Volatility forecasting for crude oil futures

Arbeitspapier

This paper studies the forecasting properties of linear GARCH models for closing-day futures prices on crude oil, first position, traded in the New York Mercantile Exchange from January 1995 to November 2005. In order to account for fat tails in the empirical distribution of the series, we compare models based on the normal, Student's t and Generalized Exponential distribution. We focus on out-of-sample predictability by ranking the models according to a large array of statistical loss functions. The results from the tests for predictive ability show that the GARCH-G model fares best for short horizons from one to three days ahead. For horizons from one week ahead, no superior model can be identified. We also consider out-ofsample loss functions based on Value-at-Risk that mimic portfolio managers and regulators' preferences. EGARCH models display the best performance in this case.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: Quaderni - Working Paper DSE ; No. 598

Classification and Topics

• Classification: Wirtschaft
• Subject: Ölpreis ; Derivat ; ARCH-Modell

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Marzo, Massimiliano ; Zagaglia, Paolo
• Event: Veröffentlichung
• (who): Alma Mater Studiorum - Università di Bologna, Dipartimento di Scienze Economiche (DSE)
• (where): Bologna
• (when): 2007

Further information

• DOI: doi:10.6092/unibo/amsacta/4684
• Handle: http://hdl.handle.net/10419/159439
• Last update: 10.03.2025, 11:41 AM CET