Estimating Risk of Natural Gas Portfolios by Using GARCH-EVT-Copula Model

This paper concentrates on estimating the risk of Title Transfer Facility (TTF) Hub natural gas portfolios by using the GARCH-EVT-copula model. We first use the univariate ARMA-GARCH model to model each natural gas return series. Second, the extreme value distribution (EVT) is fitted to the tails of...

Full description

Saved in:
Bibliographic Details
Published in:TheScientificWorld 2015, Vol.2015 (2015), p.1-7
Main Authors: Sriboonchitta, Songsak, Yuan, Xinyu, Zhou, Chao, Tang, Jiechen
Format: Article
Language:English
Subjects:
Commodities
Crude oil
Crude oil prices
Evaluation
Financial risk
Forecasts and trends
Futures
Gases
Investments
Methods
Natural gas
Natural gas prices
Prices and rates
Risk assessment
Stochastic models
Studies
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This paper concentrates on estimating the risk of Title Transfer Facility (TTF) Hub natural gas portfolios by using the GARCH-EVT-copula model. We first use the univariate ARMA-GARCH model to model each natural gas return series. Second, the extreme value distribution (EVT) is fitted to the tails of the residuals to model marginal residual distributions. Third, multivariate Gaussian copula and Student t-copula are employed to describe the natural gas portfolio risk dependence structure. Finally, we simulate N portfolios and estimate value at risk (VaR) and conditional value at risk (CVaR). Our empirical results show that, for an equally weighted portfolio of five natural gases, the VaR and CVaR values obtained from the Student t-copula are larger than those obtained from the Gaussian copula. Moreover, when minimizing the portfolio risk, the optimal natural gas portfolio weights are found to be similar across the multivariate Gaussian copula and Student t-copula and different confidence levels.
ISSN:2356-6140
1537-744X
1537-744X
DOI:10.1155/2015/125958