Stable modeling in energy risk management

Zhiguo Zhang, Kei Ichi Shibahara, Bruce Stillman

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

High price volatility in energy markets compels the companies to adopt and implement policies for measurement and management of the energy risk. A popular measure of risk exposure is the Value at Risk (VAR). Traditional methods of estimation of VaR used by major energy companies fail to capture the heavy tails and asymmetry of energy returns distributions. We suggest the use of stable distributions for modeling energy return distributions. The results of our study demonstrate that stable modeling captures asymmetry and heavy-tails of returns, and, therefore, provides more accurate estimates of energy VaR.

Original languageEnglish (US)
Pages (from-to)225-245
Number of pages21
JournalMathematical Methods of Operations Research
Volume55
Issue number2
DOIs
StatePublished - Jan 1 2002
Externally publishedYes

Fingerprint

Energy Management
Risk Management
Risk management
Energy
Modeling
Heavy Tails
Asymmetry
Industry
Stable Distribution
Value at Risk
Volatility
Estimate
Demonstrate
Heavy tails
Return distribution

Keywords

  • Energy risk management
  • Modeling
  • Stable distributions
  • Value at Risk

ASJC Scopus subject areas

  • Software
  • Mathematics(all)
  • Management Science and Operations Research

Cite this

Stable modeling in energy risk management. / Zhang, Zhiguo; Shibahara, Kei Ichi; Stillman, Bruce.

In: Mathematical Methods of Operations Research, Vol. 55, No. 2, 01.01.2002, p. 225-245.

Research output: Contribution to journalArticle

Zhang, Zhiguo ; Shibahara, Kei Ichi ; Stillman, Bruce. / Stable modeling in energy risk management. In: Mathematical Methods of Operations Research. 2002 ; Vol. 55, No. 2. pp. 225-245.
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