As the international environment changes, frequent geopolitical crises continue to hinder the healthy development of global stock markets. To analyze in-depth the risk contagion path between the international stock market and geopolitics under the impact of extreme events, this paper explores the tail risk interactive contagion mechanism and dynamic effects of the double-layer network between the international stock market and geopolitics from the perspective of complex networks. Empirical research finds that geopolitical conflicts exacerbate risk contagion among international stock markets, and there are significant differences in risk contagion between developed and emerging economies. The analysis of the complex interaction effect in the double-layer network of the international stock market and geopolitics shows that the intralayer risk spillover effect of geopolitics in the short term is significantly higher than that of the stock price volatility network layer. Finally, the study on the dynamic changes of the double-layer network connectedness between the international stock market and geopolitics found that the shock of extreme events, such as military conflict and public health security, is an important factor in triggering the cross-contagion of risks. The research conclusions provide new ideas for preventing the cross-contagion of geopolitical risks in the stock markets of various countries under the evolution of the global political and economic pattern.

This article aims to analyse the dissimilation effect of shadow banking on monetary policy and to judge the cyclical characteristics of shadow banking. Further, we analyse the dynamic response of shadow banking to financial risk shocks and regulatory shocks, and examine the influence of shadow banking on the transmission path of systemic risks, so as to provide theoretical bases for financial supply-side structural reforms in the context of high-quality development. To this end, this article constructs the multi-sector DSGE model that includes the shadow banking sector and the commercial banking sector that subjects to multiple credit regulatory constraints. And then the five-variable VAR model is used to conduct empirical tests. Empirical research has found that Chinese-style shadow banking exhibits countercyclical characteristics, and the existence of shadow banking reduces the transmission effectiveness of credit channel. Numerical simulation analysis finds that positive interest rate shocks would trigger the expansion of shadow banks and increase leverage, while reducing the credit leverage of commercial banks. Technological impacts such as financial technology have reduced loan premiums and have played a role in multi-channel evacuation of risk accumulation from the perspective of inclusive finance.

Given the existence of real estate market bubbles and risks arising from high government debt, countries are faced with the challenge of preventing systemic risks. This study investigates the macroeconomic dynamics of the real estate market and local government debt risk from the perspective of liquidity constraints. We build a dynamic stochastic general equilibrium model with real estate and local government debt risk based on the New Keynesian-Dynamic Stochastic General Equilibrium Model (NK-DSGE) model to investigate the transmission path of local government debt risk under real estate regulation. In addition, we analyze the risk transmission between the real estate market and local government under different tax systems and investigate the shock to household welfare from a local government debt default. The results show monetary policy can effectively control the scale of local government debt to reduce default risk. An increase in property taxes that restrains housing demand can effectively regulate the real estate market. Although reducing taxes can increase macroeconomic output, reducing tax rates on consumption, capital, and labor weakens the liquidity of household assets. Further, lowering taxes increases local government default risk, which reduces household welfare and makes it more difficult for local governments to deleverage. Our findings provide important insights for countries seeking an effective real estate regulation mechanism to curb local government default risk.

To analyze whether information sharing in the institutional investors plays the role of a market stabilizer or risk booster, this paper constructs the institutional investor information network employing the common holding stocks of the mutual funds as links. The information linkages between two funds with large positions in the same stock are hypothesized to be connected to each other. Then, we use the information sharing efficiency in the fund networks to study the effects of information transmission on stock market extreme risk and financial systemic risk. Especially, the speed of information diffusion in the network is characterized by the topology structures based on social network theory. Empirical research studies find that the Chinese fund information network exhibits small-world characteristics, which reflects rapid speed of information diffusion. Seen from the idiosyncratic risk of volatility, information sharing of institutional investors can improve the behavior consistency of fund managers, thus increasing the stock volatility via herd effects. Besides, it can be concluded that institutional investor information sharing can reduce the extreme risk by promoting the comprehensiveness of information flow and the market pricing efficiency of stocks, thereby reducing the degree of financial systemic risk. The obtained conclusions provide suggestions for decision-making of institutional investors. It can help the regulators to pay attention to the herd effects so as to control systemic risk.

It is of great significance to improve the corporate governance structure to study whether independent directors play the role of ‘vase’ in the governance of listed companies. Based on the social network theory, this article constructs the social network formed by interlocking independent directors and examines the influence of independent director network on stock price crash risk. The mechanism test analyses the mediating effect of principal–agent problem and large shareholder’s tunnelling on stock price crash risk. The empirical research shows that the higher the network centrality of the company’s independent directors, the lower the stock price crash risk. The independent director network can restrain the company’s stock price crash risk by reducing two types of agency costs. Further research finds that the influence of independent director network on stock price crash risk is more pronounced in companies with unreasonable ownership structure, poor internal governance and weak external supervision. The research conclusions have important implications for listed companies to reduce the risk of stock price crash and maintain the stability of the capital market.