Advances in International Applied Mathematics
Advances in International Applied Mathematics. 2024; 6: (2) ; 10.12208/j.aam.20241006 .
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中央财经大学 北京
*通讯作者： 罗兰一星,单位：中央财经大学 北京；
随着如今金融市场的不断发展，股票价格变动成为人们关注的焦点。股票价格不仅反映了公司的经营状况和市场价值，还受到宏观经济、政策调整、等多种因素的影响。因此，如何对股票价格进行准确地分析和预测，对于指导投资决策、维持金融市场稳定等具有重要意义。本文以1984-2012长时间跨度的纽约证券交易所美股收盘价格数据为基础，从分层和整体两方面构建时间序列模型对股票价格进行预测和分析。在实证分析当中，通过对比不同模型方法，旨在为提高股票价格预测的准确性和可靠性提供新的思路和方法，从而为投资者与金融机构提供更准确的决策支持，促进金融市场的稳定和发展。
With the continuous development of the financial market, stock price fluctuations have become the focus of people's attention today. Stock prices not only reflect a company's operating conditions and market value, but are also influenced by various factors such as macroeconomic and policy adjustments. Therefore, accurate analysis and prediction of stock prices are of great significance for guiding investment decisions and maintaining financial market stability. Based on the close price data of the New York Stock Exchange from 1984 to 2012, this paper constructs a time series model to forecast and analyze stock prices from two aspects: stratification and whole. In the empirical analysis, by comparing different model methods, it aims to provide new ideas and methods for improving the accuracy and reliability of stock price prediction, so as to provide more accurate decision support for investors and financial institutions, and promote the stability and development of financial market.
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