Use Intermarket Analysis to Gain an Edge
By Louis B. Mendelsohn
After years of studying the markets, observing the transition to global markets and developing countless computerized trading strategies, I began formulating an approach in the mid-1980s that explored the markets from an intermarket perspective.
By incorporating the influence of market data from closely related markets in conjunction with price data from a target market, I was able to create quantitative indicators that no longer relied only on past price data for the target market alone but incorporated the effects of related markets.
Past price data for the target market are still an essential component of this analysis, but when combined with price data from related markets, innovative technical indicators can be developed that produce superior analytics when compared to traditional technical analysis indicators or studies using only single-market data. Intermarket data helps transform lagging indicators into leading indicators that can be used to forecast expected changes in market trend direction within a short time span of a day or two into the future with a relatively high degree of accuracy.
Of course, the further you try to look into the future, the less reliable the forecast. Weather forecasters trying to predict the weather for the next six months or a year have a rather spotty record because so many random and unforeseen events can happen to alter weather patterns. In recent years, however, weather forecasters using more advanced forecasting tools have developed a good record for predicting the weather for the next few days.
The same thing is true in trading.
It’s impossible to say where the price of crude oil or any other market will be six months or a year from now with any degree of precision. That’s why I have limited the time horizon for forecasting markets to the next few days. Even being able to anticipate price action for a day ahead is still more than enough lead time to provide a trader with a tremendous trading advantage over the masses of traders who still rely only on single-market, lagging indicators.
It is not good enough to look only at each individual market by itself with popular single-market indicators that look retrospectively at an individual market’s past data in an effort to identify reoccurring patterns that can then be extrapolated into the future. This type of analysis really boils down to looking at where the market has been and trying to where it is going to go in the future.
I prefer to forecast market direction prospectively in a manner that captures the character and nature of today’s globally interdependent financial markets. This can be accomplished by using intermarket analysis tools comprised of leading indicators that can tell you whether an existing trend is likely to continue or is about to change direction, taking a lot of the guesswork out of trading.
The interrelationships of markets have become even more pronounced as the markets have become increasingly globalized. Despite the importance of analyzing intermarket relationships in this context, many traders are still too preoccupied with looking inward at each market, ignoring the interdependencies of the financial markets and their effects on one another.
In addition, technical analysts and traders have made little progress at objectively (quantitatively), not just subjectively (qualitatively), identifying repetitive patterns in market data, which is a necessary step for effective forecasting. It is now imperative for traders to adopt an intermarket perspective and to incorporate intermarket analysis into their trading strategies so they can deal with the global financial markets as they really exist.
A more quantitative approach to implementing intermarket analysis, such as I advocate, is not a radical departure from traditional technical analysis nor is it an attempt to replace it. Intermarket analysis is simply the next logical developmental stage in the evolution of technical analysis when you recognize the global nature of today’s interdependent, highly complex economies and integrated financial markets.
In truth, the only real piece of information you have to work with is the net effect of all these inputs, and that is price. As was emphasized earlier, the problem with past price data is that it has already occurred. Furthermore, everybody has access to historical price data, and they use many different techniques to massage old prices in an attempt to uncover new clues about future market strength and direction. Unfortunately, most traders who use these typical methods of analysis tend to lose money.
It may not be the techniques they are using that are solely at fault; it may also be the limited, single-market data that they are feeding into their analysis.
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This is an excerpt from the book: Trend Forecasting with Intermarket Analysis by Louis B. Mendelsohn