Analysis Of The Impact Of New Coronary Pneumonia On Systemic Financial Risk Based On Financial Stress Index And Combined Model

In recent years,the issue of systemic financial risks has attracted widespread attention from our government and academic circles.General Secretary Xi Jinping has repeatedly and publicly emphasised that "guarding the bottom line of no systemic financial risks is an inevitable requirement for China to build a modernised economic system and achieve high-quality development".In the dual context of the COVID-19 pneumonia and the construction of China’s modernised economic system,it is particularly important to accurately measure systemic financial risks,comprehensively characterise financial stresses and establish an early warning system for major risks,in order to maintain China’s financial stability.Therefore,this paper compiles a China Financial Stress Index for the period 2007 to 2020 for China’s national conditions,aiming to portray the dynamics of China’s financial risks and identify the stages of financial stress in China.A combinatorial model is constructed to analyse the impact of the new crown pneumonia epidemic on financial markets,forecast short-term financial stress conditions and put a global perspective on the systemic financial risk early warning system.Specifically,the main work of this paper is as follows.(1)Construct the China Financial Stress Index from 2007 to 2020 to identify periods of financial stress.A total of 20 indicators covering the banking,real estate,stock market,foreign trade and domestic trade sectors are selected,and the indicator weights are determined using principal component analysis and the sub-market weights are established using the CRITIC method to synthesise the China Financial Stress Index,thereby providing a picture of the dynamics of China’s financial risk.The identified high pressure periods of systemic financial risk are in the years 2007-2009,2015-2016 and early 2020,which are consistent with the financial development of China.(2)A combined model is used to simulate the situation in the absence of the epidemic and to compare it with the reality.In this study,a combined ARIMA and BP neural network model is constructed to simulate the financial stress index in China before the epidemic,and compare it with the actual index to investigate the impact of the new crown epidemic on the financial stress situation in China.At the same time,the combined model is used to predict the short-term financial stress index.The results of the study indicate that the epidemic has spiked the stress in China’s financial system,and that China will continue to be under a period of high systemic financial risk in the short term.(3)To establish an early warning system for systemic financial risk.This study takes 46 national economies as the research object,selects 12 economic indicators from 1995-2018,forms panel data,and uses global principal component analysis to process the data and constructs an early warning system for systemic financial risk based on a logistic model.The experimental results show that the logistic model has a good early warning effect on systemic financial risk and that changes in macroeconomic indicators are strongly associated with the occurrence of systemic financial risk.