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

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.

Keywords:

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