In recent years, influenced by political and economic events, the price of the Shanghai crude oil futures market has changed significantly. It is therefore of great academic and practical importance to accurately measure the price risk of the Shanghai crude oil futures market. This paper uses a variety of GARCH models to predict price risk and uses the Model Confidence Set approach to evaluate forecasting performance. The daily closing prices of the Shanghai crude oil futures market from March 2018 to February 2021 are used. The empirical results show that futures price responds more strongly to negative news shocks than to positive news shocks, and the EGARCH model can effectively improve the accuracy of price risk measurement. An accurate assessment of the price risk can help investors to arrange funds in advance or to rebalance trading positions in order to meet the margin requirements.
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Univ Technol Sydney, Finance Discipline Grp, UTS Business Sch, Broadway, NSW 2007, AustraliaUniv Technol Sydney, Finance Discipline Grp, UTS Business Sch, Broadway, NSW 2007, Australia
Chiarella, Carl
Kang, Boda
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Univ Technol Sydney, Finance Discipline Grp, UTS Business Sch, Broadway, NSW 2007, AustraliaUniv Technol Sydney, Finance Discipline Grp, UTS Business Sch, Broadway, NSW 2007, Australia
Kang, Boda
Nikitopoulos, Christina Sklibosios
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Univ Technol Sydney, Finance Discipline Grp, UTS Business Sch, Broadway, NSW 2007, AustraliaUniv Technol Sydney, Finance Discipline Grp, UTS Business Sch, Broadway, NSW 2007, Australia
Nikitopoulos, Christina Sklibosios
Thuy-Duong To
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Univ New S Wales, Australian Sch Business, Sydney, NSW 2052, AustraliaUniv Technol Sydney, Finance Discipline Grp, UTS Business Sch, Broadway, NSW 2007, Australia
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Department of Economics, St. Mary's College of Maryland, St. Mary's CityDepartment of Economics, St. Mary's College of Maryland, St. Mary's City
Ye M.
Zyren J.
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Petroleum Division, EI-42, Office of Oil and Gas, Energy Information Administration, U.S. Department of Energy, Washington, DC 20585, 1000 Independence Ave., SWDepartment of Economics, St. Mary's College of Maryland, St. Mary's City
Zyren J.
Shore J.
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Petroleum Division, EI-42, Office of Oil and Gas, Energy Information Administration, U.S. Department of Energy, Washington, DC 20585, 1000 Independence Ave., SWDepartment of Economics, St. Mary's College of Maryland, St. Mary's City
Shore J.
Lee T.
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School of Business Administration, Marymount University, Arlington, VA 22201Department of Economics, St. Mary's College of Maryland, St. Mary's City
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Univ Tunku Abdul Rahman UTAR, Fac Business & Finance, Kampar, Perak, MalaysiaUniv Tunku Abdul Rahman UTAR, Fac Business & Finance, Kampar, Perak, Malaysia
Go, You-How
Lau, Wee-Yeap
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Univ Malaya, Fac Econ & Adm, Kuala Lumpur, MalaysiaUniv Tunku Abdul Rahman UTAR, Fac Business & Finance, Kampar, Perak, Malaysia
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Donghua Univ, Glorious Sun Sch Business & Management, Shanghai, Peoples R ChinaDonghua Univ, Glorious Sun Sch Business & Management, Shanghai, Peoples R China
Wu, Xiaofei
Miao, Hailong
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Donghua Univ, Glorious Sun Sch Business & Management, Shanghai, Peoples R ChinaDonghua Univ, Glorious Sun Sch Business & Management, Shanghai, Peoples R China
Miao, Hailong
Zhu, Shuzhen
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Donghua Univ, Glorious Sun Sch Business & Management, Shanghai, Peoples R ChinaDonghua Univ, Glorious Sun Sch Business & Management, Shanghai, Peoples R China
Zhu, Shuzhen
Li, Xin
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Donghua Univ, Glorious Sun Sch Business & Management, Shanghai, Peoples R ChinaDonghua Univ, Glorious Sun Sch Business & Management, Shanghai, Peoples R China