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Anatomy of Technical Trading: Black Swan Or Mean Reversion

By "technical trading" I mean trades based primarily on considerations other than fundamental or apparently irrational (such as divine revelation, planet alignment, or social/moral responsibility) factors. It ranges from high-frequency, statistical arbitrage, pair trade, chart pattern, to certain trades involving highly structured derivatives. There is a gray area where trading is based on well debunked patterns such as Elliot Wave, which I shall simply leave to the reader to decide what to call. Another exception is the kind of technical trading that exploits inefficiencies in the market mechanics or regulatory loopholes, such as flash trades. If you can get into this game in time, congratulations and grab all the money while you can. Such opportunities by definition have very high entry barrier. Only the privileged few can get in.

My theory is that all technical trading can be broken down into a dichotomy of Black Swan and Mean Reversion, though some complicated trades may have both elements. Each has its distinct basic assumption, risk/reward profile, and application. I'll summarize in the table below:

  Black Swan Mean Reversion
Assumption Shit happens. Things will go back to normal.
Winning Odds Usually <50%, often much less. Usually >50%, often much more.
Winnings Much bigger than losses. Much smaller than losses.
Application Hard to sell, good for own money. Easy to sell, good for others' money.
Examples Momentum, buy Straddle. Pair, statistical arbitrage.

Now let's dissect them more closely.

Which Is Superior?
For every Black Swan trade, the opposing side is by definition a Mean Reversion trade whether the trader realizes or not. Is this a random game or does one side have more merit?

The Black Swan trade says either or both of two things:
  1. The market is underpricing the tail risk.
  2. The market is in transition and will not revert to historical mean.

On the other hand, the Mean Reversion trade says BOTH of the above are untrue.

Therefore, Mean Reversion requires a stronger assumption.

  1. History shows the market tends to underprice tail risk except at the height of crisis
  2. If you agree that the current price is the best prediction of future risk/reward expectation, then you're saying the market is Martingale. In reality, arguments can be made that markets are "Martingale like" in the sense that any argument for the existence of a constant mean requires some strong assumptions about market mechanism, macroeconomic behavior, or even sociopolitical structure that have been proven repeatedly by history to change over various timescales.

So it would seem that Black Swan is right. In fact, both are right, but at different timescales. For a given market and trading strategies with similar lifespan, Black Swan works on a longer timescale while Mean Reversion works on a shorter one.

But there're two fundamental problems with Mean Reversion:
  1. You never know when a black swan will swoon down. You know it will come, but don't know when or how big. You could resort to fundamental analysis for prediction, which can be a solid strategy but then it's no longer technical trading. You could try to use technical indicators to predict disaster but then it's no longer a Mean Reversion trade.
  2. At the beginning of a black swan event, the market always appears to be out of place, which by definition presents a fantastic Mean Reversion opportunity. But in fact it's a trap. In theory you could set up various kinds of stops to prevent stepping too deep into such traps. But the temptation is huge and the required discipline can be very painful.
Two spectacular failures of classic Mean Reversion: LTCM and Merrill Lynch's bond-CDS basis trade near the end of 08. In fact, in some sense the entire subprime CDO/CDS trade that dragged the world into the crisis was a gianormous Mean Reversion trade by the CDO buyers and CDS sellers. But why didn't the opposing side, CDO sellers and CDS buyers, win? Notwithstanding AIG CDS counterparties' huge win, at the macro level the Black Swan trade didn't win the equal amount of losses only because of the massive deliveraging and default/bankruptcy/foreclosure. Trading is a zero-sum game, until it's not.


Black Swan usually incurs a relatively large number of small losses before hitting the jackpot. It's very painful to take a large number of small losses. Nassim Taleb, father of the term "black swan", had limited success running his hedge fund. You may have the emotional discipline and strength to stick to the strategy. But it's impractical to ask your clients/investors to do the same. 

On the other hand, Mean Reversion can easily produce a steady stream of consistent gains. It's easy to sell to clients and investors. Then one day it'll blow up. But hopefully it's not your money by then.

This is why I said in the table above that Black Swan is suitable if you trade your own money, while Mean Reversion is for trading others'. 

Timescale And Risk Limits

Of course, when you drill down to details, things are never quite that simple or cynical.

Taleb's hedge fund took years for the black swan to make up for the losses. He was hunting for huge, rare birds. But black swans come in all timescales and sizes, from milliseconds and fractional pennies up. If you target the right timescale, it's possible to lose most trades but win most days. And once you catch a black swan, don't be afraid to ride it for as long as you can. This is what you count on to make up for the consistent small losses. Black Swan can be an easy sell.

On the other hand, the downside of Mean Reversion can be limited with careful risk management strategies and strict discipline, at least in theory. If an arb looks too good to be true, it probably is. Be quick to cut loss. Complement your Mean Reversion trade with certain combination of fundamental analysis, common sense, and a healthy dose of paranoia. Mean Reversion can be good for your own money.

In summary, Black Swan calls for erring on the greed side while Mean Reversion traders should be fearful and not too greedy.

Disclosure: None

Disclosure: None