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Crude Oil Mispricing model

SKU 00050
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About the course

The Crude Oil Mispricing Model assesses what the price of crude oil should have been if the historical relationship between crude oil and a given commodity were to have continued into the future. Vice versa, what would the price of a given commodity be if the average correlation between crude oil and a given commodity was maintained over the analysis period?

It provides a comparative study of the average-correlation-simulated time series against the actual time series over the period January 2008 to August 2011 to assess whether the price levels were justified or whether there was an argument for commodity mispricing.

The EXCEL file includes the following:

  • Historical average correlations between commodity spot prices. Commodities include crude oil, gold, fuel oil, diesel fuel, natural gas, silver, platinum, aluminum, steel, copper, cotton, corn, wheat, coffee, sugar, corn oil and soybean oil.
  • Trailing correlations based on the actual price time series data along with graphical representations.
  • Reworked commodity prices based on 60-day trailing moving average correlations using least squares analysis and Excel’s Solver Function. Using Excel’s Solver Function we minimize the sum of squared differences between each of these 60-day correlations (trailing correlations) and the historical average correlation calculated earlier by changing the prices of a given commodity. For example if we are looking at the relationship between WTI and Corn Oil, we first keep WTI prices as actual prices and change Corn Oil prices for the mentioned period so that each 60-day trailing correlation for the period is equal to the historical average. Next we keep Corn Oil Prices as the actual prices and change the WTI prices for the mentioned period so that each 60-day trailing correlation for the period is equal to the historical average.
  • Relative price ratios (i.e. “What can 1 barrel of crude oil buy?” “What can 1 ounce of gold buy?”) for crude oil and gold against each commodity, based on actual and simulated prices.
  • Graphical representation of actual and assumed prices and relative price ratios.

    Learning objectives

    After taking this course you will be able to:

    • Calculate average and trailing correlations between commodity spot prices
    • Simulate an assumed spot price time series based on historical average correlations
    • Plot the actual and simulated price series to assess either expected trends or the possibility of mispricing or systematic changes


    Some familiarity with basic mathematics and EXCEL.

    Target audience

    This course is for beginners in the finance field as well as individuals assessing opportunities and risk in treasury and risk management teams within banks, insurance companies, mutual funds and finance departments of non-financial organizations.

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