How Does The 80/20 Rule Apply To Investing? 2
At this point, it should be apparent that the entire expected value thought process is extremely subjective, and vulnerable to cognitive bias. Every trader who runs through this exercise will come up with not just different numbers, but also different scenarios.
For example, a more experienced trader would also consider the scenario of GME shares trading sideways. A more fastidious one might even include “middle” scenarios where GME moves higher/lower, but not as much as in the most bullish/bearish scenario.
Moreover, every trader will ascribe different payoff amounts to each scenario, even though all are trading the same stock, reading the same narratives, and looking at the same prices.
One trader might think a bullish scenario in GME means a $100 move higher, while another might think that it means a $50 move higher.
As such, applying the methods taught in probability/statistics textbooks to financial markets is difficult, to say the least. Unlike the simple games used in textbooks to teach probability, markets do not have discrete outcomes like getting tails on a coin flip or rolling a 6 with a dice.
Instead, we have stocks that can end the trading day anywhere between $0 and some astronomically high value, since there isn’t a cap on the upside.
It gets even more confusing and risky in other markets, like the oil futures market. WTI contracts on the CME have neither an upside cap nor a downside cap – oil futures can trade for less than $0 a barrel!
Complicating matters is the fact that trading scenarios have another dimension to them – time.
In textbooks, scenarios are always clear and simple – they end after the dice/coin settles on one of its faces. Roll, wobble a little, settle, and done.
Position management in trading/investing is not so simple due to the open-ended nature of trades. Depending on the trading strategy, the timing of the exit may not be clear. And the longer the position stays on, the more market realities change. This means that the expected value thought exercise that the trader had previously engaged in is now invalidated.
Not only will the possible payoffs for each scenario change as information and narratives develop, but the probabilities themselves will change too!
Consequently, the discrete and elegant expected value formula cannot accommodate the dynamic and continuous nature of markets.
Any trader who ignores this reality will find that ascribing probabilities and payoffs to different scenarios is an exercise in guesswork, and not reliable precision.
How then should we think about probabilities in the context of markets?
To be continued…
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