| In recent years,global warming and extreme climate disasters have occurred frequently,and the impact of climate change on the financial system has become increasingly obvious.The central banks of various countries have reached a consensus on the climate issue,believing that climate risk is one of the important sources of systemic financial risk.Therefore,international organizations dealing with climate change,such as the central banks and supervisors network for greening the financial system,actively advocate that central banks of various countries carry out research on climate finance,and analyze the relationship between climate and environmental governance and their own economic and financial systems.Based on the current status of climate risk research,this paper will explore the mechanism of climate physical risk and climate transition risk on financial stability from the perspective of financial stability.For climate physical risks,since extreme disasters have a wide range of impacts and involve many industries,this paper will use provincial-level panel data to conduct an empirical analysis of physical risks.First,we use the entropy method to establish financial stability index system,extreme climate disaster index system and various types of disaster index system,and then analyze the impact of extreme climate disasters and long-term climate change factors including average temperature and average precipitation on financial stability.Next,we explore the mechanism of various types of disasters,and analyze the intermediary effect of extreme climate disaster indicators and how various types of disasters conduct indirect risk transmission through the banking,securities and insurance markets.Finally,we come to the following conclusions: Extreme climate disaster indicators have a significant negative impact on financial stability.Long-term climate change factors represented by warm and humid climate conditions can improve the overall financial stability and promote the development of the financial system towards a stable situation.Rainstorm and flood disasters,gale,hail and lightning disasters,typhoon disasters,snow disasters and low temperature freezing disasters can have different degrees and directions of impact on financial stability,while the effect of drought disasters is not significant.In the exploration of intermediary effects,extreme climate disaster indicators can conduct indirect risk transmission through three market channels,and rainstorm and flood disasters,gale,hail,lightning disasters,snow disasters,and low temperature freezing disasters can all transmit risks to the financial system through one or two markets.But the intermediary effect of typhoon disaster is not established.As for climate transition risks,since it includes changes in public policies,technological changes,changes in consumer preferences,and market changes,it will affect high-carbon industries represented by traditional energy industries and high energy-consuming industries,and low-carbon industries represented by new energy industries and environmental protection industries.Therefore,in this part of the paper,we will use the stock price data of carbon-related industries and financial industries to analyze volatility spillovers.Firstly,at the method level,NETs VAR is used to construct Granger causality network and contemporaneous partial correlation network,and secondly,the complex network model is used to explore the impact mechanism from the three aspects of cross-sector risk dependence,carbon-related industry risk contribution to various financial industries,and the ranking of financial core companies receiving volatility spillovers.After exploring the influence mechanism of these three aspects,we finally found that when calculating the network density with absolute volatility spillover,the density of the partial correlation network in the same period is relatively denser.The volatility spillover of the Granger causality network has directionality and time lag,which means that one industry has a positive or negative impact on the future volatility of another industry.The volatility spillover of the contemporaneous partial correlation network means that the direction of volatility changes between different industries in the same period is the same or opposite.The overall carbon-related industries have certain volatility spillovers to different types of financial sub-sectors,and the types of affected financial industries are closely related to the ways and channels for carbon-related industries to obtain investment and financing.From the perspective of sectoral risk contribution,the industry with the highest contribution to the risk of large state-owned banks is the traditional energy industry such as oil service engineering.For other financial sub-sectors,the new energy and environmental protection industries have also become the main source of risk.Therefore,what risk management measures to take should be considered in combination with their own business direction.From the perspective of risk acceptance of core companies in the financial industry,the top-ranked companies are most vulnerable to risks from carbon-related industries.Some carbon-related industries have no time-lag fluctuation contribution to the companies in the financial sub-industry.In addition to the financial sub-sectors such as banking,insurance and securities that are vulnerable to climate disasters at the theoretical level,diversified financial industries including leasing companies,investment companies,trust companies,and futures companies have also become the main recipients of volatility spillovers from the carbon industry.It is particularly important to actively improve the ability of such companies to deal with risks.Our country’s financial industry should prudently respond to the impact of climate risks,and achieve risk control in the balance between social responsibility and business operations,so as to reduce the impact of extreme climate disasters and climate transition policies on the institutions themselves,and prevent risks from spreading to the entire financial system. |