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

Abstract

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

CLC Number:

F831.5

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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Macro Uncertainty and Crude Oil Price Risk Based on Nonparametric Multiple Expectile

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