How To Exploit The 80/20 Rule In Trading & Investing 1

We live in a world where Paretian effects dominate, and financial markets are no exception. Understanding this reality can bring about a paradigm shift for people exposed to this idea for the first time.
Such a shift can, in turn, result in one adopting a more profitable approach to trading.
In terms of trading/investing, having a Paretian perspective means that traders must act to both guard against, and take advantage of, Paretian effects.
Beginning with Kenneth Grant’s 100/10 observation, we know that 90% of trades will either not be particularly profitable, or be straight up losses. That means, to be prepared for the worst outcome, we should expect to lose money on most of these trades.
Consequently, losses on these trades must be limited.
Since we do not know beforehand which trades will fall into the 90% bucket and which will fall into the 10% one, losses on all trades must be limited.
To see how this works out mathematically, we can use the expected value calculation first mentioned at the beginning of this series of articles. While expected value does not work well when used to analyze scenarios for individual trades, it works very well on the portfolio level, allowing us to see just how powerful Pareto effects are.
E.V. = P(X1)×X1 + P(X2)×X2

If a trader expects to lose $100, 90% of the time, while winning $1000, 10% of the time; the expected value works out to $10.
This illustrates the degree to which Pareto distributions affect outcomes: if the trader made 10 trades and 1 was a big winner, the profits on that one trade can make up for all the total losses on the other 9.
Of course, there is a limit to this, as can be seen from the table, if the trader expects to lose $200, 90% of the time, the expected value drops to -$80.
Which means that in order to fully take advantage of the Paretian nature of markets, the trader must be conscientious with risk management, keeping losses per trade small.
The second table shows Pareto effects working against the trader. In this scenario, the trader takes many small wins, but a few large losses, which is enough to push their PnL into the red.
If the trader expects to win $100, 90% of the time, while losing $1000, 10% of the time, the expected value works out to be a net loss at -$10. Assuming this happens over a total of 10 trades, 1 trade with a big loss is enough to wipe out all previous profits.
Obviously, this underscores the need for some form of risk management to limit large losses.
To be continued…
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