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金融研究  2018, Vol. 459 Issue (9): 192-206    
  本期目录 | 过刊浏览 | 高级检索 |
国际原油市场极端风险的测度模型及后验分析
王鹏, 吕永健
西南财经大学中国金融研究中心,四川成都 611130;
东北财经大学金融学院,辽宁大连 116023
Extreme Risk Measurement Models of International Oil Market and Backtesting Analysis
WANG Peng, LV Yongjian
Institute of Chinese Finance Studies, Southwestern University of Finance and Economics;
School of Finance, Dongbei University of Finance and Economics
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摘要 采用可以捕捉收益分布尾部极端风险的ES(Excepted Shortfall)指标,同时基于时变高阶矩波动模型和常规GARCH族模型建立风险测度模型,并在多、空头寸共20个分位数水平下,综合对比了不同模型在国际原油市场风险测度中表现出的精确性差异。研究结果表明:时变高阶矩波动模型可以刻画原油市场收益分布中的时变偏度和时变峰度特征,更好地测度原油市场的极端风险,同时GARCHSK-M模型表现出了相对最高的风险测度精确性,可以作为测度原油市场极端风险相对合理的模型选择。
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王鹏
吕永健
关键词:  极端风险  预期损失  时变高阶矩波动模型  原油市场    
Abstract:  This paper use ES index which can describe the extreme risk of the tail distribution, at the same time, take the time-varying of high order moments volatility model and conventional GARCH models as risk measurement model, make comprehensive comparison of the exact difference between different models in 20 different quantile levels. The main conclusions of this paper include: The accuracy of time-varying higher order moments volatility model was significantly better than constant higher moments volatility model on the measurement of ES and GARCHSK-M model can be used as a relatively rational choice for estimating the ES of international oil market.
Key words:  Extreme Risk    Excepted Shortfall    Time-varying Higher Moments Models    Crude Oil Market
JEL分类号:  C52   C53   G15  
基金资助: 本文感谢西南财经大学中央高校基本科研业务费专项资金资助项目(JBK1805003),教育部人文社会科学研究规划基金项目(15YJA790057)和国家自然科学基金项目(71473200; 71801034)的资助。
通讯作者:  吕永健,经济学博士,讲师,东北财经大学金融学院,Email:lyuyongjian@163.com.   
作者简介:  王 鹏,管理学博士教授,西南财经大学中国金融研究中心,Email:wangpengcd@126.com.
引用本文:    
王鹏, 吕永健. 国际原油市场极端风险的测度模型及后验分析[J]. 金融研究, 2018, 459(9): 192-206.
WANG Peng, LV Yongjian. Extreme Risk Measurement Models of International Oil Market and Backtesting Analysis. Journal of Financial Research, 2018, 459(9): 192-206.
链接本文:  
http://www.jryj.org.cn/CN/  或          http://www.jryj.org.cn/CN/Y2018/V459/I9/192
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