Font Size: a A A

Research On Internet Financial Risk Measurement And Identification Based On The Mixed Frequency Data

Posted on:2024-08-11Degree:MasterType:Thesis
Country:ChinaCandidate:Z Y RenFull Text:PDF
GTID:2569307100493204Subject:Finance
Abstract/Summary:PDF Full Text Request
At present,China is actively exploring the effective path of financial digital transformation and fintech innovation.The emergence of Internet finance just meets the needs of the development of The Times.Along with technological innovation and development,Internet finance emerges at the historic moment.Internet finance is an emerging financial form that integrates key technologies such as the Internet,cloud computing,blockchain,big data and artificial intelligence.It has a decentralization trend and can improve financial efficiency.However,the inherent characteristics of Internet finance such as concealment,complexity,permeability and so on,plus the huge stock risks accumulated by blind expansion of Internet finance,brings new challenges to our current Internet finance supervision.Therefore,to further improve the quality and effectiveness of Internet finance risk regulation is an important measure to standardize the current development of Internet finance.In order to quantify the level of Internet finance risks and build a long-term regulatory mechanism,this paper compares the common and dissimilar risk characteristics of Internet finance and traditional finance and explores the origin of Internet finance risks on the basis of systematically combing the theories related to Internet finance risks.According to the current situation of China’s Internet finance development,the difficulties and blockage points of current Internet finance risk regulation are analyzed.On this basis,this paper selects nine risk indicators from the macroeconomic base,traditional financial industry,Internet industry,and Internet financial industry,constructs a mixed-frequency data set,measures the level of Internet financial risk,identifies the Internet financial risk drivers,portrays the transformation of the intrinsic generation mechanism of Internet financial risk in China,and predicts the future development trend of Internet financial risk,and the research conclusions show that,firstly,China Firstly,the overall risk level of Internet finance has shown an obvious downward trend,with systemic risks mainly appearing in the second half of 2014-2016,2018 and 2020,and the "financial" nature of Internet finance has gradually emerged,with risk-causing factors gradually converging with traditional finance and macroeconomics Second,the Internet financial risk perception index can better test the validity of the Internet financial risk index,and the Internet financial risk will be perceived by Internet financial users to the greatest extent about2 months after its emergence;Third,the contribution of risk indicators to China’s Internet financial risk is,in descending order,credit risk of financial institutions,Internet financial platform business risk,Internet financial market risk,Internet industry development,Internet industry development,Internet industry development,Internet industry development,Internet industry development,and Internet financial industry development.Internet industry development,Internet finance industry development,and macroeconomic growth;fourth,there are obvious high and low state transition characteristics of China’s Internet finance risk,and Internet finance is more likely to be in a low-risk state.Based on the above conclusions,this paper puts forward regulatory suggestions in four aspects,such as coordinating regulatory focus,strengthening the construction of Internet financial infrastructure,enhancing the financial literacy of Internet financial investors,and strengthening the complementary effect of Internet finance on traditional finance,in an attempt to build a normalized long-term regulatory mechanism for Internet finance,prevent and resolve Internet financial risks,and protect the financial market Stability.
Keywords/Search Tags:Internet financial risk, Mixed frequency data, dynamic factor model, Internet financial risk perception
PDF Full Text Request
Related items