Risk Measurement And Application Of Carbon Trading Market Based On B-spline Quantiles And Extreme Value Copula Method

At present,low-carbon development and climate issues have become a global consensus and social responsibility for human development.In the urgent situation of global carbon emissions,emission reduction has expanded from the technical level to the financial market level.As a scarce resource and special asset,carbon emission rights have formed a carbon trading market through trading and conversion between physical markets.Countries around the world are gradually establishing carbon emission trading markets to promote their low-carbon development through market-oriented means.The fluctuation of product prices in the carbon trading market is influenced by various factors,including market supply and demand,political changes,financial crises,climate change,and other factors.The fluctuation caused by these factors will bring risks to the carbon market.Therefore,how to scientifically and reasonably identify and measure market risks is an important issue for the healthy development of carbon trading,which is conducive to adopting effective carbon trading market risk management measures and ensuring the implementation of global emission reduction and low-carbon development.Firstly,this article uses bibliometric methods to organize relevant literature on carbon emission risks both domestically and internationally in recent years.It defines,classifies and describes the characteristics of carbon trading risks.The emergence of carbon trading risks is diversity due to the uncertainty of an event.It divides carbon trading risks into technical risks,legal risks,operational risk,market risks and other forms,with the basic characteristics of controllability and sensitivity,concealment and irregularity,strong destructiveness and infectivity.Analyze the risk of carbon trading market and summarize common measurement methods,including standard deviation method,sensitivity method and Va R method.Secondly,for the measurement of the risk of the provincial carbon trading pilot,this paper comprehensively considers the accuracy,interpretability and the change of the pilot trading volume of the model,and uses B-spline and local polynomial quantile methods to establish and compare the Value at risk measurement model based on nonparametric quantile regression.Considering the accuracy of different model methods,validation was conducted through repeated random sampling and Monte Carlo random number simulation.The results show that the B-spline quantile method with volume as covariate is superior to the local polynomial quantile method in terms of the fitting success rate of failure rate test.From the perspectives of bias,error,and RMSE statistics,the B-spline method has the smallest deviation value and the best data fitting effect.This article analyzes the spline method from the perspectives of practical examples and random numbers.The results show that the spline function has better predictive performance in the field of carbon finance risk,and can be extended to other market risk applications,such as hedge funds,futures hedging,and corporate credit risk.Once again,in response to the risk contagion of the carbon trading market on the stock market and its relationship with its own risks,this paper constructs an extreme Copula-Co Va R model using extreme value theory,Copula function,and Co Va R model.Firstly,the price index synthesis method is used to synthesize the price data of various carbon pilot projects in China into the China Carbon Trading Price Index.Then,the research sample data is preprocessed,yield is taken,and basic tests are conducted.Then,the spillover effect of carbon market risk is measured using the constructed extreme value Copula-Co Va R model to obtain the risk spilloverΔCo Va R value of the carbon market for each stock sector market,Finally,measure the downward ΔCo Va R values at different levels of significance,and explore the relationship between the self-risk and spillover risk of the carbon market at different levels of significance.The results indicate that the Kupiec failure rate test shows that the spillover risk value is effective,and the electricity market has the greatest risk spillover effect on the stock market.The lower the significance level,the greater the risk of the carbon market itself,and the greater the risk spillover of the carbon market to the stock market.Therefore,there is a positive correlation between the two.Finally,this article briefly discusses the limitations and prospects of research on risk measurement and spillover effect measurement in the carbon trading market.