Intermarket Analysis

What Is Intermarket Analysis?

Intermarket analysis is a method of analyzing markets by examining the correlations between different asset classes. In other words, what happens in one market could, and probably does, affects other markets, so a study of the relationship(s) could prove to be beneficial to the trader.

Understanding Intermarket Analysis

Intermarket analysis looks at more than one related asset class or financial market to determine the strength, or weakness, of the financial markets, or asset classes, being considered.

For example, when studying the U.S. market, it is worthwhile to look at the U.S. bond market, commodity prices, and the U.S. Dollar. The changes in the related markets, such as commodity prices, may have an impact on the U.S. stock market and would need to be understood to obtain a greater understanding of the future direction of the U.S. stock market.

Intermarket analysis should be considered fundamental analysis in that it relies more on relationships to provide a general sense of direction, but, it is often classified as a branch of technical analysis. There are different approaches to intermarket analysis, including mechanical and rule-based.

Intermarket Analysis Correlations

Performing an analysis of intermarket relationships is relatively simple where one would need data, widely available and free these days, and a spreadsheet or charting program. A simple correlation study is the easiest type of intermarket analysis to perform. This type of analysis is when one variable is compared with a second variable in a separate data set. A positive correlation can go as high as +1.0, which represents a perfect correlation between the two data sets. A perfect inverse (negative) correlation depicts a value as low as -1.0. Readings near the zero line would indicate that there is no discernible correlation between the two samples.

A perfect correlation between any two markets for a very long period of time is rare, 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) is statistically significant. Also, if a correlation moves from positive to negative, the relationship would most likely be unstable, and probably useless for trading.

The most widely accepted correlation is the inverse correlation between stock prices and interest rates, which postulates that as interest rates go up, stock prices go lower, and conversely, as interest rates go down, stock prices go up.