论文标题
电力期货的尾巴风险
Tail Risk of Electricity Futures
论文作者
论文摘要
本文比较了几种模型的样本外部和样本外观，用于计算2008 - 2017年在Nordpool，French，French，German和Spanish Markets交易的一个月和一年电力期货合约的尾巴风险。作为尾巴风险的度量，我们使用一日临界价（VAR）和预期的短缺（ES）。使用VAR，具有学生-T分布的AR（1）-Garch（1,1）模型是表现最佳的规范，其中Fisher测试接受该模型的情况为88％，左尾的成功率为94％，右尾部为81％。该模型通过了北浦和德国市场的100％案件的模型充分性测试，但仅在西班牙和法国市场的88％和63％的案件中。使用ES，该模型通过100％的所有市场中的100％案件进行了模型充足性的测试。历史模拟和基于分位数回归的方法误会了尾巴风险。回报的右尾比左尾更难建模，因此，在设定额外的监管资本要求和保证金帐户法规时，财务监管机构和期货市场管理员应考虑这些结果。
This paper compares the in-sample and out-of-sample performance of several models for computing the tail risk of one-month and one-year electricity futures contracts traded in the NordPool, French, German, and Spanish markets in 2008-2017. As measures of tail risk, we use the one-day-ahead Value-at-Risk (VaR) and the Expected Shortfall (ES). With VaR, the AR (1)-GARCH (1,1) model with Student-t distribution is the best-performing specification with 88% cases in which the Fisher test accepts the model, with a success rate of 94% in the left tail and of 81% in the right tail. The model passes the test of model adequacy in the 100% of the cases in the NordPool and German markets, but only in the 88% and 63% of the cases in the Spanish and French markets. With ES, this model passes the test of model adequacy in 100% of cases in all markets. Historical Simulation and Quantile Regression-based approaches misestimate tail risks. The right-hand tail of the returns is more difficult to model than the left-hand tail and therefore financial regulators and the administrators of futures markets should take these results into account when setting additional regulatory capital requirements and margin account regulations to short positions.
