The following is an explanation published in a historical edition of the Moore Research Center Report which explains the use of our correlation charts. Any questions regarding these charts can be directed to Research Director Nick Colley or Editor-in-Chief Jerry Toepke.

Of course, one would expect gold and silver futures to move in tandem, to correlate closely, with each other. They're both precious metals, aren't they? But silver is also a by product of copper mining. Would they tend to trade together-or contrarily?

Similarly, one might expect price activity in Euros and T-bonds to be similar. Conversely, the Swiss Franc and the Dollar Index should have opposite reactions to the same market input.

A primary rationale behind the continuing bull market in stocks has been declining interest rates. How closely, in fact, have T-bond and SP500 futures tracked each other on a daily basis?

For years traders have made a very non-fundamental connection between the silver and soybean markets. How closely have they traded?

Heating oil and crude oil-yes. But live cattle and the J-Yen???

Some brief explanation is required. The singular relationship under consideration is the frequency of duplicated up/down daily closings. E.g., if Market A closed higher on Day 1, did also Market B? (In that respect, the study is qualitative, not quantitative, i.e., the amount is irrelevant.)

Without going into further details of least-squares and scatterplots, the precise statistical terminology that describes each relationship is a sample coefficient of correlation, a number greater than -1 and less than +1. Thus, if, every day over the sample period, each of two markets duplicated the other's higher or lower closing, they would have a coefficient of correlation equal to 1/1, or +1. Conversely, two markets that always closed contrarily to each other would have a coefficient equal to -1. A 0 value indicates no correlation whatsoever. For convenience, however, all values in the spread sheet have been stated in terms of percentages of +1 or -1.

Remember, the amount of change is irrelevant, which can account for differences in trend.