ARCO1: An Application of Belief Networks to the Oil Market

TL;DR

ARCO1 employs belief networks to model and forecast crude oil prices, integrating expert consensus and Monte Carlo analysis for flexible, rapid updates in financial forecasting.

Contribution

This paper presents the development of ARCO1, the most advanced belief network application in financial forecasting, specifically for crude oil market prediction.

Findings

Effective modeling of oil market variables

Flexible updating of the belief network

Accurate crude oil price forecasts

Abstract

Belief networks are a new, potentially important, class of knowledge-based models. ARCO1, currently under development at the Atlantic Richfield Company (ARCO) and the University of Southern California (USC), is the most advanced reported implementation of these models in a financial forecasting setting. ARCO1's underlying belief network models the variables believed to have an impact on the crude oil market. A pictorial market model-developed on a MAC II- facilitates consensus among the members of the forecasting team. The system forecasts crude oil prices via Monte Carlo analyses of the network. Several different models of the oil market have been developed; the system's ability to be updated quickly highlights its flexibility.