Intermarket analysis

Intermarket analysis is a relationship, or a measurable correlation between certain markets. It is a form of fundamental analysis, without a time delay. Supporters of intermarket analysis state that it can be done by applying the statistical methods like correlation. Critics of intermarket analysis refute statistical methods and use only price indicators for fundamental analysis.

In John Murphy's first book, published in 1991 on Intermarket analysis he used the crash of 1987 to lay out his Intermarket hypothesis. Murray Ruggiero published Intermarket based trading systems in 1994.

Hence, intermarket market analysis can be thought of as a type of instantaneous fundamental analysis and is not really meant to work on a tick by tick basis. It gives you a general bias and direction. Thus, your intermarket work looks for times that these underlying relationships are moving opposite to the market you are trading.

There are many approaches to intermarket analysis like mechanical, rule based (while not mechanical via a different angle). One can use intermarket analysis of Oil along with the intermarket analysis of other key markets to help with profitable day trading of the Russell 2000 Emini ER2.

There are many supporters and detractors for this theory and the points to consider regarding the Intermarket Relationship have been clarified in the following sections.

1) They are tried and time-tested intermarket relationships with easily available free data and a simple spreadsheet or charting program. The quickest function to use is the simple correlation study, wherein one variable is compared with a second variable i.e. the correlation between two data series.

If it is positive; the correlation value shall go as high as + 1.0 – representing a perfect and positive correlation between the two series of prices. Moreover, a perfect inverse (negative) correlation depicts a value as low as - 1.0. Readings near the zero line would show no discernible correlation between the two samples.

Moreover, it is rare to have a perfect correlation between any two market for a very long period of time, but most analysts would probably agree that any reading sustained over the +0.7 or under the –0.7 level (which would equate to approximately a 70% correlation) would be statistically significant. Also, if the correlation value went from a positive to a negative correlation frequently, the relationship would most likely be unstable, and probably useless for trading.

...
Wikipedia