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Regional Private Financing Risk Index Model Based on Private Financing Big Data

With the rapid development of China's economy in recent decades, and the decentralization of the country's economic regulation and legal support, private financing has developed rapidly due to its simple, flexible and unique advantages. Some SMEs can solve it to some extent through private...

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Detalles Bibliográficos
Autores principales: Zhao, Jingfeng, Li, Bo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9037829/
https://www.ncbi.nlm.nih.gov/pubmed/35478772
http://dx.doi.org/10.3389/fpsyg.2022.874412
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author Zhao, Jingfeng
Li, Bo
author_facet Zhao, Jingfeng
Li, Bo
author_sort Zhao, Jingfeng
collection PubMed
description With the rapid development of China's economy in recent decades, and the decentralization of the country's economic regulation and legal support, private financing has developed rapidly due to its simple, flexible and unique advantages. Some SMEs can solve it to some extent through private financing. The company's own financing issues have also helped the local financial market's effectiveness. Based on the “Yantai Private Financing Interest Rate Index,” this paper constructs a private financial risk index model from three perspectives of interest rate risk, scale risk and credit risk, and conducts a case simulation analysis of the private financing risk index. The characteristic indicators of the early warning system are screened from the macro, micro and stability dimensions, and subjective and objective adjustment coefficients are set for each indicator from both subjective and objective perspectives. This article takes the Yantai Index as the representative of China's private financing interest rate index. Based on the term structure of Yantai's private lending rate, this paper studies its response to macroeconomic shocks and analyzes the information value it contains. And use the private financing interest rate index to build a financial risk monitoring model. Through the system transformation model, the article finds that there is a significant asymmetry in the response of private lending to macroeconomic shocks. When private lending rates are higher, inflation has a greater effect on interest rates; when private lending rates are lower, monetary policy has a stronger regulatory effect on private lending rates. In the data processing, the principal component analysis method and the Bayesian vector autoregressive model were established. Through the study of this article, it is concluded that the interest rate decreases with the increase of the term, and the risk comparison is performed for the 1-month period, 3-month period, June period, 1-year period, and more than 1-year. The risks in the previous period are greater, and the risks in the March and June periods are relatively small. This model can be used to calculate the comprehensive evaluation value and its fluctuation in the historical risk market and historical equilibrium market, so as to determine the risk range of the comprehensive evaluation value. Thus, the early warning system is verified to be feasible.
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spelling pubmed-90378292022-04-26 Regional Private Financing Risk Index Model Based on Private Financing Big Data Zhao, Jingfeng Li, Bo Front Psychol Psychology With the rapid development of China's economy in recent decades, and the decentralization of the country's economic regulation and legal support, private financing has developed rapidly due to its simple, flexible and unique advantages. Some SMEs can solve it to some extent through private financing. The company's own financing issues have also helped the local financial market's effectiveness. Based on the “Yantai Private Financing Interest Rate Index,” this paper constructs a private financial risk index model from three perspectives of interest rate risk, scale risk and credit risk, and conducts a case simulation analysis of the private financing risk index. The characteristic indicators of the early warning system are screened from the macro, micro and stability dimensions, and subjective and objective adjustment coefficients are set for each indicator from both subjective and objective perspectives. This article takes the Yantai Index as the representative of China's private financing interest rate index. Based on the term structure of Yantai's private lending rate, this paper studies its response to macroeconomic shocks and analyzes the information value it contains. And use the private financing interest rate index to build a financial risk monitoring model. Through the system transformation model, the article finds that there is a significant asymmetry in the response of private lending to macroeconomic shocks. When private lending rates are higher, inflation has a greater effect on interest rates; when private lending rates are lower, monetary policy has a stronger regulatory effect on private lending rates. In the data processing, the principal component analysis method and the Bayesian vector autoregressive model were established. Through the study of this article, it is concluded that the interest rate decreases with the increase of the term, and the risk comparison is performed for the 1-month period, 3-month period, June period, 1-year period, and more than 1-year. The risks in the previous period are greater, and the risks in the March and June periods are relatively small. This model can be used to calculate the comprehensive evaluation value and its fluctuation in the historical risk market and historical equilibrium market, so as to determine the risk range of the comprehensive evaluation value. Thus, the early warning system is verified to be feasible. Frontiers Media S.A. 2022-04-11 /pmc/articles/PMC9037829/ /pubmed/35478772 http://dx.doi.org/10.3389/fpsyg.2022.874412 Text en Copyright © 2022 Zhao and Li. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Psychology
Zhao, Jingfeng
Li, Bo
Regional Private Financing Risk Index Model Based on Private Financing Big Data
title Regional Private Financing Risk Index Model Based on Private Financing Big Data
title_full Regional Private Financing Risk Index Model Based on Private Financing Big Data
title_fullStr Regional Private Financing Risk Index Model Based on Private Financing Big Data
title_full_unstemmed Regional Private Financing Risk Index Model Based on Private Financing Big Data
title_short Regional Private Financing Risk Index Model Based on Private Financing Big Data
title_sort regional private financing risk index model based on private financing big data
topic Psychology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9037829/
https://www.ncbi.nlm.nih.gov/pubmed/35478772
http://dx.doi.org/10.3389/fpsyg.2022.874412
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