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Web of Proceedings - Francis Academic Press
Web of Proceedings - Francis Academic Press

Risk prediction model of investment bank based on dynamic neural network

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DOI: 10.25236/icfmhss.2021.002


Zixin Lin

Corresponding Author

Zixin Lin


Investment banks not only have the commonness of general financial intermediaries, but also have their own characteristics as the protagonists of the capital market. The risk of investment bank is a combination of its common risk as a financial intermediary and its own industry-specific risk. In this paper, the investment bank risk prediction model based on dynamic parameter neural network is introduced and applied to the investment bank risk prediction, and compared with the traditional time series prediction model. Empirical research shows that the accuracy of dynamic neural network model in investment bank risk results is better than that of static BP neural network model.


Parametric neural network, Investment bank, Risk profile