Research On The Application Of Multifractal Analysis Methods In Financial Market

In recent years,the world situation has not been stable.On February 24,2022,the Russia-Ukraine conflict kicked off,and the situation changed rapidly.The Russia-Ukraine conflict has caused serious economic consequences to Europe and even the world.Considering the economic and financial consequences of the dynamic interaction between markets,studying the impact of the Russia-Ukraine conflict on the financial market has important theoretical and practical significance for studying market efficiency and preventing systemic financial risks from major emergencies.In the study of financial time series,traditional time series models are difficult to describe the complexity of financial markets in all aspects.Multifractal covers the relevant content of market complexity,and conducts in-depth analysis,research,and comprehensive elaboration of market operation patterns around multiple aspects such as similarity and scaling scales.Based on this,this article uses multifractal de trend fluctuation analysis(MF-DFA)and multifractal de trend cross correlation analysis(MF-DCCA)two methods have been used to study and demonstrate the complexity of financial markets.The main research contents and conclusions of the paper are as follows:1.Using MF-DFA analysis to study the changes of multifractal characteristics of China’s crude oil related markets(oil,fertilizer,grain)before and after the Russia-Ukraine conflict,we found that the multifractal characteristics of the time series after the conflict broke out significantly increased compared with that before the conflict.This indicates that market efficiency has decreased after the outbreak of conflict.After that,MF-DCCA was used to explore the changes in the interdependencies of oil/fertilizer and oil/grain.The numerical results show that after the outbreak of conflict,the correlation between oil and fertilizer increases significantly,while the correlation between oil and grain does not increase significantly.2.Taking Brent crude oil as an example,MF-DFA is used to explore the impact of the Russia-Ukraine conflict on the effectiveness of the international crude oil market,and MF-DCCA is used to further explore the changes in the correlation between crude oil prices and the capital markets of crude oil importing and exporting countries.By analyzing multifractal indicators such as the generalized Hurst exponents,mass exponents,and multifractal spectrums,the results show that there are multifractal characteristics in the crude oil market before and after the conflict,and the multifractal characteristics are stronger after the conflict.At the same time,for crude oil importing countries,after the outbreak of conflict,the correlation between crude oil prices and their capital markets has significantly increased;On the contrary,for crude oil exporting countries,there is no obvious regularity in the correlation between the two before and after the conflict.In addition,we also found that before and after the Russia-Ukraine conflict,the sustainability of the correlation between the capital market and the crude oil price of the crude oil importing countries was weaker than that of the crude oil exporting countries.Finally,we checked the robustness of the numerical results.When the significance level is 0.05,the P value is calculated and compared with the significance level.The correctness of the conclusions are verified.