Understanding Lot Size Granularity: Why Portfolio Management Through Position Sizing is not the Best Idea

Perhaps the biggest issue when managing several trading systems is to be able to properly manage their equity allocation such that systems that are getting into deeper drawdowns are punished while systems that have more profitable results are rewarded. There are many ways in which this concept can be implemented but all of them have to include the ability of systems to become less corrosive to trading equity as their role within a portfolio setup becomes more and more negative. On today’s post I will talk about a few ways in which this can be done and why attempting to tackle this problem through  changes in the lot size of a trading strategy is not a good idea for Forex trading (particularly when the amount of traded equity is not low).

Let us suppose you have 5 algorithmic strategies trading in a portfolio and you want to make sure that systems that behave badly have less potential to lose money than systems that are trading with better results. The first intuitive way to do this is to manage trading balance independently for each system, making them trade less money as their “personal balance” grows smaller and smaller. This particular feature – implemented as a private balance mechanism in Asirikuy – has the big problem that you lose the whole ability to profit from compounding in a portfolio as the systems will not be able to compound on each other’s profits. This is the exact same thing as trading your systems in separate accounts as they have no idea of what each other does. While doing this ensure that bad trading systems get  less and less balance with time, it also defeats the whole purpose of running a portfolio (shared compounding).

If you want to preserve portfolio growth you have to think about ways in which the stake of systems can be reduced as they go into deeper draw downs while allowing them to see the entire account balance. The most intuitive way to do this is to track the performance of each system in someway – for example by following their drawdown depths – and making the lot size they trade proportional to this value. You can also make the scaling of this exponential such that systems that are bad trade less money much faster. Here is when we start to see lot size granularity issues and how they affect the management of portfolios. In practice, the implementation of the above is very problematic because the scaling in Forex trading is not infinite.

I will now give you an example so that you can see what I mean. Let us suppose that a trading system is trading 0.05 lots and risking with this a 2% share of the account per trade, this is happening on an account that currently has a balance of 5000 USD. If the system gets into a 10% drawdown and we want to make sure that its stake is now reduced we can punish it by reducing its stake to 1%. However we cannot do this because we cannot trade 0.025 lots but we need to either round up or down (to 0.03 or to 0.01), this means that we will not be trading with the 1% risk we want but we will be trading at either a higher or lower risk than what was intended. Lot size granularity problems refer to money management issues that arise due to rounding problems as the minimum tradable lot size of an account is approached (by approached I mean that you are in the same order of magnitude). 

In practice lot size granularity problems will show up with accounts that trade down to 0.01 lots on balance levels up to 50,000 USD, if adequate risks are to be maintained. This means that proper money management and scaling of positions based on drawdown depths or any other score (such as for example gradients of the equity curve or such other measurements) will be impossible to carry out with the balance levels most traders use in Forex trading (also bear in mind that cent accounts – that allow for finer management – are restricted to 2-3K account sizes so they are only suitable for testing purposes). It is practically impossible to properly manage a portfolio using any form of lot size scaling without going into serious rounding issues due to lot size granularity problems. Therefore trying to scale the lot size of trading systems to attenuate draw down effects in a portfolio setup is a bad idea unless the amount of money in the account is very high.

Obviously this does not mean that portfolio management cannot be carried out through position sizing but it implies that the degree of control that you have will be less. You should also consider that any simulations should include your lot size granularity limitations such that you can get an effect in simulations which is similar to what you would get in real life. Running simulations with the same contract sizes, minimum lot sizes and account balances that you would use in reality therefore becomes fundamental if you want to use lot sizing in order to exercise portfolio management control.

In my view however there are much better ways in which portfolio management can be carried out, giving us both the opportunity to remove bad trading instances and give more importance to trading systems that are behaving properly. Game theory allows us to control portfolio management through the use of trading probabilities rather than lot sizing effects, allowing us to control the trading composition of our portfolio instead of the actual risks taken when positions are opened and closed (which are fixed as percentages of account equity). Instead of trading less/more money what we do is simply to take less or more trading opportunities for a given strategy depending on what the game theory trading probabilities are (with this probabilities being determined by trade winning/losing history). Game theory also allows us to have clearly mathematically defined worst case scenarios if all systems turned out to be losers.

Obviously game theory will be the subject of another post but it shows us that there are better ways to manage portfolios than with the use of lot sizing approaches which are going to be easily subject to lot size granularity problems. If you would like to learn more about algorithmic trading systems and portfolio management  please consider joining Asirikuy.com, a website filled with educational videos, trading systems, development and a sound, honest and transparent approach towards automated trading in general . I hope you enjoyed this article ! :o)

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4 Responses to “Understanding Lot Size Granularity: Why Portfolio Management Through Position Sizing is not the Best Idea”

  1. Edward says:

    Hi Daniel,

    Thanks again for a good post. If you trade a particular strategy more/less often depending on its performance over the past weeks/months/years, it will likely reduce the drawdowns, but surely it will also then take longer for the strategy to get out of the drawdowns. So the drawdowns might be smaller, but won’t they simply last longer?

    Kind regards,


    • admin says:

      Hi Edward,

      Thank you for your comment :o) You need to picture here that portfolio management does not claim to make things better from a profitability perspective. If all the systems you’re trading work as they are intended to then portfolio management gives you a worse result than if you hadn’t used it. The idea however is to protect you from excessive losses in case things don’t turn out as you would want. Drawdown period lengths might indeed be longer because of the punishment but you will also have a higher chance of preserving equity (they will be shallower). This can be the price to pay for better preservation. Thanks again for commenting!

      Best Regards,


  2. pips.maker says:

    Don’t you think that you are just pushing the problems away a bit – number of trade entries or number of running instances of the algorithm are also granular.

    • admin says:

      Hi pips.maker,

      Thank you for your comment :o) Entry numbers and running instances are NOT granular, they are integers so they are not limited by any “minimum lot size” rule as is position sizing (which is what causes granularity). I hope this clears it up,

      Best Regards,


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