Research On The Relationship About Oil Price,Geopolitical Risks And Clean-energy Stock Price

With the development of industrialization,oil plays an increasingly important role in industrial production.In recent years,the fluctuation of oil price has a significant impact on economic development,and energy has become a key issue in economic development.As an alternative product of fossil energy,clean energy can solve the contradiction between resource shortage and environmental pollution caused by fossil energy consumption to a large extent,and improve the proportion of clean energy in energy consumption.It is the only way for China to practice the road of sustainable development and realize an environment-friendly society.However,with the changes in international geopolitical risks,the supply of oil and the imbalance of prices,it has brought a huge impact on economic development,especially the clean energy stock market,which is closely related to the crude oil market.Therefore,using a reasonable model to study the relationship between geopolitical risks,oil price and clean energy stock market is of great significance for the country to improve energy consumption structure,practice sustainable development path and investors to carry out statistical arbitrage.This paper first analyzes the relationship between oil price,geopolitical risks and clean energy stock price.The causal relationship between any two of the variables and their tail characteristics,and the influence of the third variable on the causal relationship are analyzed.For example,there is a causal relationship between oil prices and clean energy stock prices,and this causal relationship varies when oil prices are at different quantile levels,and this causal relationship is affected by geopolitical risks.In this context,this paper then proposes that in order to describe the distribution characteristics of causality between two variables more accurately and comprehensively,it is necessary to incorporate the influence of the third variable into the model,that is,to study the distribution characteristics of causality between two variables based on multivariate model.However,the existing research on the causal relationship between the three is often based on the two-variable model,ignoring the influence of other factors on the relationship between the two.Among them,the classic mean Granger causality test(GC)only focuses on the linear relationship between the overall mean of the two variables,ignoring the tail characteristics of financial markets;although quantile Granger causality test(GCQ)based on quantile regression can depict different tail characteristics,it cannot deal with multivariate problems.Therefore,this paper introduces the more advanced quantile parameterized conditional Granger causality test(CGCQ)method to study the causal relationship between two variables at different quantiles under the condition that the influence of the third variable is included in the research framework,so as to more accurately describe the dynamic characteristics of the causal relationship between variables at different tails.In the empirical analysis part,this paper selects the monthly data of the geopolitical risks index(GPR),oil price(Brent price index and WTI price index)and clean energy stock price index(Wilder Hill clean energy price index and SP clean energy price index)from 2011 to 2021 as the research object.Based on the three-variable model,the quantile parametric conditional Granger causality test method(CGCQ)is used to study the linkage between the two variables.Through empirical research,the following conclusions are drawn : Firstly,based on the control of the impact of clean energy stock prices,geopolitical risks and oil prices are the Granger causes of each other in the low and high quantiles.The occurrence of extreme geopolitical events will cause fluctuations in oil prices,and violent fluctuations in oil prices may also cause changes in geopolitical risks.Secondly,under the condition of controlling the influence of geopolitical risks,oil price has a one-way causal relationship with clean energy stock price.Oil price has a significant impact on clean energy stock price at low,medium and high quantiles,but clean energy stock price can not explain the fluctuation of oil price well.Thirdly,under the condition of controlling the impact of oil prices,geopolitical risk has a one-way causal relationship with clean energy stock prices.Geopolitical risk has an explanatory power for clean energy stock prices at low and high quantiles,while clean energy stock prices have no impact on geopolitical risks.In addition,the results based on CGCQ test are compared with those based on GCQ method and GC method.The results of the GC test showed that there was no causal relationship between the variables.The GCQ method believes that there are differences in the causal relationship between variables in different distribution ranges,but ignores the indirect influence of other factors on the causal relationship between the two variables,and the results are often not ideal;the CGCQ method not only considers the indirect influence of other variables on the causal relationship between the two variables,but also pays attention to the dynamic relationship between different distribution intervals and quantiles,which can more comprehensively test the linear or nonlinear causal relationship between the variables.