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posted on 08 June 2017

How Inversely Correlated Futures Markets Can Provide An Edge

by Gabe Velazquez, Online Trading Academy

Online Trading Academy Article of the Week

Each day the global financial markets are impacted by events that cause traders to react in dramatic fashion. These responses quite often will have a ripple effect that can stretch across all types of markets and asset classes. In other words, what happens in one market will in turn move another related market.

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For newer traders, it's important to understand this relationship. In this post, I'll go over some of the strongest inverse market correlations and their uses to help traders gain an edge.

But before we get started, there is one major caveat about this topic: correlations usually hold, however, there are times when what seemed to be a strong correlation between two markets breaks and no longer works. This is often a temporary phenomenon as strong correlations always revert back. An astute trader must be attuned to these changes and be flexible enough to make the adjustments necessary to keep his edge.

The first inverse correlation we'll go over is the one between stocks and bonds. For stocks, we'll use the ES (S&P 500 mini) against the (US) 30-year treasury bond futures contract to do the analysis. This is a simple risk-on versus risk-off correlation. What is meant by this is that theoretically, stocks are inherently riskier than bonds and therefore when stocks are moving higher investors generally have a bigger appetite for risk and would sell the lower yielding bond market. This changes however, when things get rough in the stock market. Investors seek the safe harbor of treasuries, and in order to raise the cash necessary to purchase these fixed yielding instruments, they sell their stock holdings. The two annotated charts below illustrate these inverse correlations.

How to use inverse correlation when you trade.

Understanding how moves in one market causes moves in other markets and using that information to your advantage.

We can see that major inverse moves happened pretty regularly in these two asset classes. The key for traders is to find both markets entering opposing levels simultaneously, thus increasing the probabilities of timing the turning points. This correlation is important for traders who engage the markets on an intermediate-term time frame as it can be a major odds enhancer. Identifying the quality supply and demand levels is the most important element of this equation.

The other inverse correlation we'll look at is that of the US Dollar index against the Euro Currency. This is a very strong inverse correlation because of how the Dollar Index is comprised, and the way the currency futures contracts are traded. First, the Dollar index is a basket of currencies traded against the US Dollar. The biggest component of this index is the Euro currency constituting over 57% of the index. In addition, currency futures are only the major global currencies (major industrialized countries) relative to the US dollar. In other words, they track the exchange rates of two currencies; because of this, the moves in the Euro currency greatly impacts the Dollar index. Similar to the Stock-Bond inverse correlation, we can see on the charts below that all the major moves happened on the same day.

What is inverse correlation?

The correlation between the US Dollar and Euro currency pair.

For traders trying to gain an edge, learning how different markets impact one another is a must. Not knowing how the US Dollar can change the trajectory of commodities such as oil, copper or gold is a big disadvantage, especially when you're competing with large banks and institutions who wouldn't think of putting their traders on the front lines if they didn't understand how the markets impact one another. If you want to have a chance to compete successfully you need to start thinking and acting like them; and one part of that is gaining an understanding of the interrelationships between markets. For the novice trader having a basic understanding of these two correlations is a good starting point.

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