Executive Summary

In deciding on investment options in the highly variable energy market, a keen understanding of the direction of oil price futures is essential. We have attempted to create a model that will explain the variables that impact oil price. Understanding the variables will allow us to profit from select investments in the sectors that drive the price of oil.

In constructing the model, we began with nine variables that we suspected had an affect on world oil price. Those variables are the following: OECD oil demand, OPEC oil supply, non-OPEC oil supply, OECD world petroleum inventory, ExxonMobil stock price, British Petroleum (BP) stock price, S&P 500 index, U.S. 10-year Treasury note and U.S. Consumer Price Index (CPI). We took monthly data figures from January 2001 through October 2005. With this information, we ran a regression to determine if these nine variables had an effect on oil price ( Output 1) . Our analysis determined that four of the nine variables are statistically significant in determining the price of oil. These four variables, OPEC supply, non-OPEC supply, BP and CPI were then used to construct our final predictive model ( Output 2) . From our final model, we formed a null hypothesis stating that the variables we chose do not affect the price of oil. Therefore, our alternative hypothesis is that the selected variables do have an effect on the price of oil.

Statistical Analysis

While we are confident that our selected variables have the predictive capability of explaining some of the causes of world oil prices, there is a benefit to understanding the theoretical predictive capability of all nine variables. The following is an explanation of how our variables influence the price of oil.

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