Energy portfolio risk management using time-varying copula methods: application to bonds, interest rate and VIX

Samar Zlitni Abdelkafi, Ahmed Ghorbel, W. Khoufi
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Abstract

This work is concerned with the statistical modelling of hedging and safe haven strategies between the energy sector (crude oil), bonds, VIX and interest rate using the concept of copulas and proposes a method for choosing the best asset in order to hedge against extreme fluctuations of energy prices based on the combination of time series. Various copula functions are used to model the dependence structure between oil and different assets (interest rates, bonds and VIX). We investigate whether there are significant changes in the relationships between energy sector and these assets especially for different horizons of investment: the global financial crisis (06/27/2008 to 12/31/2009), the sovereign debt crisis in Europe (01/04/2010 to 12/31/2012) and the post-crisis period (01/02/2013 to 02/24/2016). Results show that TRUS is the best hedge for the energy sector because it presents the highest hedge ratio in most cases. The implied volatility (VIX) provides the second highest hedging ratio indicating the usefulness of a volatility index in hedging oil prices. Second, hedge ratios vary considerably over the sample as a consequence of the change in the dependence structure and the horizon of investment period indicating that hedged positions should be updated regularly.
时变耦合方法的能源投资组合风险管理:债券、利率和波动率的应用
本文利用copulas概念对能源部门(原油)、债券、VIX和利率之间的对冲和避险策略进行了统计建模,并提出了一种基于时间序列组合的最佳资产选择方法,以对冲能源价格的极端波动。我们使用各种联结函数来模拟石油与不同资产(利率、债券和波动率指数)之间的依赖结构,并研究能源部门与这些资产之间的关系是否存在显著变化,特别是在不同的投资时期:全球金融危机(2008年6月27日至2009年12月31日)、欧洲主权债务危机(2010年4月1日至2012年12月31日)和危机后时期(2013年2月1日至2016年2月24日)。结果表明,TRUS在大多数情况下具有最高的对冲比率,是能源板块的最佳对冲工具。隐含波动率(VIX)提供了第二高的对冲比率,表明波动率指数在对冲油价方面的有用性。其次,由于依赖结构的变化和投资周期的变化,对冲比率在样本中变化很大,这表明对冲头寸应定期更新。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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