Research on Financial Risk Control Model Based on Deep Neural Network
Journal: Modern Economics & Management Forum DOI: 10.32629/memf.v5i3.2348
Abstract
Affected by the deterioration of the international environment, risks in China's financial market are constantly accumulating, which puts forward higher requirements for financial risk control. In particular, the liquidity risk control of commercial banks has become the focus of academic attention. To control financial risks, we must first control the liquidity risk of commercial banks. With the help of the deep neural network model, this paper, based on the financial data of Chinese commercial banks in 2020, conducts research on financial risk control problems, aiming to explore effective financial risk control strategies.
Keywords
deep neural network; financial risk control; liquidity risk; commercial bank
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[2]Guo Lilun, Zhou rises. Liquidity of commercial banks: research on risk measurement, influencing factors and countermeasures [J]. The Economist Journal, 2023,10(03):59-83.
[3]Bai J, Krishnamurthy A, Weymuller C H. 2018. Measuring liquidity mismatch in the banking sector[J]. The Journal of Finance, 73(1): 51-93.
[4]Rose PS. Commercial bank management[M]. McGraw-Hill/Irwin,2012.
[5]Paola Bright. Inter-bank lending liquidity and banking crises[J]. Economic Notes by Banca dei Paschidi Siena Spa,2002,31(3):493-521.
[6]Brunnermeier M. Deciphering the Liquidity and Credit Crunch 2007-2008[J]. Journal of Economic Perspectives ,2009,23,77-100.
[7]Yang Zhongyuan, Xu Wen. Research on Asset Portfolio Optimization based on Dual Liquidity Risk Control [J]. Economic Management of East China, 2011,25 (06): 71-73.
[8]Gertler M, Kiyotaki N. 2013. Banking, liquidity and bank runs in an infinite-horizon economy[R]. National Bureau of Economic Research Working Paper, No. 19129.
[9]Chatterjee U. Bank liquidity creation and asset market liquidity[J]. Journal of Financial Stability, 2015(18): 39-153.
[10]Luo Shengze. Research on the relationship between liquidity risk and business performance of Commercial Banks in China — Based on the perspective of literature review [J]. Guangxi Quality Supervision Guide, 2020, (03): 125-126.
[11]Xu Jinghong , Yang Daguang. Financial Risk Control Model Based on Deep Neural Networks[J]. Scientific Programming,2022.
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