Profitable ETF Trading Strategies: Understanding regional correllation

Based on our market classification scheme, there are 9 market states derived from 3 price momentum measures combined with 3 volatility measures. There is an important phenomenon related to the Bull-Sideways-Bear market states that can give you both insight into current conditions as well as a decisive market edge in risk management.  The edge comes from observing and understanding the correllation in returns from geographical regions of the world with respect to US market returns.

Correllation is a basic statistic that examines the degree to which 2 streams of returns (in this case) move in tandem. At high levels of correllation and with a hypothesis in support, we may begin to look for cause and effect, but for our purposes simple correllation is sufficient for insight into favorable trading conditions.

When the world market is in Bull conditions, and the sun is shining, it is normal to find correllations diminishing, with some regions of the world achieving much higher than normal rates of return.  Simply based on the size of the US market it is usual to find different parts of the world leaving the US behind.

As we have seen lately though, when things turn south, correllations quickly converge and the whole world starts going south together. It is normal in these conditions for a flight to quality to occur and money seeks out the relative safety of the mature companies of the US. This sets up perfect conditions for a pair trade that goes long the US markets and short the rest of the worls, which can either be the mature economies of Europe and Asia (represented by ETF symbol EFA) or emerging market (represented by symbol EEM).

This strategy essentially will eliminate market direction and allow you to benefit from the persistent relative strength between regions of the world. This strategy allowed for you to benefit tremendously from the current market volatility, and it repeats itself with surprising regularity over long time periods.

Updated: October 25, 2008 — 4:37 pm
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