The mystery of losing long/short reversions

One of the most puzzling things about a long/short trade, crafted with hard cointegration-based analysis, fundamental data, sentiment assessment et cetera, can be to see its spread revert to its mean at a loss.

How can that be possible? Cointegration is supposed to identify enduring economic relationships, is it not?

Well, there are several losing paths where the theory of Mr Profit meets Mr. Reality (and comes off the worse). For example:

• The spread distribution underlying the Z score chart is not near-normal. Z scores rely on normality or near normality to be meaningful.

• The live beta deviates during the trade from the modeled historic beta. That may be due to a disturbance to the underlying cointegrated relationship – i.e. conditions are changing. This is common in FX where there are macroeconomic announcements nearly every day that are more signal than noise and can break cointegrated pairs – especially at the intraday level.

• The beta is unreliable due to a low R² (a measure of model strength). We find R²s less than 70% have a higher likelihood of failing to revert with profit.

Keep in mind, too, that many strategies typically rely on Z score triggers. Yet a Z is only a description of the spread – it is not an indicator of cointegration. If it blows out it may be reflecting a weakening cointegration situation; or it might be reflecting a small sample size (if one was used for the Z calculation) making it more sensitive to the incoming price data.

These types of scenario are the main reason ArbMaker software integrates “dynamic filters” into its Tracker allowing stops to be set based on the mean reversion coefficient, R², degree of cointegration and so forth. These are measures of and/or prerequisites for cointegration and will pick up direct changes to the underlying relationship better than a stop on the Z alone.

All the selections of our newsletter service use strategies that make allowance for this information. We strongly suggest users of our software take a similar approach!