ARIMA 方法在中国股票进程预测中的有效性研究

Kailin Liang, Hongru Wu, Yinuo Zhao
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引用次数: 0

摘要

股票市场波动较大,股票价格经常受到各种因素的影响,这就增加了股票预测的复杂性。根据文献综述,ARIMA(自回归平均积分移动平均)模型是金融预测中最常用的方法之一,其有效性已在许多国家得到验证,这也导致需要对中国 A 股市场的模型进行准确检验。由于 ARIMA 模型适用于短期预测,本文利用该模型对三只具有代表性的 A 股股票进行了 24 天的价格预测。最后,主要证实了 ARIMA 模型短期预测的高效性和长期预测的低准确性,值得进一步研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Study of effectiveness of the ARIMA method in forecasting stock process in China
The stock market is volatile, and the prices of stocks are often influenced by various factors that enhance the complexity of stock prediction. According to the literature review, The ARIMA (autoregression average integrated moving average) model is one of the most-used methods for financial prediction, the effectiveness of which has been tested in many countries, which also leads to a need for accurate examination of the model for Chinas A-share market. In the paper, Due to its suitability for short-term forecasting, the ARIMA model is utilized to forecast the prices of three representative A-share stocks over 24 days. Finally, the efficiency of the short-term prediction and the low accuracy of the long-term prediction of the ARIMA model are primarily confirmed, which is worthy of further study.
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