Research On The Correlation Between International Crude Oil Price And Chinese Stock Market

Since the 1990 s,China has started to become a net oil importer from net oil exporters,and oil imports have increased year by year.Especially after 2001,China’s accession to the WTO(WTO),the number oil imports of China,consumption is rapidly rising every year,and in 2003 surpassed Japan to become the world’s second largest oil consumer.In 2017,China’s crude oil imports reached 41.957 million tons,and the proportion of crude oil in China’s energy consumption structure has increased continuously,making it more sensitive to fluctuations in international crude oil prices.Studying the impact of international crude oil price fluctuations on various industries will help deal with the economic disturbance caused by fluctuations in the international energy market in advance and maintain the stable operation of the economy.Previous studies on the impact of crude oil price on economic development have focused on the study of macroeconomic variables’ reactions to oil price volatility.Research on the stock market has focused on integrated stock indexes or certain industries that are closely linked to oil.This article does not set a specific industry but studies the relationship between international crude oil prices and 27 different industries and conducts a comparative analysis.In the study,weekly data from January 2000 to January 2018 were used.The VAR-DCC-GARCH model was established to model international crude oil prices and stock indexes in different industries and conduct comparative analysis.Taking into account the asymmetry of financial market volatility,we replaced the EGARCH model and the GJRGARCH model on the basis of the original model.The main research conclusions are: During the sample period,the average yields of all industries,including international crude oil prices,were positive,and the average yields of household appliances,food and beverage,pharmaceutical biology,automobiles,leisure services,and real estate industries were higher.It shows that since 2000,the residents’ expenditure on clothing,food,housing,entertainment and medical care has increased faster than other industries.This indicates to a certain degree that economic development makes the living standards of the residents and medical services increase faster than the industry average;The VAR model analysis found that the international crude oil price has a volatility spillover effect on the steel industry,extractive industry,chemical industry,machinery and equipment industry,national defense industry,textile and clothing industry and non-ferrous metals industry.building materials industry,building decoration Industry,commercial trade,light industry manufacturing agriculture,forestry,animal husbandry and fishery;At the 95% confidence level,the auto industry and public utilities have a volatile spillover effect on international oil prices;Under the 95% confidence level,there is a two-way volatility spillover effect between the electronics industry and international crude oil prices.At the 90% confidence level,there is a two-way volatility spillover between the media and international crude oil prices.There is no significant single or two-way volatility spillover effect between the industry and international crude oil prices other than those mentioned above;This paper compares the three models and finds that only 13 groups of EGARCH residuals have passed the test.The number of GJRGARCH and GARCH models fit for the industry is similar,and the latter is only one more than the former.There is an inclusion relationship among the three applicable industries,that is,the industry GJRGARCH applicable to the EGARCH model is also applicable,and the industry GARCH model applicable to GJRGARCH is also applicable.And according to the AIC criteria,the AIC minimum value was generated in EGARCH or GJRGARCH in all industries where all three models were used.In the industry where only GJRGARCH and GARCH models are applicable,the minimum AIC values are all GJRGARCH models,which indicates that the industry fluctuations are asymmetrical,and that some industry asymmetric fluctuations are exponential;According to the DCC model parameter test,only the a1 and b1 parameters of the real estate industry pass the significance test at the same time.Most other industries only have the parameter b1 passed the significance test,indicating that there is a strong continuation of the correlation between the various industries and international crude oil prices.At the same time,by analyzing the time-varying dynamic correlation coefficient maps of various industries and crude oil,it is found that the correlation coefficient between various industries and crude oil is not high,most of them are around 0.1,but the correlation coefficient can reach 0.3 or more in a special period.This fully shows that the correlation coefficient changes dynamically.In this paper,there are six groups of failures in the residual fitting.The main reason is that the residual autocorrelation test fails after fitting.The fitting of the higher-order lag model is not suitable for this article.