Modeling Uncertainty of Iran's Oil by Mean Reverting Stochastic Process

Uncertainty is different from risk. When a variable is having uncertainty, as oil prices where unique characteristics are expected, risk analysis can not explain the behavior of that variable. Stochastic differential equations are able to model the behavior of such variables. Mean reverting stochastic process is a kind of stochastic differential equation which is assumed to have the variable fluctuating in the proximity of its long run average. In this paper, we measure a proxy of uncertainty for Iran's heavy oil prices by mean reverting stochastic process in the period of 1985-2009. The results indicate that the most uncertainties were in 2005, 2006 and 2007 and the least were in 1985, 1986 and 1998.