In this research, the stock market is forecasted to identify the stock market trend in the future. The FBM KLCI closing prices data was utilized to build Long Short-Term Memory (LSTM) models to predict the stock market. The performance of the model has been evaluated using the root mean squared error (RMSE) and the mean absolute error (MAE) in order to choose the best model. The researcher used the Bursa Malaysia data to forecast the stock market for five years, from October 20, 2016, to October 20, 2021, which has been scrapped from the Yahoo Finance website. The data is analyzed by running Python coding in Google Colab. The result proves that the accuration of the LSTM model by using Recurrent Neural Network (RNN) approach is accurate and the predicted value of the stock market at the date 2021-10-05 is increased by 1.87%. It can be used to predict the future closing stock prices in stock market prediction in FBM KLCI stock market. The results are expected to provide an accurate prediction for a better profit. Thus, prediction in stock market investment can support long-term economic growth, or in other words, it can help economic sustainability.
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