The network structure of Chinese finance market through the method of complex network and random matrix theory

Abstract

Summary As we know, economic policy has a significant influence on the stock market. So, it should be interesting to detect the relation between the correlation structure of the stock market and economic policy. To achieve this target, the correlation matrix is analyzed through component analysis method first, to detect the economic implication of the components of correlation matrix. It is found that the biggest driving force of market behavior affects the whole stock market instead of individual stock or plate and the evolution of important plates of the second component relates closely to economic policies. Then, ordinary networks, denoising networks, and noise networks are constructed for different periods and distinction among the structures of different networks in the same period is analyzed. The result suggests that the economic factors corresponding to the first and second components make the stock market be sensitive and lead to a gathering effect in ordinary and denoising networks. At last, based on the inferences from this paper, the formation of power law in the stock network and the influence of crisis on the structure of stock network are discussed.

The analysis of cross‐correlation between Istanbul Stock Exchange and major stock markets and indices: An empirical analysis using Random Matrix Theory

“…Several cleaning methods for correlation matrices have been investigated by Bun et al 25 In a different approach, a study focusing on the Korean Stock market have investigated the effect of foreign exchange on the correlations and found that certain sectors showed different behavior than others when their prices converted into Korean Won and US Dollar 26 . In another different setup, Ji et al 27 investigated the relation between the correlation of the Chinese stock market and economic policy. The RMT is not only used for the stock markets but other financial entities.…”

Comparing the collective behavior of banking industry in emerging markets versus mature ones by random matrix approach

“…For these reasons, these systems have various properties, including nonlinearity and collective behavior. Therefore, the study of an entity alone will not be helpful and the whole system must be analyzed collectively [4][5][6][7][8][9]. A notable feature of these systems is the spatial and temporal dependence of their components [10][11][12][13].…”

The Impact of COVID-19 on the Dependence of Chinese Stock Market

“…At the beginning of 2020, the outbreak of COVID-19 caused global panic. It is reported by WHO that up to September 1st, 2020, there have been 25,327,098 confirmed cases of COVID-19, including 848,255 deaths globally. Since the outbreak of COVID-19, in order to effectively curb the spread of the pandemic, many countries have implemented a series of necessary measures, including shutdown of the production and business and home isolation.…”

“…Clearly analyzing the interdependence structure of the stock market is not only of great significance for investors to diversify investment and build investment portfolios during the pandemic, but also is conducive to risk management of the financial market by the regulatory authorities. In recent years, there has been a certain amount of researches on the subject of interdependence among stock markets [18][19][20][21][22][23][24][25]; in these studies, GARCH model, Copula model, Granger causality test, DCC model, and other methods are used to study the interdependence structure between various stock sectors in different countries.…”