苹果股票分析 - 基于 R

Junjie Yu, Wenjia Sang, Yiqian Tang
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摘要

随着中国经济的不断发展,股票市场日趋成熟,股票在经济生活中起着至关重要的作用。股票的发展变化可以衡量企业的经济发展状况。同时,股票投资也成为人们获取经济利益的一种手段。股票的发展与经济发展息息相关。股票价格的波动可以反映国家经济政策的执行情况,也可以综合反映居民的生活状况。随着股票市场的不断完善,准确分析股票价格的走势已成为一个重要的研究课题。准确分析股票价格的变化,对于宏观经济政策的调控和投资者的最优选择具有重要意义。股票价格的波动是一个复杂的非线性动态过程,传统的线性模型无法准确描述和分析其发展变化。时间序列模型可以有效拟合曲线数据,因此在分析和描述股价变化方面具有重要意义。在本研究中,我们收集了苹果公司 2021 年 1 月 1 日至 2021 年 6 月 29 日所有交易日的股票数据,并利用时间序列模型分析了股票价格的变化。在本文中,我们首先对苹果公司股票价格的变化进行了简单的描述性统计分析,发现苹果公司股票价格的波动并不围绕一个特定的值。其次,通过对股票价格的观察和预处理,发现序列是非平稳的。本文采用一阶差分法实现静态化,并利用 ARIMA 模型对数据进行拟合。对于 ARIMA 模型的不同参数,根据 AIC 准则和修正 AIC 系数确定了最优模型。此外,还对股票价格的异常值进行了处理,从而有效预测了苹果公司股票价格的未来走势。通过研究分析,本文得出的结论是:苹果公司的股票价格不仅受随机因素的影响,还受到滞后 5 期股票价格的显著影响。总体而言,苹果公司股票价格变化趋势相对稳定。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysis of Apple Stock - Based on R
With the continuous development of China's economy, the stock market is becoming increasingly mature, and stocks play a crucial role in the economic life. The development and changes in stocks can measure the economic development of enterprises. Meanwhile, stock investment has become a means for people to obtain economic benefits. The development of stocks is closely related to economic development. The fluctuation of stock prices can reflect the implementation of national economic policies and also comprehensively reflect the living conditions of residents. With the continuous improvement of the stock market, accurately analyzing the trend of stock prices has become an important research topic. Accurate analysis of stock price changes is of great significance for the regulation of macroeconomic policies and making optimal choices for investors. The fluctuation of stock prices is a complex nonlinear dynamic process, and traditional linear models cannot accurately describe and analyze its development and changes. Time series models can effectively fit curve data, so they are of great importance in the analysis and description of stock price changes. In this study, we collected all trading days' stock data of Apple Inc. from January 1, 2021, to June 29, 2021, and used a time series model to analyze the changes in stock prices. In this paper, we first conducted a simple descriptive statistical analysis of the changes in Apple's stock prices and found that the price fluctuations of Apple's stock did not revolve around a specific value. Secondly, through the observation and preprocessing of stock prices, it was found that the sequence was non-stationary. This paper used the first-order difference method to achieve stationarity and fitted the data using the ARIMA model. For different parameters of the ARIMA model, the optimal model was determined based on the AIC criterion and the modified AIC coefficient. Furthermore, the abnormal values of the stock prices were processed, enabling effective prediction of the future trend of Apple's stock prices. Through research analysis, the conclusion drawn in this paper is that the price of Apple's stock is not only influenced by random factors but also significantly affected by the lagged 5-period stock prices. Overall, the trend of Apple's stock price changes is relatively stable.
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