Advances in Economics, Management and Political Sciences
- The Open Access Proceedings Series for Conferences
Proceedings of the 2nd International Conference on Financial Technology and Business Analysis
Series Vol. 46 , 01 December 2023
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Access | Article
Research on the Performance of the ARIMA Model in the Stock Market
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Abstract
With the rapid development and upgrading transformation of Chinese financial industry and increasing investment quality, the investment enthusiasm of the masses has been improved. The prediction of stock price has an effective reference for investors to determine investment strategies. In this paper, ARIMA model is used to compare the model performance of Shanghai Composite Index, Shenzhen Composite Index and Science and Technology Innovation Board. This model is also fitted to the normal period and the shock period of the stock market respectively. The study found that the Shanghai Composite Index is the most mature market, and the fitting performance of the stock market in the normal period is better than that in the shock period. From the middle of 2015 to the beginning of 2016, the Shanghai Composite Index and Shenzhen Composite Index fluctuated significantly. This study not only helps investors to adopt more reasonable investment strategies, but also has important reference value for market regulators to guide the market effectively, avoid violent fluctuations in the stock market and maintain market stability.
Keywords
time series analysis, financial forecasting, model performs evaluation
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Data Availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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- Volume Title
- Proceedings of the 2nd International Conference on Financial Technology and Business Analysis
- ISBN (Print)
- 978-1-83558-139-1
- ISBN (Online)
- 978-1-83558-140-7
- Published Date
- 01 December 2023
- Series
- Advances in Economics, Management and Political Sciences
- ISSN (Print)
- 2754-1169
- ISSN (Online)
- 2754-1177
- DOI
- 10.54254/2754-1169/46/20230322
- Copyright
- 01 December 2023
- Open Access
- This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited