Trend and Volatility Analysis of Shanghai Composite Index Returns Based on ARMA and LSTM Model
This paper takes the daily return rate of the Shanghai Composite Index as a sample to establish the ARMA-LSTM (Long Short-Term Memory) model for the Shanghai Composite Index. It compares the fitting effect of ARMA model on the volatility of the Shanghai Composite Index under different distribution a...
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| Main Author: | |
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| Format: | Article |
| Language: | English |
| Published: |
Tamkang University Press
2025-07-01
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| Series: | Journal of Applied Science and Engineering |
| Subjects: | |
| Online Access: | http://jase.tku.edu.tw/articles/jase-202603-29-03-0010 |
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| Summary: | This paper takes the daily return rate of the Shanghai Composite Index as a sample to establish the ARMA-LSTM (Long Short-Term Memory) model for the Shanghai Composite Index. It compares the fitting effect of ARMA model on the volatility of the Shanghai Composite Index under different distribution assumptions, calculates and tests the coverage of the prediction results of the Value-at-Risk (VaR) value of the Shanghai Composite Index on the actual losses. The analysis results show that the ARMA model is more suitable for measuring the conditional variance of the Shanghai Composite Index. With the t -distribution, the model can better reflect the distribution characteristics of the perturbation term of the Shanghai Composite Index’s return rate. Furthermore,
in order to overcome the large errors that occur in the medium and long-term prediction of the ARMA model, the ARMA model combined with the LSTM model is used to predict the exponential volatility, effectively improving the prediction accuracy of the ARMA-LSTM model. Finally, through the ARMA model, the impact of the full implementation of the registration system in China’s stock market on the volatility of the Shanghai Composite Index is preliminarily examined. It is found that the implementation of this policy significantly
reduces the fluctuation range of the Shanghai Composite Index. |
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| ISSN: | 2708-9967 2708-9975 |