Handbook of computational and numerical methods in finance
Handbook of computational and numerical methods in finance
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金融计算和数值方法手册
DOI：
10.1007/978-0-8176-8180-7
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发表时间：
2004
期刊：
影响因子：
--
通讯作者：
S. Rachev
中科院分区：
文献类型：
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作者：
S. Rachev
价格高度波动是世界石油市场的一个长期特点，最近也是天然气和电力市场的一个长期特点。然而，由于能源价格分布的复杂性，对于价格波动的最佳模型和措施是什么，没有广泛接受的答案。能源价格的复杂分布模式和波动集群激发了对能源融资的大量研究。这些研究建议通过纳入随时间变化的条件波动模型或使用随机模型来处理能源价格的非正态性。已经开发了几个Gestro模型，并成功地应用于能源价格建模。他们代表了一个显着的改进模型的无条件正态分布的能量回报。然而，这样的模型可以通过将帕累托稳定分布误差项进一步改进。本文比较了正态Gesterday模型的性能与能量回报的无条件分布模型的统计特性。然后，我们提出了基于稳定分布的误差项的能量Gestival的估计结果，并比较正常的Gestival和稳定的Gestival的性能。
High price volatility is a long-standing characteristic of world oil markets and, more recently, of natural gas and electricity markets. However, there is no widely accepted answer to what the best models and measures of price volatility are because of the complexity of distribution of energy prices. Complex distribution patterns and volatility clustering of energy prices have motivated considerable research in energy finance. Such studies propose dealing with the non-normality of energy prices by incorporating models of time-varying conditional volatility or using stochastic models. Several GARCH models have been developed and successfully applied to modeling energy prices. They represent a significant improvement over models of unconditionally normally distributed energy returns. However, such models may be further improved by incorporating the Pareto stable distributed error term. The article compares the performance of normal GARCH models with the statistical properties of unconditional distribution models of energy returns. We then present the results of estimation of energy GARCH based on the stable distributed error term and compare the performance of normal GARCH and stable GARCH.