Intermarket analysis involves the analysis of more than one related class of assets – such as stocks, bonds, commodities, and currencies. The analysis is done to help determine the strength or weakness of the asset class being considered. The concept was first introduced by John Murphy, a financial market analyst, in his book, “Trading with Intermarket Analysis.”
According to Murphy, traders can benefit from looking at relationships between different classes of assets. Intermarket analysis can help investors identify the stage of the investing cycle, along with best-performing and worst-performing asset classes.
Breaking Down Intermarket Analysis
Intermarket analysis involves looking at asset classes or financial markets that have strong correlations. For example, when analyzing the US stock market, an investor can look at related markets such as the US dollar, commodity prices, and the bond market. Commodity prices often have a direct effect on the US stock market. Therefore, analysis of commodities and stocks together may be used to help predict the future direction of the stock market.
Intermarket Analysis Correlation
Analyzing the intermarket relationships between two or more variables is usually possible with available data, chart comparisons, or a spreadsheet. Most investors/traders use correlations to analyze the intermarket relationship between one variable and a second variable in a different data set. The degree of correlation between the variables indicates the strength of the relationship.
1. Positive correlation
A correlation study of two variables can either yield a positive or negative correlation. Positive correlation means the two variables tend to move in tandem. The correlation reading can go as high as +1.0, which would be perfect positive correlation. In the investing world, this would mean that two assets or asset classes move in lock-step with each other. Obviously, perfect correlation is very rare.
Any reading between +0.7 to +1.0, sustained for a long period of time, indicates that the two variables are statistically significant to each other. Identifying such relationships through intermarket analysis can be very helpful to investors in making buy/sell decisions.
2. Negative/Inverse correlation
On the other hand, a negative correlation, also known as inverse correlation, shows a negative relationship between two variables. Negative correlation values can go as low as -1.0. A sustained correlation between -0.7 to -1.0 indicates a statistically significant relationship. With negative correlations, it’s important to keep in mind that the variables will move inversely to one another.
When the relationship is close to the zero point, it indicates that the relationship between the two variables is weak. If the relationship moves from positive to negative (and vice-versa), it shows that the relationship between the two variables is unstable, and cannot be relied upon to provide trading direction. Essentially, there is no reliable correlation between the variables.
Inflationary and Deflationary Relationships
Two of the main factors influencing intermarket analysis and relationships are inflationary and deflationary forces. The most clearly defined intermarket relationships affected by inflation/deflation include bonds and commodities, stocks and bonds, and commodities and the US dollar.
1. Inflationary relationships
In an inflationary environment, there is a usually a positive correlation between stocks and bonds. When the value of one asset rises, the other asset follows suit. Typically, bonds change direction before stocks, so a reversal in the direction of bond prices may indicate that stock prices may change trend in the near future.
Further, during inflation, there is typically an inverse relationship between the US dollar and commodities, and between bonds and commodities. When one asset class rises in price, the other asset class declines.
2. Deflationary relationships
In a deflationary environment, there is usually an inverse relationship between stock prices and bond prices. Note that this translates to a positive correlation between stock prices and interest rates.
Also, there is an inverse relationship between the US dollar and commodity prices, as well as between bonds and commodities. These present the same scenarios as was the case with an inflationary environment. The only positive correlation in a deflationary environment is between stock prices and commodity prices.
Importance of Intermarket Analysis
Intermarket analysis can provide an insight into the future direction of financial markets. Determining the correlations between various kinds of asset classes can provide important confirmations into the probable direction of the asset being considered. For example, relationships between certain stocks can provide insights into when a new trend is starting. This can help investors in either exiting existing positions or entering new positions poised to profit from a trend change.
However, no method of analysis is designed to be used as the only method of analyzing assets. Intermarket analysis is most effectively used along with other analytical tools or techniques. Also, keep in mind that correlations revealed through intermarket analysis are not guaranteed to remain stable.
Changing economic conditions may lead to changing correlations. Positive correlations between asset classes may become negative correlations, or a correlation may cease to exist altogether – meaning there is no longer any statistically significant relationship between the assets.
Thank you for reading CFI’s explanation of Intermarket Analysis. CFI offers the Financial Modeling & Valuation Analyst (FMVA)® certification program for those looking to take their careers to the next level. To keep learning and advancing your career, the following resources will be helpful: