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Academic Journal of Business & Management, 2021, 3(10); doi: 10.25236/AJBM.2021.031020.

The Empirical Analysis and Prediction of China's FinTech Index Based on GARCH Model and BP Neural Network Model


Ming Li1, Hefei Wang2, Hua Fang3

Corresponding Author:
Ming Li

1&3Business School, University of Shanghai For Science and Technology, Shanghai, 200093, China

2School of Public Management, Inner Mongolia University, Hohhot, Inner Mongolia, 010021, China


In recent years, the development of FinTech has moved from behind the scenes to the front, greatly promoting the development of innovation and high-quality supply in the financial sector. The development level of China's FinTech is generally leading in the world, and many listed FinTech companies have brought vitality to the financial market. But on the other hand, fintech also contributes to market volatility. Reasonable prediction of its trend and prevention of investment risks are still important issues. In this paper, CNI Xiangmi Lake FinTech Index, which can measure the overall performance of China's FinTech listed companies, is selected as the research object, and GARCH model and BP neural network model are used to conduct empirical analysis and forecast research on the index. The results show that the two time series models can fit the curve and the actual trend well. Compared with the prediction accuracy, the prediction effect of GARCH model is better than BP neural network model.


FinTech; GARCH model; BP neural network model.; Forecast analysis

Cite This Paper

Ming Li, Hefei Wang, Hua Fang. The Empirical Analysis and Prediction of China's FinTech Index Based on GARCH Model and BP Neural Network Model. Academic Journal of Business & Management (2021) Vol. 3, Issue 10: 119-126. https://doi.org/10.25236/AJBM.2021.031020.


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