基于自动回归综合移动平均(ARIMA)模型的马鲁蒂铃木股价预测

K. Khan, Dileep Singh
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引用次数: 1

摘要

股票价格预测是金融领域和经济学中一个非常重要的课题。多年来,投资者一直对建立更好的预测模型感兴趣。自回归综合移动平均(ARIMA)模型以前用于时间序列预测。本文展示了运用ARIMA模型进行股票价格预测的过程。用于分析的历史股票数据从国家证券交易所(NSE)获得,并与股票价格一起使用ARIMA模型进行预测。ARIMA模型的短期预测效果较好,可以用现有的股票价格预测方法进行验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Stock Price Forecasting of Maruti Suzuki using Auto Regressive Integrated Moving Average (ARIMA) Model
Forecasting of stock prices is a very important subject in the financial world and economics. For many years, investors have been interested in making better forecasting models. The autoregressive integrated moving average (ARIMA) model was used previously for time series forecasting. This article shows the process of stock price forecasting using an ARIMA model. Historical stock data for analysis is obtained from the National Stock Exchange (NSE) and is used along with the stock price for forecasting using an ARIMA model. The result obtained from an ARIMA model is better for short-term forecasting and can be proven with existing methods for stock price prediction.
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