Using CTA Trend Following Systems to Find Global Macro Trading Opportunities

CTA's or commodity trading advisers have been using long term trend following technical rules for years with great success. Some of the benefits of such a system is that once you have designed and tested the system it does not usually take much time to update it and have your trades ready for the next day.

Some of the common public domain type systems are based on moving average crossovers, Bollinger bands, and Donchian channels. While there are hundreds if not thousands of variants to these and other trend following systems the basic idea remains the same. Namely that trends can last a lot longer then you might expect and that the market is always right. You can have the best fundamental reasoning ever but if the market disagrees you will lose money. By going with the trend you significantly raise your odds of having not just a winner but a big winner.

For years CTA's have been applying long term trend following systems to the markets and making fairly consistent money. Most traders have heard of the Turtles, AHL, and John Henry. These are all people and firms that have made huge sums of money trading purely automatic trading systems with a long time frame. Most of these systems are fairly simple. Most CTA's biggest tool is position sizing and risk management and not the specific entry and exit rules.

So how can we use a trend following system to find good Macro Trading opportunities? Well it is common sense that one set of eyes can only see so many things. As a trader, researcher, or analyst you can only look at so many markets and do in depth research on them. By using a simple trend following system you are able to better focus your efforts. In simple terms you will better be able to go where the money is.

One other significant benefit is that with the proliferation of the ETF market we can track a technical system with almost any software package, web site, or even in Excel with little effort. So whether you are spending $2,000 a month on a Bloomberg or spending nothing using a charting web site you can track different markets and focus on the markets that are in solid up and down trends.

To implement a long term system into your analysis, simply pick some parameters that more often then not signify a trend. For instance if you are using a moving average crossover you could take a 20, 50, and 200 day simple moving averages. If the 20 is above the 50 and they are both above the 200 then it is in an uptrend and if the 20 is below the 50 and they are both below the 200 then it is in a downtrend. Pretty simple and yet it helps you focus on markets that are moving.

Another simple system is to use Donchian channels. You could use a 40 day high and low channel and if the market hits a new 40 day high then it is in an uptrend and if it hits a 40 day low it is in a downtrend. Simple and yet it works. You can easily follow 10, 20, 50, even hundreds of markets with this type of system.

Now take this system and accompany it with your economic, sentiment, and fundamental analysis and you can find a lot more good trade ideas. If you are used to bottoms up investment analysis just think if this as a guide as the where you should be focusing your efforts. You don't have to waste time on idea after idea looking for the next big trade. Just look at the signals and if they say uptrend then you do the research and see if the fundamentals support the trend.

With technology where it is today we don't need 100 analysts or thousands of dollars in software to find good investment opportunities. We need a systematic approach that is based on a solid theoretical and real world framework. This is not the Holy Grail but at The Macro Trader we have been using this as one of our approaches for a long time and it has helped us spot emerging trends that we otherwise would have missed. This shouldn't be the end of analysis but it is a good start.

Seed Newsvine

Bookmark this article in your preferred program

Comments

Add Comment

Popular Articles in this cathegory

This article is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License.