Skip to main content

2015 | OriginalPaper | Buchkapitel

53. Evaluating the Performance of VaR Models in Energy Markets

verfasst von : Saša Žiković, Rafał Weron, Ivana Tomas Žiković

Erschienen in: Stochastic Models, Statistics and Their Applications

Verlag: Springer International Publishing

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

We analyze the relative performance of 13 VaR models using daily returns of WTI, Brent, natural gas and heating oil one-month futures contracts. After obtaining VaR estimates we evaluate the statistical significance of the differences in performance of the analyzed VaR models. We employ the simulation-based methodology proposed by Žiković and Filer in Czech J Econ Finan 63(4):327–359, 2013, which allows us to rank competing VaR models. Somewhat surprisingly, the obtained results indicate that for a large number of different VaR models there is no statistical difference in their performance, as measured by the Lopez size adjusted score. However, filtered historical simulation (FHS) and the BRW model stand out as robust and consistent approaches that – in most cases – significantly outperform the remaining VaR models.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Literatur
1.
Zurück zum Zitat Agnolucci P (2009) Volatility in crude oil futures: a comparison of the predictive ability of GARCH and implied volatility models. Energy Econ 31:316–321 CrossRefMATH Agnolucci P (2009) Volatility in crude oil futures: a comparison of the predictive ability of GARCH and implied volatility models. Energy Econ 31:316–321 CrossRefMATH
2.
Zurück zum Zitat Aloui C (2008) Value-at-risk analysis for energy commodities: long-range dependencies and fat tails in return innovations. J Energy Mark 1(1):31–63 MathSciNet Aloui C (2008) Value-at-risk analysis for energy commodities: long-range dependencies and fat tails in return innovations. J Energy Mark 1(1):31–63 MathSciNet
5.
Zurück zum Zitat Danielsson J, de Vries C (1997) Tail index and quantile estimation with very high frequency data. J Empir Finance 4:241–257 CrossRef Danielsson J, de Vries C (1997) Tail index and quantile estimation with very high frequency data. J Empir Finance 4:241–257 CrossRef
6.
Zurück zum Zitat Diebold FX, Mariano R (1995) Comparing predictive accuracy. J Bus Econ Stat 13:253–263 Diebold FX, Mariano R (1995) Comparing predictive accuracy. J Bus Econ Stat 13:253–263
7.
Zurück zum Zitat Giot P, Laurent S (2003) Market risk in commodity markets: a VaR approach. Energy Econ 25:435–457 CrossRef Giot P, Laurent S (2003) Market risk in commodity markets: a VaR approach. Energy Econ 25:435–457 CrossRef
8.
Zurück zum Zitat Hansen PR (2005) A test for superior predictive ability. J Bus Econ Stat 23(4):365–380 CrossRef Hansen PR (2005) A test for superior predictive ability. J Bus Econ Stat 23(4):365–380 CrossRef
9.
Zurück zum Zitat Hollander M, Wolfe DA (1999) Nonparametric statistical methods. Wiley, Hoboken MATH Hollander M, Wolfe DA (1999) Nonparametric statistical methods. Wiley, Hoboken MATH
10.
Zurück zum Zitat Hung JC, Lee MC, Liu HC (2008) Estimation of value-at-risk for energy commodities via fat-tailed GARCH models. Energy Econ 30(3):1173–1191 CrossRef Hung JC, Lee MC, Liu HC (2008) Estimation of value-at-risk for energy commodities via fat-tailed GARCH models. Energy Econ 30(3):1173–1191 CrossRef
11.
Zurück zum Zitat Kupiec P (1995) Techniques for verifying the accuracy of risk management models. J Deriv 3:73–84 CrossRef Kupiec P (1995) Techniques for verifying the accuracy of risk management models. J Deriv 3:73–84 CrossRef
12.
Zurück zum Zitat Lopez AJ (1999) Methods for evaluating value-at-risk estimates. Econ Policy Rev (Federal Reserve Bank of New York) 2:3–17 Lopez AJ (1999) Methods for evaluating value-at-risk estimates. Econ Policy Rev (Federal Reserve Bank of New York) 2:3–17
13.
Zurück zum Zitat Mabrouk S (2011) Value-at-risk and expected shortfall estimations based on GARCH-type models: evidence from energy commodities. J Energy Dev 35:279–314 Mabrouk S (2011) Value-at-risk and expected shortfall estimations based on GARCH-type models: evidence from energy commodities. J Energy Dev 35:279–314
14.
Zurück zum Zitat Marimoutou V, Raggad B, Trabelsi A (2009) Extreme value theory and value at risk: application to oil market. Energy Econ 31:519–530 CrossRef Marimoutou V, Raggad B, Trabelsi A (2009) Extreme value theory and value at risk: application to oil market. Energy Econ 31:519–530 CrossRef
15.
Zurück zum Zitat McNeil AJ, Frey R (2000) Estimation of tail-related risk measures for heteroscedastic financial time series: an extreme value approach. J Empir Finance 7:271–300 CrossRef McNeil AJ, Frey R (2000) Estimation of tail-related risk measures for heteroscedastic financial time series: an extreme value approach. J Empir Finance 7:271–300 CrossRef
16.
Zurück zum Zitat Mohammadi H, Su L (2010) International evidence on crude oil price dynamics: applications of ARIMA-GARCH models. Energy Econ 32(5):1001–1008 CrossRef Mohammadi H, Su L (2010) International evidence on crude oil price dynamics: applications of ARIMA-GARCH models. Energy Econ 32(5):1001–1008 CrossRef
17.
Zurück zum Zitat Wei Y, Wang Y, Huang D (2010) Forecasting crude oil market volatility: further evidence using GARCH-class models. Energy Econ 32(6):1477–1484 CrossRef Wei Y, Wang Y, Huang D (2010) Forecasting crude oil market volatility: further evidence using GARCH-class models. Energy Econ 32(6):1477–1484 CrossRef
19.
Zurück zum Zitat Weron R (2014) Electricity price forecasting: a review of the state-of-the-art with a look into the future. Int J Forecast 30(4):1030–1081 CrossRef Weron R (2014) Electricity price forecasting: a review of the state-of-the-art with a look into the future. Int J Forecast 30(4):1030–1081 CrossRef
21.
Zurück zum Zitat Žiković S, Filer RK (2013) Ranking of VaR and ES models: performance in developed and emerging markets. Czech J Econ Finan 63(4):327–359 Žiković S, Filer RK (2013) Ranking of VaR and ES models: performance in developed and emerging markets. Czech J Econ Finan 63(4):327–359
22.
Zurück zum Zitat Žiković S, Vlahinić-Dizdarević N (2011) Similarities between expected shortfall and value at risk: application to energy markets. Int J Manag Cases 13(3):386–399 CrossRef Žiković S, Vlahinić-Dizdarević N (2011) Similarities between expected shortfall and value at risk: application to energy markets. Int J Manag Cases 13(3):386–399 CrossRef
Metadaten
Titel
Evaluating the Performance of VaR Models in Energy Markets
verfasst von
Saša Žiković
Rafał Weron
Ivana Tomas Žiković
Copyright-Jahr
2015
DOI
https://doi.org/10.1007/978-3-319-13881-7_53