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Oil Price Volatility Modeling and a Proper Measure fo Quality of Prediction  Fulltext 

[ Amir Hossien Khalilzadeh ] - MSc in Pure Statistics, Petroleum Ministry Fifth Building, No. 175, Taleghani Ave., Tehran, Iran. Corresponding address
[ Carol Dahl ] - Faculty Member of Golden School of Mines, Division of Economic and Business, Colorado University, Dir CSM/IFP Petroleum Economics and Management, USA.
[ Hojatollah Ghanimi fard ] - Faculty Member of Petroleum University of Technology, Head of N.I.O.C. International Affairs, Tehran, Iran.

خلاصه مقاله:

In this paper we try to model oil price volatility using the well-known ARCH/GA models. We focus on volatility of the spot prices of WTI crude oil, over the period 2 Jan 1986 to 27 July 2005 representing 5386 observations. The preferred model is a ARMA GARCH (1,1) model with student’s t-errors distribution. Special emphasis is given o problem of volatility prediction and the issue of a proper measure for the quality of predi In order to compare the different predictors of squared returns, we will use two po performance measures: Mean Squared Error (MSE) of prediction and Mean Ab Deviation (MAD) of prediction. So an optimal predictor is formulated, and the usefuln the new predictor is demonstrated on a real dataset.

ARCH models, oil price volatility, volatility prediction, mean absolute error, squared error.