Internet Financial Market Risk Measurement Based On GARCH-VaR Model Technology-driven Risk Regulation Research

With the emergence of new technologies such as big data,cloud computing,and artificial intelligence,the foundation of Internet finance development and the allocation efficiency of financial resources have been significantly improved.The Internet financial business model has changed,and the pace of financial product changes and innovation has accelerated.It has spawned many new forms of Internet finance,and technology has become a direct and obvious driving force for financial innovation.While financial technology brings convenience to Internet finance,the financial business model is more virtualized,the financial risk situation is more complex and changeable,and the supervision of Internet financial risks faces enormous challenges.At the government level,the risk prevention of Internet finance has also been paid more and more.On the one hand,new technologies have driven financial innovations to bring new risk scenarios and risk characteristics,and it is necessary for the regulators to clarify the problem of “technology-to-technology”.On the other hand,regulators urgently need to obtain more comprehensive and accurate data.In the face of the massive data submitted by financial institutions,it is necessary to use technology to improve processing efficiency and regulatory effectiveness.This paper starts with the related concepts of Internet financial risk and technology-driven risk supervision,and summarizes the theoretical basis of this paper.Firstly,it makes an in-depth analysis of the current status and supervision of Internet financial risks,and conducts research on Internet finance in a broad scope.The empirical study of risk measurement,the sample data selected based on the daily closing price of 1119 Internet financial indices from 2014 to 2018,using the conditional variance characteristics of the GARCH family model to characterize the changes in the fluctuations of the rate of return,combined with the VaR risk measurement method Accurately calculate the risk value.The empirical analysis shows that the sequence distribution of Internet financial index returns has obvious peak and thick tail characteristics,and its fluctuation shows clustering and conditional heteroscedasticity,and it is verified that it has ARCH effect and leverage effect.According to this,according to the lower the better the Achichi Information Criterion(AIC),the optimally fitted GARCH(1,1)model is established,and the corresponding conditional variance and the quantile under different confidence levels are calculated iteratively,using VaR.The calculation formula obtains the risk value of the internet financial rate of return sequence at different confidence levels.Secondly,it is proposed that the Internet financial risk measurement model can be used as an important part of the big data risk monitoring and early warning system.Accurately measuring the Internet financial market risk can transform the Internet financial data information into intelligent data decision-making activities,thus achieving intelligent monitoring and dynamicization.The early warning process provides an important basis for the technology-driven regulatory system.Then,it further analyzes and summarizes the problems existing in traditional supervision,and concludes that relying on new technologies such as big data,cloud computing,artificial intelligence,and blockchain to construct a “technology-driven supervision” system is an inevitable choice for strengthening Internet financial risk supervision.From the aspects of construction principles,regulatory objectives,regulatory mechanisms,and regulatory application scenarios,the paper analyzes the logical dimensions of the technology-driven regulatory system and finds a way out for strengthening Internet financial risk supervision.Finally,it puts forward some countermeasures and suggestions for implementing science-driven risk supervision in China,starting from deepening the supervision system,innovating supervision methods,perfecting the data collection system,establishing risk monitoring and early warning system,introducing third-party regulatory agencies and accelerating the research and application of technology-driven supervision.