The Law of Large Numbers | Tackle Trading

≈ Numbers don’t lie. ≈

The Law of Large Numbers states that the average of the results obtained from a large number of trials should be close to the expected value, becoming even closer as more trials are performed, i.e., as the sample size grows, the mean will get closer to the expected value of the whole population.

The classic approach to explain this probability theory is using the coin flipping example. You got a 50% chance of either get heads or tails. The more you toss the coin, the closer you get to the 50% expected value. The first toss might give you heads. The second one too. And the third. But as you keep trying, say 10,000 times, you will get 4,990 heads, and, therefore, 49.90%.

The key here is long-term consistency.

Now, replace the coin flipping with trading. You enter a position that has a 90% POP (0.10 Delta ≈ 10% Prob. ITM). You get the point: the more you trade, the more the mean of your sample size will get closer to the expected value of the whole population (90% POP). You might lose the first, the second and the third rounds. That doesn’t change the fact that the trade has a 90% POP. You can keep trading as long as you don’t lose your shirt during the first rounds. That is the essence of money management.

≈ If you are pushing the edge, eventually you find the edge. ≈

Chart of the Day: Distribution Analysis

Never try to predict the future, instead, think about it in terms of probabilities. A histogram like this can be developed from your trading system to give you an idea of how the future might turn out. A simple reading you can do: If most of your trades are gathered to the right side of the charts (after the 0.00% mark), you’re doing fine.

Video of the Day: Free Solo

A stunning, intimate and unflinching portrait of free soloist climber Alex Honnold, as he prepares to achieve his lifelong dream: climbing the face of the world’s most famous rock: the 3,200ft El Capitan in Yosemite National Park. Without a rope.

Originally published at tackletrading.com on January 18, 2019.