A data envelopment analysis-based framework for the relative performance evaluation of competing crude oil prices' volatility forecasting models
Forecasts of crude oil prices' volatility are important inputs to many decision making processes in application areas such as macroeconomic policy making, risk management, options pricing, and portfolio management. Despite the fact that a large number of forecasting models have been designed to forecast crude oil prices' volatility, so far the relative performance evaluation of competing forecasting models remains an exercise that is unidimensional in nature. To be more specific, most studies tend to use several criteria and their measures to assess the relative performance of these models, but competing models are always ranked by performance measure; thus, leading in general to different rankings for different criteria and to a situation where one cannot make an informed decision as to which model performs best with respect to all criteria under consideration. The purpose of this paper is to propose a single ranking that takes account of several criteria using a Data Envelopment Analysis framework. Our empirical results reveal that the unidimensional rankings for different criteria might differ significantly and that the multidimensional ranking of some models could be substantially different from their unidimensional rankings, which highlights the importance of the proposed performance evaluation tool.
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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.:
- Massimiliano Marzo & Paolo Zagaglia, 2010.
"Volatility forecasting for crude oil futures,"
Applied Economics Letters,
Taylor & Francis Journals, vol. 17(16), pages 1587-1599.
- M. Marzo & P. Zagaglia, 2007. "Volatility Forecasting for Crude Oil Futures," Working Papers 599, Dipartimento Scienze Economiche, Universita' di Bologna.
- Marzo, Massimiliano & Zagaglia, Paolo, 2007. "Volatility forecasting for crude oil futures," Research Papers in Economics 2007:9, Stockholm University, Department of Economics.
- Ghysels, E. & Harvey, A. & Renault, E., 1996.
Cahiers de recherche
9613, Universite de Montreal, Departement de sciences economiques.
- GHYSELS, Eric & HARVEY, Andrew & RENAULT, Eric, 1995. "Stochastic Volatility," CORE Discussion Papers 1995069, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Ghysels, E. & Harvey, A. & Renault, E., 1995. "Stochastic Volatility," Papers 95.400, Toulouse - GREMAQ.
- Ghysels, E. & Harvey, A. & Renault, E., 1996. "Stochastic Volatility," Cahiers de recherche 9613, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
- Eric Ghysels & Andrew Harvey & Éric Renault, 1995. "Stochastic Volatility," CIRANO Working Papers 95s-49, CIRANO.
- Lutz Kilian, 2009.
"Not All Oil Price Shocks Are Alike: Disentangling Demand and Supply Shocks in the Crude Oil Market,"
American Economic Review,
American Economic Association, vol. 99(3), pages 1053-69, June.
- Kilian, Lutz, 2006. "Not All Oil Price Shocks Are Alike: Disentangling Demand and Supply Shocks in the Crude Oil Market," CEPR Discussion Papers 5994, C.E.P.R. Discussion Papers.
- Chib, Siddhartha & Nardari, Federico & Shephard, Neil, 2002. "Markov chain Monte Carlo methods for stochastic volatility models," Journal of Econometrics, Elsevier, vol. 108(2), pages 281-316, June.
- Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
- James D. Hamilton, 2009.
"Understanding Crude Oil Prices,"
The Energy Journal,
International Association for Energy Economics, vol. 0(Number 2), pages 179-206.
- Agnolucci, Paolo, 2009. "Volatility in crude oil futures: A comparison of the predictive ability of GARCH and implied volatility models," Energy Economics, Elsevier, vol. 31(2), pages 316-321, March.
- Robert B. Barsky & Lutz Kilian, 2004.
"Oil and the Macroeconomy Since the 1970s,"
Journal of Economic Perspectives,
American Economic Association, vol. 18(4), pages 115-134, Fall.
- 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.
- Pindyck, Robert S, 1991.
"Irreversibility, Uncertainty, and Investment,"
Journal of Economic Literature,
American Economic Association, vol. 29(3), pages 1110-48, September.
- Robert S. Pindyck, 1990. "Irreversibility, Uncertainty, and Investment," NBER Working Papers 3307, National Bureau of Economic Research, Inc.
- Pindyck, Robert S., 1990. "Irreversibility, uncertainty, and investment," Working papers 3137-90., Massachusetts Institute of Technology (MIT), Sloan School of Management.
- Pindyck, Robert, 1989. "Irreversibility, uncertainty, and investment," Policy Research Working Paper Series 294, The World Bank.
- Perry Sadorsky, 2005. "Stochastic volatility forecasting and risk management," Applied Financial Economics, Taylor & Francis Journals, vol. 15(2), pages 121-135.
- Andersen, Torben G & Bollerslev, Tim, 1998. "Answering the Skeptics: Yes, Standard Volatility Models Do Provide Accurate Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 885-905, November.
- Cook, Wade D. & Seiford, Larry M., 2009. "Data envelopment analysis (DEA) - Thirty years on," European Journal of Operational Research, Elsevier, vol. 192(1), pages 1-17, January.
- Sadorsky, Perry, 2006. "Modeling and forecasting petroleum futures volatility," Energy Economics, Elsevier, vol. 28(4), pages 467-488, July.
- Per Andersen & Niels Christian Petersen, 1993. "A Procedure for Ranking Efficient Units in Data Envelopment Analysis," Management Science, INFORMS, vol. 39(10), pages 1261-1264, October.
- Vo, Minh T., 2009. "Regime-switching stochastic volatility: Evidence from the crude oil market," Energy Economics, Elsevier, vol. 31(5), pages 779-788, September.
- Hamilton, James D, 1988. "A Neoclassical Model of Unemployment and the Business Cycle," Journal of Political Economy, University of Chicago Press, vol. 96(3), pages 593-617, June.
- 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.
- Kang, Sang Hoon & Kang, Sang-Mok & Yoon, Seong-Min, 2009. "Forecasting volatility of crude oil markets," Energy Economics, Elsevier, vol. 31(1), pages 119-125, January.
- Kilian, Lutz, 2010. "Oil price volatility: Origins and effects," WTO Staff Working Papers ERSD-2010-02, World Trade Organization (WTO), Economic Research and Statistics Division.
- Donna F. Davis & John T. Mentzer & Teresa M. Mccarthy & Susan L. Golicic, 2006. "The evolution of sales forecasting management: a 20-year longitudinal study of forecasting practices," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(5), pages 303-324.
- Tashman, Leonard J., 2000. "Out-of-sample tests of forecasting accuracy: an analysis and review," International Journal of Forecasting, Elsevier, vol. 16(4), pages 437-450.
- Yokuma, J. Thomas & Armstrong, J. Scott, 1995. "Beyond accuracy: Comparison of criteria used to select forecasting methods," International Journal of Forecasting, Elsevier, vol. 11(4), pages 591-597, December.
- Jan Bentzen, 2007. "Does OPEC influence crude oil prices? Testing for co-movements and causality between regional crude oil prices," Applied Economics, Taylor & Francis Journals, vol. 39(11), pages 1375-1385.
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