Risk Modelling of Energy Futures: A Comparison of RiskMetrics, Historical Simulation, Filtered Historical Simulation, and Quantile Regression
Risk Modelling of Energy Futures: A Comparison of RiskMetrics, Historical Simulation, Filtered Historical Simulation, and Quantile Regression
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能源期货的风险建模：RiskMetrics、历史模拟、过滤历史模拟和分位数回归的比较
DOI：
10.1007/978-3-319-13881-7_31
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发表时间：
2015
期刊：
影响因子：
--
通讯作者：
Sjur Westgaard
中科院分区：
文献类型：
--
作者：
Kai Erik Dahlen;R. Huisman;Sjur Westgaard
能源商品期货的价格通常会随着时间的推移而表现出较高的波动性和收益分布的变化，这使得准确的风险建模既重要又具有挑战性。对于金融资产非常有效的非复杂风险衡量方法在应用于能源商品时表现较差。已经开发出更先进的方法来处理这些问题，但对于从业者来说要么过于复杂，要么由于它们适用于一种商品而不适用于另一种商品而表现不一致。本文的目的是从欧洲能源从业者的角度来检验是否可以找到一些计算风险价值的非估计复杂方法来为不同的能源商品期货提供一致的结果。我们比较了应用于原油、柴油、天然气、煤炭、碳和电力期货的 RiskMetrics™、历史模拟、过滤历史模拟和分位数回归。我们发现，使用指数加权移动平均线 (EWMA) 过滤的历史模拟针对近期趋势和波动性在本文的商品中表现最佳且最一致。
Prices of energy commodity futures often display high volatility and changes in return distribution over time, making accurate risk modelling both important and challenging. Non-complex risk measuring methods that work quite well for financial assets perform worse when applied to energy commodities. More advanced approaches have been developed to deal with these issues, but either are too complex for practitioners or do not perform consistently as they work for one commodity but not for another. The goal of this paper is to examine, from the viewpoint of a European energy practitioner, whether some non-estimation complex methods for calculating Value-at-Risk can be found to provide consistent results for different energy commodity futures. We compare RiskMetrics™, historical simulation, filtered historical simulation and quantile regression applied to crude oil, gas oil, natural gas, coal, carbon and electricity futures.We find that historical simulation filtered with an exponential weighted moving average (EWMA) for recent trends and volatility performs best and most consistent among the commodities in this paper.