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Dynamic Analyses of Contagion Risk and Module Evolution on the SSE A-Shares Market Based on Minimum Information
Muzi Chen1, Yuhang Wang1, Boyao Wu2
1School of Management Science and Engineering, Central University of Finance and Economics, Beijing 102206, China.
Entropy (Basel, Switzerland)
|April 30, 2021
Summary
The Chinese stock market experiences significant interactive effects, especially during bear markets, leading to abnormal volatility and risk contagion. This study analyzed Shanghai Stock Exchange A-shares from 2005-2018 to understand these dynamics.
Area of Science:
- * Financial Economics
- * Network Science
- * Market Dynamics
Background:
- * The Chinese stock market exhibits significant interactive effects, contributing to abnormal volatilities and risk contagion.
- * Understanding these dynamics is crucial for investment strategies and regulatory policies.
- * Previous research has not fully explored the evolving network structures during different market conditions (bull vs. bear).
Purpose of the Study:
- * To investigate the interactive patterns and network evolution in the Shanghai Stock Exchange (SSE) A-shares market.
- * To compare the heterogeneity of market structures during bull and bear market stages.
- * To identify the characteristics of stocks that act as risk sources.
Main Methods:
- * Construction of stock networks using the Least Absolute Shrinkage and Selection Operator (LASSO) method.
- * Analysis of daily stock returns from the SSE A-shares market between 2005 and 2018.
- * Application of the Map Equation method to analyze the evolution of network modules.
Main Results:
- * The connected effect is more pronounced in bear markets, increasing market volatility.
- * Network analysis revealed a system module in early stages and industry-driven module differentiation in later stages.
- * Medium- and small-cap stocks with weaker financial health were identified as primary risk sources, particularly in bear markets.
Conclusions:
- * Market interconnectedness significantly impacts volatility and risk contagion, especially during downturns.
- * The structural evolution of the stock market network shifts from systemic to industry-specific clustering.
- * Identifying vulnerable stocks is key for mitigating systemic risk and informing policy decisions.
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