JOURNAL ARTICLE

An Empirical Study on Stock Price Forecasting Based on ARIMA Model

Han Peng

Year: 2022 Journal:   The Frontiers of Society Science and Technology Vol: 4 (6)

Abstract

The time series data in the financial market contains historical information, which can reveal the operation law of the system. This paper analyzes and predicts the stock price of China Merchants Bank based on the ARIMA model, selects 243 sample data of the daily stock closing price of China Merchants Bank from July 1, 2021 to July 1, 2022 as the research object, establishes the ARIMA model with Eviews, and uses Python for drawing. Finally, the closing price of the next 3 working days is predicted based on the model. The empirical results show that the ARIMA model has a good effect on the short-term prediction of stock prices, but in the long-term prediction, it can be considered to combine with other forecasting methods, and pay more attention to the stock market information and national macro policies, so as to improve the accuracy of the model prediction.

Keywords:
Autoregressive integrated moving average Econometrics Stock (firearms) Stock price Stock market Economics Closing (real estate) Time series Macro Python (programming language) Empirical research China Computer science Financial economics Finance Statistics Series (stratigraphy) Engineering Mathematics

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2
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0.40
FWCI (Field Weighted Citation Impact)
2
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0.62
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Is in top 1%
Is in top 10%

Citation History

Topics

Stock Market Forecasting Methods
Social Sciences →  Decision Sciences →  Management Science and Operations Research

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