Speculative trading strategy of buying crude oil for refinery on spot market

TLDR: In this paper, an Artificial Neural Network (ANN) was designed as a part of Decision Support System (DSS) and an innovative approach was applied in modelling the ANN to assure convenience yield and speculative gain by reducing the cost of crude oil.

Abstract: This paper examines buying of the crude oil for a refinery on spot market based on a speculative trading strategy. The goal is to assure convenience yield and speculative gain by reducing the cost of crude oil. An Artificial Neural Network (ANN) was designed as a part of Decision Support System (DSS). Because of difficulties in forecasting the crude oil spot price, an innovative approach was applied in modelling the ANN. ANN output variables are not future spot prices, but decisions that represent small, mid or large quantity of crude oil to be bought. The ANN was trained on decisions during the five years time period (1995-2000) and was validated during the three years time period (2001-2003). Input variables to the ANN were heuristically derived from the historical spot prices of crude oil. About 3 % speculative gain has been obtained. Designed methodology presented in this work could be implemented on any application where the energy or raw material is being bought on spot market in order to be stored for consuming within a short time period of up to 3 months.