Research on the Application of Computer Big Data Artificial Intelligence Technology in Financial Institutions' Digital Sensitivity Analysis Economic Risk Model

Yingkai Ma

doi:10.54097/hbem.v9i.9259

Authors

Yingkai Ma

DOI:

https://doi.org/10.54097/hbem.v9i.9259

Keywords:

VaR; ES; ARMA; Financial Institutions; Sensitivity; Risk Measurement.

Abstract

This paper uses a risk factor model to construct a joint distribution of returns on major risk exposures of financial institutions. This paper also examines the sensitivity of the overall risk of the study to changes in the financial business portfolio and changes in risk correlations. The author mainly introduces VaR, ES and ARMA, the quantitative risk analysis methods widely recognized by the financial industry recently. A measure of the overall risk of a financial institution in terms of returns. At the same time, the sensitivity of different risk measurement tools to changes in financial business portfolio and changes in risk correlation.

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References

Wang Zhuquan, Song Xiaobin, Wang Yuanzhuo. Evaluation and Judgment of Short-term Financial Risks in Chinese Real Economy--Comprehensive Evaluation and Early Warning of Short-term Financial Risks Considering Stock and Flow. Management World, vol. 36, pp. 14-22, October 2020.

Wang Hui, Zhu Jiayun, Chen Xu. Optimal coping strategies for inter-bank market network stability and systemic financial risks: the perspective of government holding. Economic Research, vol. 56, pp. 19-23, November 2021.

Jin Chengxiao, Li Mengjia. An Empirical Study on the Time-varying Mechanism of Monetary Policy Response Function Channels Influencing the Financial Cycle. Journal of Chongqing University: Social Science Edition, vol. 27, pp. 130-135, June 2021.

AA Maikabara, S Maulida, AM Aderemi, Debt-Based Versus Equity-Based Financing: A Comparative Analysis on Efficiency of Islamic Financial System, Ihtifaz Journal of Islamic Economics Finance and Banking, vol. 55, pp. 17-22, April 2020.

E Mbedzi, M Simatele, Small, micro and medium enterprises financing: Costs and benefits of lending technologies in the Eastern Cape province of South Africa, Journal of Economic and Financial Sciences, vol. 41, pp. 24, February 2020.

P Guerra, M Castelli, N Crte-Real, Machine learning for liquidity risk modelling: A supervisory perspective, Economic Analysis and Policy, vol. 24, pp. 140-145, March 2022.

AV Szabo, Credit Risk Modelling of Mortgage Loans in the Supervisory Stress Test of the Magyar Nemzeti Bank, Financial and Economic Review, vol. 40, pp. 17-24, October 2022.

A Atsanan, GC Onuigwe, The Impact of Financial Institutions Intermediation Activities to Economic Growth in Nigeria, Journal of Humanities, vol. 56, pp. 18-20, September 2021.

J Begenau, T Landvoigt, Financial Regulation in a Quantitative Model of the Modern Banking System, Review of Economic Studies, vol. 24, pp. 36-37, October 2022.