Research on enterprise information utility indifference curve of big data time

Yang, Changhui

doi:10.3233/jcm-150521

Cited by 2 publications

(1 citation statement)

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“…In this case, interest rates on private lending have increased significantly. The private loan market plays an indelible role in alleviating the shortage of credit funds (Yang, 2015 ). On the other hand, despite the continuous growth of Chinese residents' income and per capita disposable income, Party C still has limited formal investment models, mainly through real estate, savings deposits, government bonds, stocks, bonds, funds, futures, options and other financial Derivatives (Liang, 2016 ).…”

Section: Introductionmentioning

confidence: 99%

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

Zhao

2022

Front. Psychol.

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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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Section: Introductionmentioning

confidence: 99%