Imagine you run a local convenience shop in a small village, mainly selling fresh produce with a short shelf-life.
Every week you place a new order with the wholesaler, to make sure your shop has a constant supply of stock. This means you have the challenge each week of deciding which items you will need and what quantity you should buy.
When you first opened your shop, you decided to keep things simple and to place an equal order of everything; whether it was apples, oranges or even something exotic like a passion-fruit. However, over time you began to take some items off your list. You realised no one was buying the passion-fruit or lychees, so you might as well stop ordering them. This left you with just the essentials, plus a few items that you liked to keep in stock that only sell occasionally.
So let’s imagine you are left with 20 types of perishable items that you need to buy each week. Every item carries a potential return (making a sale for a profit) and a potential risk (losing the cost of the item if it doesn’t sell before the end of its shelf-life).
How would you divide your order?
This is pretty straight forward. Most people would answer that they would stop buying everything in equal amounts and choose to buy more of the popular items and less of the unpopular items instead.
If you have Jimmy from the village, who’s the only person that buys your pineapples, but he only comes once a month when his mum is visiting, it doesn’t make sense to stock the same amount of pineapples as oranges. You would rather put more money behind the items with less risk.
This makes logical sense, doesn’t it?
So, why don’t the majority of traders follow the same logic?
We know particular levels or specific setups will provide different amounts of uncertainty and the potential return from these setups will differ as well. However, from my experience in dealing with people learning to trade, this is information that is understood but largely neglected.
This is the curse of the static position size!
Of course, having a position size that limits the percentage of your account at risk (preferably 1–2% max.) is better than having no limit (which often seems to be the case with new traders!), but many traders don’t seem to realise how important it is for this to be a dynamic figure.
It’s definitely a lot easier to stick to a static position size, such as 1% of your account at risk every trade, but this is just like ordering the same amount of oranges as pineapples. You know one carries a lower success rate, so why wouldn’t you limit your exposure to that uncertainty?
Profitable traders may not see the issue. Likewise, the shop may be turning a profit while carrying stock that it doesn’t sell… but positive optimisation is never a bad thing!
While we are building a trading strategy that works, we are constantly optimising our analysis. But that’s just the front-end, we need to make sure the back-end is working well too.
It’s a bit of a tricky thing to get to grips with, since it requires approximations and estimates about expected success rates, but this is something you can improve over time if you focus on following the appropriate steps.
With that in mind, I have the right prescription to help you on this path to optimised position sizing.
First, I recommend you watch this video on how we consider our dynamic position sizing:
And once you’ve got to grips with this concept of having a maximum quantity for each combination of signals (and had a giggle at my poor drawing skills), you should move onto this next video, which will explain how you can improve your forecasting accuracy through calibration:
I would love to know how you get on and whether you start to see any changes in your trading results. You can leave a comment below to let me know.