Oil companies and industry consultants alike have for years used specific models in their pricing analysis for the price differentials between crudes produced worldwide and “marker” crudes such as the Brent or WTI. But, as more developing countries contribute to the overall oil market, current models need to be improved to include characteristics such as acidity or any other factors affecting the final price. A mere focus on the statistical analysis of specific gravity or sulphur content is no longer adequate. Total Acid Number (TAN) now plays a role in pricing varying according to the level of acidity. So far, the method has consisted of a simple pair wise comparison of crudes identical in every major aspects of quality except the one being investigated. The introduction of regression model now permits the simultaneous incorporation of all quality differences. Considering first that the effects of a one-unit difference in quality remain the same regardless of the crudes being considered and second that the effects of differences in several measures of quality are additive.

Then, the discount effect can be expressed by:

Δprice = a + ∑ i bi (Δqualityi)

with Δprice= difference in price between a crude X and a “marker” crude.

Δqualityi = difference in quality I between that crude X and the “marker” crude.

∑ = sum of the qualities

a, bi are parameters to be established by regression analysis where b measures the effect on the price differential of a one-unit increase in the difference in each dimension of quality between the crude in question and the marker crude.

Our analysts are able to estimate in an innovative way the model for crudes with data available on both quality specifications and spot prices.