Author(s)

Yidi Sun ¹

Affiliation(s)

¹ School of Statistics and Data Science, Xinjiang University of Finance and Economics, Urumqi, Xinjiang Uygur Autonomous Region, 830012, China

Corresponding Author

Yidi Sun

ABSTRACT

Since 2011, the Chinese government began to pay attention to the prevention of regional financial risk in the financial field. The effective assessment of regional financial risk is an indispensable link in risk prevention, which is of great significance to maintain economic operation. This paper selects 5 first-level indicators and 15 second-level indicators to build a regional financial risk evaluation system. Based on the economic data of Jiangsu from 2015 to 2020, AHP and entropy weight method are used to calculate the corresponding weights of indicators at all levels. The multi - level fuzzy evaluation model is used to evaluate the financial risk in Jiangsu province. The results show that the membership degree of financial risk to the "general security" level is 0. 5050 at most, among which the proportion of macro environment is 0. 3932 at most, and the degree of external environment is 0. 0625 at least. It can be seen that the economic operation of Jiangsu is relatively stable and the financial risk is small.

KEYWORDS

Regional financial risk, Entropy method, AHP, Multi-level fuzzy comprehensive evaluation

CITE THIS PAPER

Yidi Sun, Study on the comprehensive evaluation of regional financial risk . Financial Engineering and Risk Management (2022) Vol. 5: 97-105. DOI: http://dx.doi.org/10.23977/ferm.2022.050613.

REFERENCES

[1] YU S Y. Analysis on the causes of regional financial risks [J]. Journal of Jilin Economic Management Cadre Institute,2008(04):54-56. (in Chinese)
[2] Tan Zhongming, Liu Qian, Li Jie. Will Internet finance accelerate the accumulation of regional financial risks?-- Research on spatial spillover effect [J]. Finance and Economics,2020(04):51-59. 
[3] Ma Ruowei, Ding Xin. Research on the Influence of Internet Finance on Regional Financial Risk: Based on the adjustment effect of industrial structure [J]. Rural Finance Research,2022(03):39-52. 
[4] Chen Lei, Ren Wenda, Huang Bingrou. Research on the impact of fintech on regional financial risk in China [J]. Fujian Forum (Humanities and Social Sciences 8 Edition),2021(10):155-167. 
[5] Li Kaifeng, Li Xing. Identification of Debt Risk Level and Its Influence on Regional Financial Risk: Based on entropy weight TOPSIS method and comprehensive fuzzy evaluation method [J]. Shanghai Finance,2019(03):74-80. 
[6] Zhang Zhipeng, Li Man. Research on regional financial risk assessment in Jiangsu Province [J]. Continental Bridge Perspective,2021(05):39-41. 
[7] Sang Yumeng, Han Xiuping. Construction of logistics financial risk assessment model based on entropy weight method [J]. Business Economic Research,2019(09):165-167. 
[8] Fan L J . Study on the Comprehensive Evaluation of Oil Sunflower Regional Trials[J]. Ningxia Journal of Agriculture and Forestry Science and Technology, 2017. 
[9] Zhang Xin, Zhu Yixin. Regional systemic financial risk measurement and monitoring: A case study of Xinjiang [J]. Regional Finance Research,2022(05):39-43. 

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