Correlation Analysis

  • Nigel Da Costa Lewis
Part of the Finance and Capital Markets Series book series (FCMS)


To this point, we have dealt almost exclusively with problems of estimation and statistical inference about a parameter of a probability distribution or characteristic of a sample. Another important element of applied statistical modeling of energy risks concerns the relationship between two or more price or other variables. Generally, a risk manager will be interested in whether above (below) average values of one variable tend to be associated with above (below) average values of the other variable. Take for example, a risk manger working for a petroleum refinery, who for hedging purposes, is interested in knowing the relationship between the spot price of Brent Crude and the future price of diesel fuel. If the risk manager simply assumes crude oil and diesel fuel prices always move in tandem, the company will be exposed to the price risk if this relationship breaks down. If on the other hand, the closeness of the two indices is defined in terms of a correlation coefficient, then the manager at least has some rudimentary way of assessing whether or not the relationship exists and its strength.


Future Price Spot Price Gross National Product Time Series Plot Price Risk 
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Further Reading

  1. Albers, W. (1999) “Stop-loss premiums under dependence,” Insurance: Mathematics and Economics, 24, 173–85.Google Scholar
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  3. Bullimore J. (2000) “Jet Fuel Price Risk Management,” Swiss Derivatives Review, Autumn, 16, 20.Google Scholar
  4. Co, T. (2000) “High Prices Fuel Airlines’ Anxiety,” Asia Risk, November, Special 5th Anniversary Issue, 6.Google Scholar
  5. Considine, T. J. and Heo, E. (2000) “Price and Inventory Dynamics in Petroleum Product Markets,” Energy Economics, 22, 527–47.CrossRefGoogle Scholar
  6. Dale, C. (1981) “The Hedging Effectiveness of Currency Futures Markets,” The Journal of Futures Markets, 1(1) 77–88.CrossRefGoogle Scholar
  7. Ederington, L. H. (1979) “The Hedging Performance of the New Futures Market,” The Journal of Finance, 34(1) 157–70.CrossRefGoogle Scholar
  8. Galambos, J. (1987) The Asymptotic Theory of Extreme Order Statistics, Kreiger Publishing Co., Melbourne, FL.Google Scholar
  9. Harlow, W. (1991) “Asset Allocation in a Downside-risk Framework,” Financial Analysts Journal, 47(5) 28–40.CrossRefGoogle Scholar
  10. Horsewood, R. (1997), R. (1997) “Options and Oils,” Asia Risk, August 1997.Google Scholar
  11. Johnson, L. L. (1960) “The Theory of Hedging and Speculation in Commodity Futures,” Review of Economic Studies, 27(3) 139–51.CrossRefGoogle Scholar
  12. Joe, H. (1997) “Multivariate Models and Dependence Concepts”, Chapman & Hall, London.CrossRefGoogle Scholar
  13. Lewis, Nigel Da Costa (2004) Operational Risk with Excel and VBA: Applied Statistical Methods for Risk Management, John Wiley & Sons, Inc., New York.Google Scholar

Copyright information

© Nigel Da Costa Lewis 2005

Authors and Affiliations

  • Nigel Da Costa Lewis

There are no affiliations available

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