How Does The 80/20 Rule Apply To Investing? 1
Most people understand on some basic intellectual level that few outcomes in financial markets (and life) are certain – that is, luck is a factor.
In turn, the existence of luck means that market outcomes are rarely binary. How does this affect our ways of thinking about markets? More importantly, what does the 80/20 Rule have to do with it?
In order to answer these questions, we have to begin thinking in maybes.
Our human minds seem predisposed to jumping to conclusions when we are faced with a paucity of information. Reddit’s certainty of how their GME short squeeze could only turn out in their favor is a good example of this.
Retail traders saw GME’s price chart go vertical and somehow that was enough to convince them the stock could only go higher. Of course, more than a few of them learned the very hard way that certainty is not a luxury anyone in financial markets can afford.
Perhaps it would be wiser not to think in terms of “yes”, or “no”, but in terms of “maybe”, and “maybe” to what degree?
Going back to the GME example, a retail trader, when faced with the question “Can GME only go higher?”, instead of immediately thinking “YES!” and rushing to execute the trade, would pause and ponder different possible scenarios – the maybes.
Maybe GME won’t go higher, or maybe it will. Maybe the short squeeze ends a few days after the trade is executed. Maybe it doesn’t and the stock price really does go to the moon.
It doesn’t take much effort to work out a few basic scenarios of what GME may or may not do. If this abstract level of uncertainty is tricky enough, the bad news is that it only gets worse after this point.
The general (and most widely accepted) idea at this juncture is to apply what is taught in school, which is to run through an expected value calculation.
Unfortunately, as we will see, this calculation isn’t fit for purpose when it comes to financial markets. This is due to the nature of uncertainty in markets, which precludes any sort of precision.
Expected value is calculated:
E.V. = P(X1)×X1 + P(X2)×X2 + P(X3)×X3 + … + P(Xn)×Xn
Where P(X) is the probability of the scenario number (1,2,3,…,n) occurring, and X is the payoff the scenario gives.
As such, our hypothetical retail trader thinking about taking a punt on GME has to assign probabilities to each scenario occurring, as well as the payoffs he thinks are associated with each scenario.
Considering that our trader is already biased by all the GME short squeeze talk flying around, he will naturally overweight the most bullish scenario, say at 70%, and the associated payoff at $150.
The trader then considers the bearish scenario of GME’s share price falling like a stone, and weights this at 30%, since 70% + 30% = 100%, with the associated payoff -$150.
The expected value works out to be $60, which gives our trader even more confidence in going long GME!
Obviously something isn’t working correctly. How could someone come out of a thought exercise meant to highlight prevailing uncertainty with even more certainty ?
To be continued…
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