Preventing and resolving systemic financial risks is an important issue for economic and financial systems，Especially today's high -speed development of information technology，A reasonable and effective measurement of systemic risks has become the basic prerequisite for preventing and resolving systemic risks。Due to small data coverage、Low -update frequency and other defects，Traditional methods are monitoring scope、Monitoring frequency、Monitoring Time、Trustness and other aspects there are still limitations。With big data、In -depth integration of artificial intelligence with various industries，Financial Technology is high due to its monitoring frequency、wide coverage、Data sources are wide、True and credible、Model predictability and many characteristics，The advantages of the field of systemic risk prevention and resolution are increasingly prominent。

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Measurement of systemic financial risks，Focusing on the correlation between financial institutions，Drawing the risk of infection caused by financial institutions during negative impact。Different from data and methods，Traditional measurement models of systemic financial risks are roughly divided into two categories: First, use the model of financial market data，If the rear dependencies of the tail、The overflow index model; the second is to use Bet365 app download the network model of the financial institution's balance sheet。

First，The model of the financial market data focuses on the overall income of the financial market in different pressure environments and the correlation between institutional income。Where，Tail dependency model mainly uses the importance of institutions to the system、The influence of the system on individual institutions，and the financial system in the state of pressure, the shortage of capital shortage of individual financial institutions gives systemic risk levels。The overflow index model Consider the overall dependencies of the system，Mainly returns through constructing a vector，Use the prediction error square to decompose results，Constructing each financial market、The overflow index between financial institutions，Then calculate indicators such as system fragility and system importance。

2，The network model mainly uses the level of the financial institution's balance sheet to give system risk level。The network model is divided into direct、indirect correlation network。Where，Direct related network reflects the relationship between interbank debt and debt，The source of the data is the total bank asset of the bank、Total debt。The indirect association model reflects the correlation caused by the assets held by banks，Follow the asset liquidity risk。Current，Preventing and resolving systemic risks is the basis for maintaining the stability of the country's economy and financial，Therefore, it is necessary to accurately monitor systemic financial risks，Then take appropriate measures to prevent。Systemic financial risks that depend bet365 best casino games on financial market data and financial institutions' balance sheet data measuring in the financial market are facing multiple challenges，It is becoming more and more difficult to match the complex reality of systemic financial risk prevention and resolution。

First，Data source limited。Data directly related to the network from the bank's balance sheet，Data from the indirect network comes from various asset data on the bank asset side，These data have problems with low update frequency。Listed Bank announces the balance sheet of balance every quarter，Data such as non -listed banks' balance sheets and other data announcement frequency is lower，and it is more difficult to get。Some small financial institutions，Especially the asset -liability information of illegal financial institutions with greater risks，Can't get it，Further restricting the scope of method application。Asset -liability data is not timely，Leadage to regulatory regulation。

Next，Data types are single。Whether it is the tail dependency model or the network model，Using an asset -liability or a kind of data in the financial market。But，Different data data has different advantages。Financial market data frequency is high; asset -liability data can portray bank financial information; text reviews are closely related to investors' mood，You can predict future risk changes through investors' emotions。Only comprehensive use of data from different sources，Only to get a comprehensive and effective systemic financial risk indicator。

again，Data credibility Questions。Asset -liability data disclosed by financial Bet365 app download institutions may not match the facts，Especially small and medium -sized financial institutions，Forge the financial statements for obtaining unfair interests，The authenticity of the result of the result of systemic financial risks。

Last，The influence of investor emotions cannot be captured。Metering method based bet365 best casino games on financial market data，If the rear dependencies of the tail，Good feasibility、Advantages of high market data frequency。But，The financial market at this stage is not a complete effective market，A lot of noise，Investors' behavioral psychological factors will change future expectations，Affects stock price。The speculators in the financial market use the psychology of investors to chase and kill，Zoom in short -term stock trends，Make the stock price away from the fundamentals。Risk indicators measured by the financial market，May be affected by speculators。When investor emotionally fluctuates，When irrational transactions occur，Risk indicators will lose validity。

More importantly，The financial market measurement method can only measure the risk when the stock price falls，Often can only achieve cyclical synchronous monitoring。When the market is good，The stock price of all institutions is almost rising，The measurement method based on market data believes that all financial institutions risks are low，But the economic prosperity period is a period of rapid risk rising。When the stock price falls，Measurement risk based on market data will rise，But at this time is the stage of concentrated risk，The risk indicators of monitoring have obvious lag。

　　Financial Technology indicates a new direction for systemic risk measures 

Fintech is also known as Fintech，Flows on technological progress, especially financial innovation driven by information technology progress，Investment and financing、Operation、Risk Management、Payment and liquidation and other fields play an important role。Fintech has become increasingly becoming a research hotspot in the field of systemic financial risk supervision。Big data in fintech means、text mining、Emotional Analysis Technology，Quantitative market sentiment，expanded the information dimension of traditional supervision，Improving the monitoring frequency，This can effectively prevent and resolve systemic financial risks。

First，Use emotional analysis technology，Get text emotions，Vane before the implementation of systemic risk。Risk infection is usually related to negative market emotions。Panic market emotions will lead to institutions、Investors sell financial assets，Selling of financial assets will cause the spread of panic，to form a vicious cycle。Research Discovery，Before the financial crisis，Investors' emotions are relatively positive，Investors' views are consistent; after the financial crisis occurs,，Investor emotions turn into pessimism。Live in excitement、The point of view of low anxiety consensus may become an important early warning signal for the financial system crisis。

2，Digging through text，Data source，It is mainly reflected in the expansion of the acquisition processing of text data。An attempt is the process of building text to the network，Use the bank's co -instead Bet365 app download of the traditional asset liabilities in the text。The risk indicators of the structure have a high update frequency、wide coverage、Data sources extensive advantages。Another attempt is every other time，Calculate the emotional index of each bank，Forming time sequence。Emotional index sequence into the overflow index model，Get the overflow matrix of the bank，Evaluation system importance and vulnerability。Not only that，You can also make full use of big data、Diverse and true features，Precisely predict systemic financial risks from multiple sources and perspectives，Monitor the monitoring of systemic financial risks more realistic and credible。

third，Based on machine learning technology，Can achieve the fusion of different types of data。Deep learning model fusion ordinary values、Class values ​​and even text content。Using one-HOT encoding，Convert the class value to 0-1 variables; use Word2vec word vector technology，Quantization of text。Deep learning powerful information processing ability，Help to draw useful features from complicated data。Related researchers have also used the Bayesian model，Fusion Tweet data and market data，Based on the daily change of the bank's "emotion"，Build a network model to evaluate the risk of the system，Used to evaluate the mutual dependence between financial institutions，Describes the spread of the risk of breach of contract between banks。

　　(This article is the National Natural Science Foundation of China "The Study on the Study on Systemic Risk Prevention and Resolution of the Bank of China in the Perspective of the Financial Period" (71973162) phase results) 

　　(Author Unit: National Development and Strategy Research Institute of Renmin University of China; Risk Management Department of CITIC Construction Investment Co., Ltd.