Forecasting Nonlinear Crude Oil Future Prices

The Energy Journal, Vol. 27, No. 4, 2006

29 Pages Posted: 23 Sep 2010 Last revised: 5 Oct 2013

See all articles by Saeed Moshiri

Saeed Moshiri

Saint Thomas More College University of Saskatcehwan

Faezeh Foroutan

World Bank

Date Written: September 22, 2006

Abstract

The movements in oil prices are very complex and, therefore, seem to be unpredictable. However, one of the main challenges facing econometric models is to forecast such seemingly unpredictable economic series. Traditional linear structural models have not been promising when used for oil price forecasting. Although linear and nonlinear time series models have performed much better in forecasting oil prices, there is still room for improvement. If the data generating process is nonlinear, applying linear models could result in large forecast errors. Model specification in nonlinear modeling, however, can be very case dependent and time-consuming.

In this paper, we model and forecast daily crude oil futures prices from 1983 to 2003, listed in NYMEX, applying ARIMA and GARCH models. We then test for chaos using embedding dimension, BDS(L), Lyapunov exponent, and neural networks tests. Finally, we set up a nonlinear and flexible ANN model to forecast the series. Since the test results indicate that crude oil futures prices follow a complex nonlinear dynamic process, we expect that the ANN model will improve forecasting accuracy. A comparison of the results of the forecasts among different models confirms that this is indeed the case.

Keywords: Crude oil futures prices, nonlinear dynamic, chaos, BDS, Lyapunov exponent, neural networks, forecasting

JEL Classification: C12, C13, C32, C45, C53

Suggested Citation

Moshiri, Saeed and Foroutan, Faezeh, Forecasting Nonlinear Crude Oil Future Prices (September 22, 2006). The Energy Journal, Vol. 27, No. 4, 2006, Available at SSRN: https://ssrn.com/abstract=1681016

Saeed Moshiri (Contact Author)

Saint Thomas More College University of Saskatcehwan ( email )

1437 College Dr
Saskatoon, Saskatchewan S7N 0W6
Canada

Faezeh Foroutan

World Bank ( email )

1818 H Street, N.W.
Washington, DC 20433
United States

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