Value-at-risk estimations of energy commodities via long-memory, asymmetry and fat-tailed GARCH models
In this paper, we evaluate the value-at-risk (VaR) and the expected shortfalls for some major crude oil and gas commodities for both short and long trading positions. Classical VaR estimations as well as RiskMetrics and other extensions to cases considering for long-range memory, asymmetry and fat-tail in energy markets volatility were conducted. We computed the VaR for three ARCH/GARCH-type models including FIGARCH, FIAPARCH and HYGARCH. These models were estimated in the presence of three alternative innovation's distributions: normal, Student and skewed Student. Our results show that considering for long-range memory, fat-tails and asymmetry performs better in predicting a one-day-ahead VaR for both short and long trading positions. Moreover, the FIAPARCH model outperforms the other models in the VaR's prediction. These results present several potential implications for energy markets risk quantifications and hedging strategies.
If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Baillie, Richard T. & Bollerslev, Tim & Mikkelsen, Hans Ole, 1996.
"Fractionally integrated generalized autoregressive conditional heteroskedasticity,"
Journal of Econometrics,
Elsevier, vol. 74(1), pages 3-30, September.
- Tom Doan, . "RATS programs to replicate Baillie, Bollerslev, Mikkelson FIGARCH results," Statistical Software Components RTZ00009, Boston College Department of Economics.
- Serletis, Apostolos & Andreadis, Ioannis, 2004. "Random fractal structures in North American energy markets," Energy Economics, Elsevier, vol. 26(3), pages 389-399, May.
- Jacob A. Mincer & Victor Zarnowitz, 1969. "The Evaluation of Economic Forecasts," NBER Chapters, in: Economic Forecasts and Expectations: Analysis of Forecasting Behavior and Performance, pages 3-46 National Bureau of Economic Research, Inc.
- William J. Baumol, 1963. "An Expected Gain-Confidence Limit Criterion for Portfolio Selection," Management Science, INFORMS, vol. 10(1), pages 174-182, October.
- Massimiliano Marzo & Paolo Zagaglia, 2010.
"Volatility forecasting for crude oil futures,"
Applied Economics Letters,
Taylor & Francis Journals, vol. 17(16), pages 1587-1599.
- Marzo, Massimiliano & Zagaglia, Paolo, 2007. "Volatility forecasting for crude oil futures," Research Papers in Economics 2007:9, Stockholm University, Department of Economics.
- M. Marzo & P. Zagaglia, 2007. "Volatility Forecasting for Crude Oil Futures," Working Papers 599, Dipartimento Scienze Economiche, Universita' di Bologna.
- Stavros Degiannakis, 2004. "Volatility forecasting: evidence from a fractional integrated asymmetric power ARCH skewed-t model," Applied Financial Economics, Taylor & Francis Journals, vol. 14(18), pages 1333-1342.
- R.W.J. van den Goorbergh & P.J.G. Vlaar, 1999.
"Value-at-Risk Analysis of Stock Returns Historical Simulation,Variance Techniques or Tail Index Estimation?,"
DNB Staff Reports (discontinued)
40, Netherlands Central Bank.
- R.W.J. van den Goorbergh & P.J.G. Vlaar, 1999. "Value-at-Risk analysis of stock returns: Historical simulation, varinace techniques or tail index estimation ?," WO Research Memoranda (discontinued) 579, Netherlands Central Bank, Research Department.
- Paul H. Kupiec, 1995. "Techniques for verifying the accuracy of risk measurement models," Finance and Economics Discussion Series 95-24, Board of Governors of the Federal Reserve System (U.S.).
- Andrew W. Lo, 1989.
"Long-term Memory in Stock Market Prices,"
NBER Working Papers
2984, National Bureau of Economic Research, Inc.
- Sadeghi, Mehdi & Shavvalpour, Saeed, 2006. "Energy risk management and value at risk modeling," Energy Policy, Elsevier, vol. 34(18), pages 3367-3373, December.
- Christoffersen, Peter F, 1998. "Evaluating Interval Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 841-62, November.
- Tang, Ta-Lun & Shieh, Shwu-Jane, 2006. "Long memory in stock index futures markets: A value-at-risk approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 366(C), pages 437-448.
- Ding, Zhuanxin & Granger, Clive W. J., 1996. "Modeling volatility persistence of speculative returns: A new approach," Journal of Econometrics, Elsevier, vol. 73(1), pages 185-215, July.
