Volatility in crude oil futures: A comparison of the predictive ability of GARCH and implied volatility models
The WTI future contract quoted at the NYMEX is the most actively traded instrument in the energy sector. This paper compares the predictive ability of two approaches which can be used to forecast volatility: GARCH-type models where forecasts are obtained after estimating time series models, and an implied volatility model where forecasts are obtained by inverting one of the models used to price options. Although the main scope of the research discussed here is to evaluate which model produces the best forecast of volatility for the WTI future contract, evaluated according to statistical and regression-based criteria, we also investigate whether volatility of the oil futures are affected by asymmetric effects, whether parameters of the GARCH models are influenced by the distribution of the errors and whether allowing for a time-varying long-run mean in the volatility produces any improvement on the forecast obtained from GARCH models.
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.:
- Diebold & Lopez, "undated".
"Modeling Volatility Dynamics,"
_062, University of Pennsylvania.
- Neely, Christopher J., 2009.
"Forecasting foreign exchange volatility: Why is implied volatility biased and inefficient? And does it matter?,"
Journal of International Financial Markets, Institutions and Money,
Elsevier, vol. 19(1), pages 188-205, February.
- Christopher J. Neely, 2004. "Forecasting foreign exchange volatility: why is implied volatility biased and inefficient? and does it matter?," Working Papers 2002-017, Federal Reserve Bank of St. Louis.
- West, Kenneth D. & Edison, Hali J. & Cho, Dongchul, 1993.
"A utility-based comparison of some models of exchange rate volatility,"
Journal of International Economics,
Elsevier, vol. 35(1-2), pages 23-45, August.
- Kenneth D. West & Hali J. Edison & Dongchul Cho, 1992. "A Utility Based Comparison of Some Models of Exchange Rate Volatility," NBER Technical Working Papers 0128, National Bureau of Economic Research, Inc.
- Kenneth D. West & Hali J. Edison & Dongchul Cho, 1993. "A utility based comparison of some models of exchange rate volatility," International Finance Discussion Papers 441, Board of Governors of the Federal Reserve System (U.S.).
- Sadorsky, Perry, 2006. "Modeling and forecasting petroleum futures volatility," Energy Economics, Elsevier, vol. 28(4), pages 467-488, July.
- Hull, John C & White, Alan D, 1987. " The Pricing of Options on Assets with Stochastic Volatilities," Journal of Finance, American Finance Association, vol. 42(2), pages 281-300, June.
- Ding, Zhuanxin & Granger, Clive W. J. & Engle, Robert F., 1993. "A long memory property of stock market returns and a new model," Journal of Empirical Finance, Elsevier, vol. 1(1), pages 83-106, June.
- Gibson, Rajna & Schwartz, Eduardo S, 1990. " Stochastic Convenience Yield and the Pricing of Oil Contingent Claims," Journal of Finance, American Finance Association, vol. 45(3), pages 959-976, July.
- Jose A. Lopez, 1995.
"Evaluating the predictive accuracy of volatility models,"
9524, Federal Reserve Bank of New York.
- Lopez, Jose A, 2001. "Evaluating the Predictive Accuracy of Volatility Models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 20(2), pages 87-109, March.
- Barone-Adesi, Giovanni & Whaley, Robert E, 1987. " Efficient Analytic Approximation of American Option Values," Journal of Finance, American Finance Association, vol. 42(2), pages 301-320, June.
- Beckers, Stan, 1981. "Standard deviations implied in option prices as predictors of future stock price variability," Journal of Banking & Finance, Elsevier, vol. 5(3), pages 363-381, September.
- Robert F. Engle & Joshua Rosenberg, 1998.
"Testing the Volatility Term Structure using Option Hedging Criteria,"
New York University, Leonard N. Stern School Finance Department Working Paper Seires
98-031, New York University, Leonard N. Stern School of Business-.
- Robert F. Engle & Joshua Rosenberg, 1966. "Testing the Volatility Term Structure Using Option Hedging Criteria," New York University, Leonard N. Stern School Finance Department Working Paper Seires 96-24, New York University, Leonard N. Stern School of Business-.
- Fong, Wai Mun & See, Kim Hock, 2002. "A Markov switching model of the conditional volatility of crude oil futures prices," Energy Economics, Elsevier, vol. 24(1), pages 71-95, January.
- 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.
- Davidson, Wallace N. & Kim, Jin Kyoung & Ors, Evren & Szakmary, Andrew, 2001. "Using implied volatility on options to measure the relation between asset returns and variability," Journal of Banking & Finance, Elsevier, vol. 25(7), pages 1245-1269, July.
- Awartani, Basel M.A. & Corradi, Valentina, 2005. "Predicting the volatility of the S&P-500 stock index via GARCH models: the role of asymmetries," International Journal of Forecasting, Elsevier, vol. 21(1), pages 167-183.
- Bollerslev, Tim & Chou, Ray Y. & Kroner, Kenneth F., 1992. "ARCH modeling in finance : A review of the theory and empirical evidence," Journal of Econometrics, Elsevier, vol. 52(1-2), pages 5-59.
- Canina, Linda & Figlewski, Stephen, 1993. "The Informational Content of Implied Volatility," Review of Financial Studies, Society for Financial Studies, vol. 6(3), pages 659-681.
- Hentschel, Ludger, 1995. "All in the family Nesting symmetric and asymmetric GARCH models," Journal of Financial Economics, Elsevier, vol. 39(1), pages 71-104, September.
When requesting a correction, please mention this item's handle: RePEc:eee:eneeco:v:31:y:2009:i:2:p:316-321. 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: (Dana Niculescu)
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.