Research On The Correlation Between International Oil Price Trend Factors And Energy With Related Industry Returns

Since the use of oil by ancient civilizations such like Babylon in the 10th century BC,oil has played an important role in human production and life.Until now,oil is still an important factor affecting the global economy.Therefore,oil is called black gold.Judging from the impact of historical oil price fluctuations on the economy.Whether oil prices rise or fall,they all have affected the global stock markets and caused financial market turbulence even systemic financial risks.In a sense,the risk of oil prices can also be used as a"wind vane"for the health of economy.In response,China strictly controls systemic financial risks and vigorously stabilizes the development of the economic market environment.The relationship between energy related industries and oil is inseparable.The energy industry,as one of the important components of national economic support,plays a decisive role in the country’s economic development.Relationships are important.However,the existence of information noise and time lag in oil prices greatly reduces the prediction of oil prices for energy with related industries.It is important to find an oil price factor that eliminates noise to better predict the stock index returns of energy with related industries.It is beneficial for the development of energy with related industries.It will also help investors build better and lower risk investment portfolios.In order to eliminate the information noise in oil prices and find the relationship between international oil prices and energy related industries in the stock market more comprehensively and accurately,the following research steps have been performed:Based on previous studies,we analyzed the impact of international oil prices on the stock market.In theory,the mechanism of the fluctuation of crude oil prices is analyzed through historical stages.We analyze the theory of oil prices on the stock market from both the real economy and financial markets.Then we analyze the impact of oil prices on energy related industries.In terms of data,we need international oil price volatility,index returns of energy related industries and market index returns.We choose four industries related to energy:coal industry,energy industry,petrochemical industry,and oil gas industry.For the market index,we use the CSI 300 Index.The oil price is selected from the future price of West Texas Intermediate Crude Oil（WTI）.Analyze the descriptive statistics of the data and find that the data can be applied to semi-parametric models and GARCH（1,1）models.Secondly,on the basis of previous studies,in order to reduce the information noise and time lag of oil prices,we used the moving average method to construct the international oil price trend factor.In empirical terms,we use the international oil price trend factors to estimate semi-parametric econometric models for various industries,and find the best international oil price trend factors that can predict energy related industries based on the model’s fit.Then we established the GARCH（1,1）model to further verify and compare.The following conclusions were reached:1.The international oil price trend factor constructed using the moving average method to reduce noise is more powerful than the international oil price volatility in predicting the returns of energy with related industries.And in the relationship chart between the fitting degree of the semi-parametric model and W,we can see that when W=13,the semi-parametric models of the coal,energy,petrochemical,and oil gas industries have the best fitting effect,R_o,T,13has the strongest predictive power and the least noise in the energy with related industries.2.Yields of energy related industries are positively correlated with market yields.The energy with related industries have a positive relationship with the optimal international oil price trend factor,but this positive relationship is a dynamic positive relationship.Due to data errors,data noise,and time lag,there will be a small number of negative effects.But most of data is in a positive effect,especially where data is intensive.The optimal international oil price factor can predict the yields of energy with related industries.3.The GARCH（1,1）model also verified that the optimal international oil price trend factor has a positive impact on energy related industries,and there are fluctuations in the two.The optimal international oil price trend factor has fluctuating spillover efficiency for energy with related industries.4.In the study of this paper,the semi-parametric model has better modeling ability and practical significance than the GARCH（1,1）model.Finally,on the basis of summarizing the conclusions of the full text,this article puts forward suggestions for the government to deal with fluctuations in oil prices and proposes investment ideas for investors based on the current state of economic development in China and China’s national conditions.