My 10% Best Days Account For 50% Of Profits
Last Updated on April 18, 2023
I had a brief look at the distribution of my trading profits over the last four years. I simply ranked my net profit per day in descending order and got the following result:
| % best days | |||||
| 5% | 10% | 15% | 20% | 25% | |
| % of P/L | 0.32 | 0.53 | 0.70 | 0.83 | 0.96 |
The number 0.32 means that the 5% best trading days make 32% of my total profits over the four year period. Also, the 25% best days make 96% of all my profits. In other words, 75% of my trading days are basically just a waste of time and I better stay in bed. Unfortunately, I don’t know the result when I wake up, so I need to grind out every day no matter what.
This also emphasizes the need for discipline: you have to be at your desk every day. The minority of the days make all your money.
Another confirmation of Pareto principle (80/20)
Hi Oddmund,
When it comes to having to grind out every day I believe your conclusion may not be correct. If you relied heavily on trend following systems and 5% of your trades made 90% of gains then this could be true, but your returns I believe are more normally distributed. Hence if you randomly skip a day per week your profits in the long run should decline ~20% as you are taking 20% of time off. You will skip some good days but you will also skip some bad days. In fact the worst losses in mean reversion systems tend to be worse than the best gains. So take a day off and enjoy it if you feel like it, as long as you pick the days off at random.
Hi Oddmund,
you probably know this but in Equity investing, this is quite similar. A small percentage of days are responsible for the bulk of the profits. However, the analysis is flawed. I did the same analysis eliminating also the 5% or 10% of worst days and then the Sharp Ratio improved quite a bit (so eliminating 10% best days and worst days). You might find a similar result…
Hi, that’s a good point, and I should have mentioned it. But luckily, my losses are smaller relative to wins 🙂 Removing the biggest losses have far less impact than best days.