Research On Crude Oil Futures Risk Measurement And Spillover Effect Based On Conditional Autoregressive Value At Risk

As an important industrial raw material,crude oil has been widely used in all walks of life in the national economy and plays an important role in the development of the economy and society.With the increasingly prominent financial attributes of crude oil,crude oil futures prices have become the pricing basis for spot prices.Crude oil futures prices will be affected by geopolitics and financial capital and other multi-dimensional factors,and will deviate from their supply and demand fundamentals in the short term.Since the 21st century,the price of crude oil futures has undergone severe fluctuations for many times,which not only severely affected social and economic development,but also harmed the interests of enterprises and investors related to the crude oil industry chain.From the perspective of crude oil futures,this article takes the market risk of crude oil futures as the research object,and uses univariate and bivariate conditional autoregressive value at risk to study the risk measurement and spillover effects of crude oil futures.The specific discussion is divided into the following five chapters:The first chapter is the introduction,which mainly introduces the research background,research significance and literature review of this article.First,it explains the violent fluctuations in the crude oil futures market in recent years.Effective risk measurement and spillover efect analysis of the crude oil futures market has important theoretical and practical significance.Secondly,it reviews the research methods of risk measurement and risk spillover at home and abroad.Finally,it introduces the research framework and content of this paper,and summarizes the innovations and shortcomings of the full text.The second chapter introduces the basic theory of the method used in this article,first introduces the main influencing factors of crude oil futures price,and then discusses the method used in this article from two aspects.On the one hand,it introduces the conditional autoregressive value-at-risk model(CAViaR)based on quantile regression,and the likelihood ratio test and dynamic quantile test used to test risk measurement methods.On the other hand,it introduces the multivariate multi-quantile conditional autoregressive value-at-risk model(MVMQ-CAViaR)used to analyse risk spillover effects.The third chapter carries on the risk measurement of crude oil futures prices.Taking Brent crude oil futures as the research object,using the conditional autoregressive value-at-risk model and the GJR model for empirical research,the results show that the asymmetric conditional autoregressive value-at-risk model is estimated in the four types of conditional autoregressive value-at-risk models and the GJR model It has the best effect and can effectively measure the risk of Brent crude oil futures.The fourth chapter studies the risk spillover effects of crude oil futures market and external related markets on the basis of the asymmetric conditional autoregressive value-at-risk model.Selected Brent crude oil futures,US dollar index futures,S&P 500 index futures,New York gold futures and VIX index futures to analyze risk overflow.First,use the risk Granger causality test to determine the direction of spillover,and then use the multi-quantile conditional autoregressive value-at-risk model to analyze the strength of the risk spillover effect.The fifth chapter summarizes the results of empirical research and provides corresponding reference opinions for policymakers based on the development of my country's crude oil market.Finally,based on the current deficiencies of this article,the future research prospects are summarized.Main work and conclusions of this paper:The conditional autoregressive value-at-risk model is used to measure the risk of crude oil futures.This model can effectively avoid the shortcomings of traditional measurement methods that need to assume the distribution of returns and directly model returns.In the estimation process,it is found that the asymmetric CAViaR model has achieved good estimation results in both the upward and downward returns.By interpreting its parameters,it is found that there is an asymmetric leverage effect in the risk of crude oil futures,and crude oil futures generally show the characteristics of mild rise and sharp decline.After that,an asymmetric multi-quantile conditional autoregressive value-at-risk model is used to analyze the risk spillover analysis of Brent crude oil futures and the US dollar market,gold market,stock market and VIX panic index.The results show that the risk spillover effect between the US dollar market and the crude oil market is obvious,and there is a negative spillover relationship between the two.The stock market and the crude oil market generally show the same rise and fall,and the decline in the stock market will increase the downside risk of crude oil futures.At the same time,the decline in crude oil increases the upside risk of the VIX index,which triggers investor panic.The gold market and the crude oil market generally show a negative spillover relationship,but the spillover effect is not obvious.In summary,in the research of using univariate and bivariate conditional autoregressive value-at-risk to measure the risk of crude oil futures market and spillover effects,it can be found that crude oil futures market risk is caused by the interaction of many factors.In the foreign exchange market,the stock market has a greater impact on the crude oil futures market,and risks can easily be passed to the crude oil futures market through the US dollar and US stocks.The Shanghai crude oil futures market is currently in a stage of steady development,but domestic crude oil prices are in a state of passively accepting risks.Therefore,my country's crude oil futures market and related derivatives trading mechanisms should be improved to make Shanghai crude oil futures operate more stable and function more effectively.,To help related companies and investors resist external market risks.