Beschreibung
Crude oil is the commodity de jour and its pricing is of paramount importance to the layperson as well as to any responsible government. However, one of the main challenges facing econometric pricing models is the forecasting accuracy. Historically, linear and non-linear time series models were used. Although, a great success was achieved in that regard, yet there were no definite and universal conclusions drawn. The crude oil forecasting field is still wide open for improvement, especially when applying different forecasting models and alternative techniques. Toward this end, the proposed research implemented Artificial Neural Network models (ANN). The models will forecast the daily crude oil futures prices from 1996 to 2006, listed in NYMEX. Due to the nonlinearity presented by the test results of the crude oil pricing, it is expected that the ANN models will improve forecasting accuracy. An evaluation of the outcomes of the forecasts among different models was done to authenticate that this is undeniably the situation.
Autorenporträt
I was born in Lebanon about half a century ago. Pursued undergraduate studies in engineering in France, followed by Masters degree in engineering then an MBA with concentration in Finance. Received a PhD in finance from NOVA Southeastern University where I have been teaching. I also lecture at other national/international universities in finance.
Herstellerkennzeichnung:
BoD - Books on Demand
In de Tarpen 42
22848 Norderstedt
DE
E-Mail: info@bod.de
