Information flow networks of Chinese stock market sectors
arXiv:2004.08759 · doi:10.1109/ACCESS.2020.2966278
Abstract
Transfer entropy measures the strength and direction of information flow between different time series. We study the information flow networks of the Chinese stock market and identify important sectors and information flow paths. This paper uses the daily closing price data of the 28 level-1 sectors from Shenyin \& Wanguo Securities ranging from 2000 to 2017 to study the information transmission between different sectors. We construct information flow networks with the sectors as the nodes and the transfer entropy between them as the corresponding edges. Then we adopt the maximum spanning arborescence (MSA) to extracting important information flows and the hierarchical structure of the networks. We find that, during the whole sample period, the \textit{composite} sector is an information source of the whole stock market, while the \textit{non-bank financial} sector is the information sink. We also find that the \textit{non-bank finance}, \textit{bank}, \textit{computer}, \textit{media}, \textit{real estate}, \textit{medical biology} and \textit{non-ferrous metals} sectors appear as high-degree root nodes in the outgoing and incoming information flow MSAs. Especially, the \textit{non-bank finance} and \textit{bank} sectors have significantly high degrees after 2008 in the outgoing information flow networks. We uncover how stock market turmoils affect the structure of the MSAs. Finally, we reveal the specificity of information source and sink sectors and make a conclusion that the root node sector as the information sink of the incoming information flow networks. Overall, our analyses show that the structure of information flow networks changes with time and the market exhibits a sector rotation phenomenon. Our work has important implications for market participants and policy makers in managing market risks and controlling the contagion of risks.
arXiv comment12 pages including 9 figures
References in corpus (25)
- Measuring Information Transfer
- The diameter of the world wide web
- Hierarchical Structure in Financial Markets
- Dynamical and correlation properties of the Internet
- A Random Matrix Approach to Cross-Correlations in Financial Data
- A tool for filtering information in complex systems
- Dynamics of market correlations: Taxonomy and portfolio analysis
- Inverse Cubic Law for the Probability Distribution of Stock Price Variations
- Networks of equities in financial markets
- Clustering and information in correlation based financial networks
- Transmission of Information and Herd Behavior: an Application to Financial Markets
- Bubble Diagnosis and Prediction of the 2005-2007 and 2008-2009 Chinese stock market bubbles
- Information flow between stock indices
- Correlation, Network and Multifractal Analysis of Global Financial Indices
- Mutual Information Rate-Based Networks in Financial Markets
- Spanning Trees and bootstrap reliability estimation in correlation based networks
- Transfer Entropy as a Log-likelihood Ratio
- Structure and causality relations in a global network of financial companies
- Degree stability of a minimum spanning tree of price return and volatility
- The dynamic of information-driven coordination phenomena: a transfer entropy analysis
- Antibubble and Prediction of China's stock market and Real-Estate
- Spectral and network methods in the analysis of correlation matrices of stock returns
- Topological structures in the equities market network
- Market correlation structure changes around the Great Crash
- Maximal spanning trees, asset graphs and random matrix denoising in the analysis of dynamics of financial networks