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Spillover of international crude oil prices on China's refined oil wholesale prices and price forecasting:Daily-frequency data of private enterprises and local refineries 被引量:2
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作者 Xun-Zhang Pan Xi-Ran Ma +3 位作者 Li-Ning Wang Ya-Chen Lu Jia-Quan Dai Xiang Li 《Petroleum Science》 SCIE CAS CSCD 2022年第3期1433-1442,共10页
Compared with retail prices of state-owned companies used in almost all existing studies,China’s refined oil wholesale prices of private enterprises and local refineries are more affected by the market and better ref... Compared with retail prices of state-owned companies used in almost all existing studies,China’s refined oil wholesale prices of private enterprises and local refineries are more affected by the market and better reflect the real supply-demand situation.For the first time,this paper applies own-monitored dailyfrequency wholesale prices of China’s private enterprises and local refineries during 2013-2020 to derive spillover effects of international crude oil prices on China’s refined oil prices through the VAR-BEKKGARCH(vector autoregression-Baba,Engle,Kraft,and Kroner-generalized autoregressive conditional heteroscedasticity)model,and then tries to forecast wholesale prices through the PCA-BP(principal component analysis-back propagation)neural network model.Results show that international crude oil prices have significant mean spillover and volatility spillover effects on China’s refined oil wholesale prices.Changes in crude oil prices are the Granger cause of changes in refined oil wholesale prices.With the improvement of China’s oil-pricing mechanism in 2016,the volatility spillover from the international crude oil market to China’s refined oil market gradually increases,and the BRENT price variation has an increasing impact on the refined oil wholesale price variation.The PCA-BP model could serve as a candidate tool for forecasting China’s refined oil wholesale prices. 展开更多
关键词 Own-monitored daily-frequency data refined oil wholesale prices Spillover effects VAR-BEKK-GARCH PCA-BP neural Network
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