Risk contagion in multilayer network of financial markets

Wang, Hu; Li, Shouwei

doi:10.1016/j.physa.2019.123325

Cited by 6 publications

(2 citation statements)

References 22 publications

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“…In 2010, the financial crisis investigation committee defined a shadow bank as a financial institution, which is outside the traditional commercial banking system, engages in financial activities, which are similar to banks' activities and is not or less regulated. In recent years, researchers mainly focus on the operating activities of shadow banks, and they find that it mainly has five characteristics, namely, high leverage (Istiak, 2019), maturity mismatch (Gao et al, 2018), low transparency (Maryam et al, 2018), regulatory arbitrage (Wang and Li, 2020) and high potential risk (S aiz et al, 2019). There are two typical characteristics of shadow bank in Europe and the USA, namely, one, shadow bank is a transaction behavior between product innovation and financial market, the core of which is asset securitization; two, shadow bank is a product of the proliferation of financial innovation and the oversupply of financial services in the context of easy monetary policy and less regulation, and it is a reflection of excessive financial development ).…”

Section: Literature Reviewmentioning

confidence: 99%

Risks’ cross-contagion between shadow banks based on complex network theory: evidence from China

Jin

2020

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Purpose The purpose of this paper is to analyze the network path and internal mechanism of risks’ cross-contagion between shadow banks and design strategies for preventing risk infection between shadow banks. Design/methodology/approach Using the complex network theory, analyze the mechanism of risks’ cross-contagion between shadow banks from the credit network, business relationship network (BRN) and social network (SN); the cross-contagion mechanism using the structural equation model on the basis of China’s shadow banks is tested; based on the three risk infection paths, the prevention and control strategies for risk infection using the mathematical models of epidemic diseases are designed. Findings There are three network risk contagion paths between shadow banks. One, the credit network, risks are infected crossly mainly through debt and equity relationships; two, the BRN, risks are infected crossly mainly through business network and macro policy transmission; three, investor SN, risks are infected crossly mainly through individual SN and fractal relationships. The following three strategies for preventing risk’s cross-contagion between shadow banks: one, the in advance preventing strategy is more effective than the ex post control strategy; two, increasing the risk management coefficient; three, reducing the number of risk-infected submarkets. Originality/value The research of this study, especially the strategies for preventing the risks’ cross-contagion, could provide theoretical and practical guidance for regulatory authorities in formulating risk supervision measures.

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Section: Literature Reviewmentioning

confidence: 99%

Risks’ cross-contagion between shadow banks based on complex network theory: evidence from China

Jin

2020

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“…There are a variety of factors, some of which have very close and complex relationships. Many scholars use network analysis to explore these relationships [21][22][23]. The correlation, causation, cointegration, and other relationships between price fluctuations between multiple stocks are important components of complexity science.…”

Section: Introductionmentioning

confidence: 99%

Research on the Quantitative Causal Transmission of Stock Price Fluctuations of Listed Companies in the Rare Earth Industry Chain

Dong,

Jia,

Wang

et al. 2023

International Journal of Energy Research

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Rare earth is an important strategic mineral resource, and the study of the causes of stock price fluctuations of rare earth listed companies and their transmission can enable all parties in the market to have a clearer understanding of current market relationships. In this study, the quantitative causality analysis model and complex network method are used to analyze each link within the rare earth industry chain and the relationship between regions from the quantitative causality of stock price fluctuations among listed companies in the rare earth industry. The main transmission paths of fluctuations in each link between companies are also given. It is found that the quantitative causal relationship between the price fluctuations of rare earth industry stocks has positive causation, negative causation, and unclear causation, and the dominant causal relationship is mostly positive causation. The positive causal relationship between enterprises in the same region is significantly greater than that between enterprises in different regions. The negative causal relationship and unclear causal relationship between enterprises in different regions are significantly greater than the negative causal relationship and unclear causal relationship between enterprises in the same region.

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Modeling the Paths of China’s Systemic Financial Risk Contagion: A Ripple Network Perspective Analysis

2022

Comput Econ

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Risk contagion in multilayer network of financial markets

Cited by 6 publications

References 22 publications

Risks’ cross-contagion between shadow banks based on complex network theory: evidence from China

Risks’ cross-contagion between shadow banks based on complex network theory: evidence from China

Research on the Quantitative Causal Transmission of Stock Price Fluctuations of Listed Companies in the Rare Earth Industry Chain

Modeling the Paths of China’s Systemic Financial Risk Contagion: A Ripple Network Perspective Analysis

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