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Correlation used in futures price analysis is a statistical measure of the degree to which movements in two commodities are related. A low correlation coefficient suggests that the relationship between the two commodities is weak or non-existent. A high correlation coefficient indicates that one commodity will most likely change when the other one changes, in the same direction if it is positive and in the opposite direction if the coefficient is negative. |
Correlation can also be used to study the relationships between commodity prices and their indicators. When using this type of analysis, you must realize that the relationship between commodities and their indicator will change over time. As such, the past relationship of two commodities may not necessarily allow you to foretell the future. This concept should be part of any basis in trading your commodity portfolio. For example, two commodities that are negatively correlated with a coefficient of -0.88 are the Swiss Franc and Crude Oil. This is based on weekly data dating back from May 22, 1998 to October 12, 2001. This negative coefficient is not guaranteed since daily correlation coefficients will be different. When using this type of analysis, one must watch these values on a weekly basis as they can sometimes go from a very negative correlation to not being correlated at all within a few short weeks or months. |
Figure 1: Unusual correlations between commodities. |
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What is the purpose for using correlation analysis? Although this type of analysis cannot predict future price movements, it can help eliminate potential losers in your portfolio. For instance, based on the coefficients above, you probably would not want to have a long position in both Feeder Cattle and the Swiss Franc at the same time. Or if you have a short position in Coffee, you might want to look at the British Pound market for potential shorting opportunities as well. |
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