.png){kind=icon}
返回
Gas storage valuation under multifactor Levy processes
.png){kind=icon}
OA
AI
DOI：10.1016/j.jbankfin.2018.02.012.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
A practical problem for energy companies is instituting a consistent framework across its supply and trading activities to deliver on all-important P&L and at-Risk reporting requirements. With a focus on storage assets and wider natural gas market exposures, we present a gas storage valuation methodology, which uniquely uses a flexible multifactor Levy process setting that allows for consistent valuation and risk management reporting across a general derivative book. Our approach is capable of replicating the complex covariance structure of the natural gas forward curve and capturing time spread volatility, a key driver of extrinsic storage value, while being simultaneously capable of accurately calibrating to market traded options. We begin by extending a single factor Mean Reverting Variance Gamma process to an arbitrary number of dimensions and, by way of specific examples, show how the traditional Principal Component Analysis based view of gas forward curve dynamics can be incorporated into a primarily market based valuation. We develop in the process an innovative implied moments based calibration technique, which allows for efficient calibration of general multifactor forward curve models to delivery period options common in energy and commodity markets. Furthermore, to accommodate the forward curve and traded options market consistency, we propose an appropriate joint market based calibration and historical estimation methodology. Through a formal model specification analysis, we provide evidence that the multifactor Levy models we propose provide a better joint fit to NBP natural gas options-forward market data, relative to comparative benchmark models. Finally, we develop a novel multidimensional fast Fourier transform based storage valuation algorithm and provide empirical evidence that the multifactor Levy model suite is better specified to more accurately capture extrinsic value. (C) 2018 Elsevier B.V. All rights reserved.
Keyword:
Gas storage valuation
Multifactor Levy processes
Mean reverting variance gamma processes
Implied moments calibration
Fast fourier transform
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
J
IF:
3.8
论文数:
6.4K
被引数:
2.4W
机构
引用论文
Risk factors for renal impairment revealed after unilateral adrenalectomy in patients with primary aldosteronism.png)
MedicineOAAI
MedicineIF0
OAAI分享收藏The Morphology, Taxonomy, and Sexuality of the Rice Stem Rot Fungus, Magnaporthe Salvinii (Leptosphaeria Salvinii)Mycologia
MycologiaIF0
PREAI
分享收藏
Protection against pneumococcal infection elicited by immunization with glutamyl tRNA synthetase, polyamine transport protein D and sortase AVaccine
VaccineIF0
PREAI
分享收藏
查看更多内容