基于非参多元Expectile模型的原油价格风险测度研究—宏观不确定性视角

doi:10.16381/j.cnki.issn1003-207x.2021.2622

摘要/Abstract

摘要： 当下政治经济环境存在诸多不确定性，原油价格随着不确定性的增加而大幅波动，因此在当前不确定性环境中建立一个有效的风险预测模型具有重要的实际意义。本文基于非参多元Expectile模型，选取2010年1月5日至2020年1月6日的美国西德克萨斯原油价格的日度数据，构建同时包含地缘政治风险、经济政策不确定性等六个宏观不确定性变量的原油价格风险预测模型。此外，引入APARCH模型和基于蒙特卡罗方法的GARCH模型，比较以上三个模型预测能力。最后，基于预测的VaR值计算调整的Sharpe比率。结论表明，整体上，非参多元Expectile模型能较好处理多个宏观变量包含的信息，具有更高的预测能力。在不确定性事件叠加发生的时期预测表现依然优于其他模型，减少了不确定性增加导致原油市场波动幅度增加带来的风险，具有更强的稳定性。因此，在经济转型的关键时期，本研究可为政策制定者和监管当局面临不确定性上升环境下建立有效的原油价格风险预测模型提供参考，制定应对政策防范化解风险，同时也为投资者在当前复杂的国际形势下提供预测参考，尽量规避损失同时获取收益。

关键词: 宏观不确定性；非参多元Expectile；原油价格风险测度；Sharpe比率；GBDT算法

Abstract: The crude oil price reflects the impact of macro uncertainty on economic activities and investors' expectations. Once the crude oil price is significantly impacted, the macro uncertainty will affect it in turn. Therefore, it is essential to construct a crude oil price risk prediction model that incorporates several macro variables simultaneously. The main models for measuring crude oil price risk include GARCH, APARCH, GARCH-MIDAS. However, the results may be biased due to the increasing number of parameters estimated by the above model after containing multiple variables.Thus, it aims to explore a risk prediction model that simultaneously contains several variables and has good prediction ability.The nonparametric multiple expectile is suitable for constructing the crude oil price risk measurement model embedded with multiple macro variables because it can estimate more than five explanatory variables.

Key words: macro uncertainty;nonparametric multiple expectile;crude oil price risk; Sharpe ratio; GBDT algorithm

中图分类号:

F831.5

严复雷, 张语桐, 崔钟月, 张高勋. 基于非参多元Expectile模型的原油价格风险测度研究—宏观不确定性视角[J]. 中国管理科学, 2022, 30(12): 222-233.

YAN Fu-lei, ZHANG Yu-tong, CUI Zhong-yue, ZHANG Gao-xun. Macro Uncertainty and Crude Oil Price Risk Based on Nonparametric Multiple Expectile[J]. Chinese Journal of Management Science, 2022, 30(12): 222-233.

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