Research On Cross-correlation Of Financial Market Fluctuations Under Extreme Risk Event

At the Central Economic Work Conference,Chinese President Xi Jinping stressed that preventing and resolving major financial risks is a strategic and fundamental event related to the development of Chinese economy.Preventing and mitigating the impact of extreme external events in the financial markets is also one of the core research projects in the financial research.The volatility of the financial market is one of the most important aspects reflecting the financial risks,thus the exploration of the volatility characteristics and the driving factors of the financial market is helpful to understand the risk transmission mechanism of the financial market,also helps the prevention and control of the spread of risk.With the development of Econophysics,Multifractal Theory is widely used to analyze the fractal characteristics of time series in the financial market,and provides a rich theoretical and empirical basis for understanding the fluctuation patterns and influencing factors of financial markets by exploring the crosscorrelation between different financial entities or with other external factors.In recent years,the global financial system,including China,has been hit by extreme risk events such as the U.S.-China trade conflict,the coronavirus epidemic,and the Russia-Ukraine conflict.However,under the impact of such extreme risk events,issues such as the changes in the volatility pattern of financial products such as futures and stocks,trends in risk spillovers,investor sentiment and the role of financial policy in this dynamic still need further study.Based on the Multifractal Theory,this paper focuses on the two extreme risk events i.e.the global coronavirus epidemic and the U.S.-China trade conflict,we study the evolution pattern and influencing factors of the volatility of two types of financial products namely the futures prices and the individual stock trading volume.Firstly,the dynamic evolution of the cross-correlation network and the volatility spillover network of commodity futures market prices under the background of the global coronavirus epidemic is studied.Taking the daily price data of the main continuous contracts of the main varieties of the U.S.commodity futures market in the past 9 years as the research object,the detrended cross-correlation analysis based on the Multifractal Theory is applied to construct the cross-correlation network between different commodity futures,and the derivative model DY model based on vector autoregressive model is applied to construct the spillover network between different commodity futures.The two networks show a certain degree of similarity,and the measurement of centrality based on the cross-correlation network can identify the main risk transmitters and receivers in the spillover network.Compared with the period when it was not affected by the global coronavirus,the cross-correlation network showed obvious structural changes during the epidemic.The impact of the pandemic has increased the cross-correlations and shortened the diameter of the network in commodity futures market.Moreover,the intensify of cross-correlation is more obvious between different types of commodity futures,and the spread of risk between different types of commodity futures is more likely to occur during the epidemic.The above analysis provides practical insights for understanding the dynamic transmission mechanism of risk in the commodity futures market,and provides new ideas for further controlling the spread of financial risks.Secondly,this paper studies the cross-correlation between individual stock trading volume,policies and investor sentiments in the stock market under the background of U.S.-China trade conflict.The daily trading volume data of representative U.S.listed companies in the most affected industries during the period was used as the research object.Based on the Multifractal Theory,the multifractal characteristics of the selected time series are explored by applying detrended fluctuation analysis.Furthermore,the multifractal detrended cross-correlation analysis is applied to explore the cross-correlation among policy,investor sentiment and individual stock trading volume,and the results show that there are strong cross-correlations between any pair of time series of the selected stocks.It means that policy and investor sentiment have an impact on the trading volume of individual stocks,and the investor sentiment is also affected by policy.Based on the conjecture that social media platforms have a spreading effect on government policies,the mediation analysis is applied to explore the mediating role of investor sentiment in the cross-correlation between policy and stock trading volume.The results show that at most 36% of the cross-correlation between policy and individual stock trading volume is mediated by investor sentiment.The analysis identify and measure the transmission pathways of cross-correlations between policy and individual stock trading volume,providing a new understanding of the driving factors of financial market volatility.In general,based on the multifractal characteristics of financial markets,this paper explores the cross-correlation of price fluctuations between financial products under extreme risk events and the cross-correlation between external factors(policies,investor sentiments)and trading volume fluctuations of financial products by selecting different extreme risk events and different financial markets.Results show that under the impact of extreme risk events,volatility spillovers in financial markets tends to intensify,cross-correlations between individuals become closer,and individuals are more susceptible to affect by policy and public opinion.From the perspective of theoretical research,this paper enriches the understanding of the impact of extreme risk events on financial market volatility,and provides new ideas for understanding the spread mechanism of risk in the financial market when extreme risk events occur.In terms of practical application,given that the impact of extreme risk events is mostly global,studying the factors affecting the volatility of the U.S.financial market under extreme risk events is conducive to providing new ideas for studying the volatility of Chinese financial market,especially helping better formulate corresponding measures to prevent and resolve major financial risks according to the cross-correlation between financial products and public opinion,and reduce the impact of systemic risks caused by extreme risk events in the financial market.