The black crow

Call it good omen or bad, human beings have associated natural occurrences with events. Though ‘objectivists’ say human beings suffer from illusions and see what they want to, reconsideration shows there is more to illusions than just a black crow or swan.

Watching a crow perched outside your window or watching a black swan in the country side lake or on the trading screen are patterns because they repeat (even if rarely). If there was a crisis (large economic fluctuation) happening all the time we would not have connected them to ‘birds’ because there would be no precedence. Only when the passing comet coincides with a famine that we label its next visit as a bad omen. It’s the repetition (cyclicality) of a process that guides society to establish patterns (frequent or rare).

The point I am making here is that identifying an outlier (a rare crow in our case) and metaphorically connecting it to economics, sensationalising a fluctuation does not make it all objective. At the soul of every pattern is a repetition (a cycle). The pattern keeps repeating because the cycle keeps pulsating. So, if time is at the heart of every pattern, why do patterns sell more than a time cycle. Ok, patterns do offer a story and humans love stories (Shiller in Irrational Exuberance), but is there really an objective reason, which can make cycles more objective and scientific?

If we could connect an outlier with a cycle, in other words, if we could prove that outliers happen cyclically, we could time the reappearance of the crow (or swan). Before we connect the two (cycles and outliers) we need to understand the character of an outlier (an extremity). Conventionally, outliers can be defined as extreme or rare events (rare large price fluctuations). An example is the Great Depression, the 1987 crash or the recent 2008 crash. Statistically, however, data has both positive and negative outliers. And the 1985 DeBondt, Thaler paper on mean reversion and three-year worst portfolio outperforming the three-year best portfolio is statistical proof that outliers among a group reverse in performance, and this happens repeatedly (cyclically).

So, as early as 1985, the two researchers looked at outliers on a relative basis (as part of a group) and proved extremity and reversion were connected. If we could increase the duration from three years to five years or more, we should get similar reversion in outliers. Shiller’s price-earnings (PE) work assumes decade-long PE reversion. The worst valuations of a decade tended to reverse. So, if outliers were always reversing and doing so repeatedly, what stops us from timing the appearance of the black crow (a rare event)?

I think some more research and some more time would generate enough cases on outlier cyclicality i.e. today’s worst are tomorrow’s best (and vice versa). And outlier cyclicality could be used to time the next big earthquake, the next large volatility spike, the next crash, the next $10 intraday move on oil or just about anything else.

Another thing that stops us from understanding black crows is how we define market in the first place. If the market for you is the Sensex 30, the chances of your understanding the worst or the best (the outlier) are small. (‘Redefining ‘market’ in risk assessment’ June 2011). You need to extend your group to a 1,000 assets or maybe 10,000 before you are sure what is really worst (or best). And once you reach there, the only challenge would be to have the courage to buy the worst, despite the black crow or the swan.

 

The author is CMT, and Co-Founder, Orpheus CAPITALS, a global alternative research firm