- Jarque, Carlos M. & Bera, Anil K., 1980. "Efficient tests for normality, homoscedasticity and serial independence of regression residuals," Economics Letters, Elsevier, vol. 6(3), pages 255-259.
- Hassler, Uwe & Wolters, Jurgen, 1994. "On the power of unit root tests against fractional alternatives," Economics Letters, Elsevier, vol. 45(1), pages 1-5, May.
- Timotheos Angelidis & Alexandros Benos & Stavros Degiannakis, 2007. "A robust VaR model under different time periods and weighting schemes," Review of Quantitative Finance and Accounting, Springer, vol. 28(2), pages 187-201, February.
- Y. K. Tse, 1998. "The conditional heteroscedasticity of the yen-dollar exchange rate," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 13(1), pages 49-55.
- Davidson, James, 2004. "Moment and Memory Properties of Linear Conditional Heteroscedasticity Models, and a New Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 22(1), pages 16-29, January.
- Alvarez-Ramirez, Jose & Cisneros, Myriam & Ibarra-Valdez, Carlos & Soriano, Angel, 2002. "Multifractal Hurst analysis of crude oil prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 313(3), pages 651-670.
- Diebold, Francis X. & Rudebusch, Glenn D., 1991.
"On the power of Dickey-Fuller tests against fractional alternatives,"
Elsevier, vol. 35(2), pages 155-160, February.
- Francis X. Diebold & Glenn D. Rudebusch, 1990. "On the power of Dickey-Fuller tests against fractional alternatives," Finance and Economics Discussion Series 119, Board of Governors of the Federal Reserve System (U.S.).
- Celso Brunetti & Christopher L. Gilbert, 1999.
"Bivariate FIGARCH and Fractional Cointegration,"
408, Queen Mary University of London, School of Economics and Finance.
- David Cabedo, J. & Moya, Ismael, 2003. "Estimating oil price 'Value at Risk' using the historical simulation approach," Energy Economics, Elsevier, vol. 25(3), pages 239-253, May.
- Serena Ng & Pierre Perron, 1997.
"Lag Length Selection and the Construction of Unit Root Tests with Good Size and Power,"
Boston College Working Papers in Economics
369, Boston College Department of Economics, revised 01 Sep 2000.
- Serena Ng & Pierre Perron, 2001. "LAG Length Selection and the Construction of Unit Root Tests with Good Size and Power," Econometrica, Econometric Society, vol. 69(6), pages 1519-1554, November.
- Giraitis, Liudas & Kokoszka, Piotr & Leipus, Remigijus & Teyssiere, Gilles, 2003. "Rescaled variance and related tests for long memory in volatility and levels," Journal of Econometrics, Elsevier, vol. 112(2), pages 265-294, February.
- Jeff Fleming, 2001. "The Economic Value of Volatility Timing," Journal of Finance, American Finance Association, vol. 56(1), pages 329-352, 02.
- Wu, Ping-Tsung & Shieh, Shwu-Jane, 2007. "Value-at-Risk analysis for long-term interest rate futures: Fat-tail and long memory in return innovations," Journal of Empirical Finance, Elsevier, vol. 14(2), pages 248-259, March.
- GIOT, Pierre & LAURENT, SÃ©bastien, 2003.
"Market risk in commodity markets: a VaR approach,"
CORE Discussion Papers
2003028, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Tabak, Benjamin M. & Cajueiro, Daniel O., 2007. "Are the crude oil markets becoming weakly efficient over time? A test for time-varying long-range dependence in prices and volatility," Energy Economics, Elsevier, vol. 29(1), pages 28-36, January.
- Askari, Hossein & Krichene, Noureddine, 2008. "Oil price dynamics (2002-2006)," Energy Economics, Elsevier, vol. 30(5), pages 2134-2153, September.
- So, Mike K.P. & Yu, Philip L.H., 2006. "Empirical analysis of GARCH models in value at risk estimation," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 16(2), pages 180-197, April.
- Ser-Huang Poon & Clive W.J. Granger, 2003. "Forecasting Volatility in Financial Markets: A Review," Journal of Economic Literature, American Economic Association, vol. 41(2), pages 478-539, June.
When requesting a correction, please mention this item's handle: RePEc:eee:enepol:v:38:y:2010:i:5:p:2326-2339. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Zhang, Lei)
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.