A METHODOLOGY FOR THE CHOICE OF THE BEST FITTING CONTINUOUS-TIME STOCHASTIC MODELS OF CRUDE OIL PRICE THE CASE OF IRAN))
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Abstract
This study, it has been attempted to select the best continuous- time stochastic model, in order to describe and forecast the oil price of Iran, by information and statistics about oil price that has been available for oil price in the past. For this purpose, method of The Maximum Likelihood Estimation is implemented for estimation of the parameters of continuous-time stochastic processes. The result of unit root test with a structural break, reveals that time series of the crude oil price is a stationary series. The simulation of continuous-time stochastic processes and the mean square error between the simulated prices and the market ones shows that the Geometric Brownian Motion is the best model for the Iranian crude oil price.
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