Big and Small Money: Does the Little Guy Have an Advantage?

There is an argument that has always been used by people who are fixed on the achievement of extremely high profit targets when they are confronted with the real-world evidence which shows that “top player” audited market performance values have been at most of about 20-30% annually and in average about 7-10%. This argument is that we do not see bigger figures in long term audited accounts because these accounts play “big money” and therefore they cannot have the “freedom” that small money has. The logic behind this argument is that the “little guy” has an inherent advantage due to the simple flexibility around the way in which money is invested and how they can get in and out of the market in a “quicker” and more efficient fashion. On today’s post I am going to talk about the “little guy” advantage, why this is NOT as important as you think along with some evidence that this is in fact the case.

The idea here is that volume plays a fundamental role when we trade in the market. When John Doe wants to trade with his 10K account he can easily get in and out of the market and therefore he has a lot of flexibility of when and how he trades his account. On the other hand the idea of volume dependency suggests that a “big guy” who is trading with a 50 million account cannot effectively do this since he depends on the liquidity the market has to offer. In essence what we’re saying is that the “big guy” doesn’t have as much flexibility because he depends dramatically on the actual offers inside the market while for John it is always very easy to get in and out as the market always has enough liquidity to fill his orders. Therefore since John has more flexibility he can get more profit and effectively the average compounded yearly profit to maximum draw down ratio we see on long term audited performers should not be applied to him because he is not a “big guy”.

However we can easily destroy this argument in several ways. The first important fact is that “big money” has access to better liquidity and they also do not trade from a huge account with 50 million dollars or whatever huge quantity. When people trade money in this way they distribute their money along many smaller accounts which are allocated to individual traders or small trading groups which then use this money to trade. They therefore have the “small money” advantage with the added plus of trading on a far more superior architecture and a much more professional environment, added to the fact that the money they lose isn’t theirs so there is a lot of psychological pressure relief that retail traders do not have (as they lose their own money).

The above argument is further reinforced by an in-depth analysis of long term audited performers on the Barclay Currency Trader Index. Who makes the most money? In contrast with the proposition that volume is “worse” for long term performance the truth is that the larger players here make the most money. If you divide accounts into those that trade more than 10 million and those which trade 1 million or less you’ll find out that large players are making a lot more money in the long term. Having more money is not a disadvantage in regards to execution or getting “in and out” as money management is in most cases NOT centralized and execution conditions and trading environment are MUCH better than what any retail trader could have.

However there is an advantage the little guy has which the large guy doesn’t have which is related to risk taking. Although both types of market participants have the same inherent average compounded yearly profit to maximum draw down long term “cap” the funds with larger accounts cannot have the luxury of withstanding moderate to high draw down levels because they will be destructive to their image towards their customers. While a small retail trader could – for example –  trade to make 100% a year with a 50% worst case scenario (which is determined by Monte Carlo simulations of his or her portfolio) a trader managing more than 1 million would never take such a risk – with the exact same portfolio – because if a worst case scenario materializes it will be devastating for their track record. They would rather trade to make 20% a year with a 10% worst case scenario because this preserves the integrity of their trading performance even if they have to create a new portfolio due to an inherent failure of the current portfolio’s characteristics. This strategy makes more sense regarding long term profitability and account growth.

So there you have it, the little guy does have an important advantage over the big guys which is NOT related to execution or how the “little guy” can trade but it is related to the fact that the “little guy” doesn’t need to show anyone audited performance, has no customers and therefore can take larger amounts of risk. This means that yes, you can be more profitable if you’re a retail trader but you will always be more profitable at the expense of a higher draw down and a higher worst case scenario value. There is no free lunch in trading and the inherent limitations shown by audited performers apply (as the past 25 years of evidence on the Barclay Index have shown).

If you would like to learn more about automated trading and how you too can learn to build your own systems and determine the worst case scenarios of your strategies through Monte Carlo simulations please consider joining, 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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2 Responses to “Big and Small Money: Does the Little Guy Have an Advantage?”

  1. Jeff says:

    Hi Daniel,

    Thanks for another interesting and thought-provoking posting.

    Related to this post and others you’ve written re Brclayhedge currency trading index, it seems the Holy Grail of Forex is a myth (see

    And for instance the current Top 10 performers over the last 3 years:

    …. shows that one would simply have to achieved over 12% compounded annual return (which may not seem size a large figure) to be in that Top 10.

    My question (I got there eventually!):

    Asirikuy systems can be combined into a portfolio that on backtest results can easily outperform this 12% figure and also maintain low drawdown e.g. Watukushay No1 (Qallaryi) with risk setting 1.2 gives the following backtest results:

    Compound Annual Growth Rate 12.5%
    Max Drawdown 10%
    Average Risk per trade 1.7%
    Sharpe Ratio (compared to S&P 500) 1.7

    So, which is correct:

    1. Asirikuy and its systems are the Holy Grail :-) – or at least can perform on a par with the best in the world, or even out-perform them?

    2. Backtests are just that and are not indicative of future live results?

    3. Something other than options 1 and 2 above?

    Best wishes,


    PS Please feel free to praise Asirikuy systems, because we all know you to be honest in your opinions and you make claims on a sound statistical basis.

    • admin says:

      Hi Jeff,

      Thank you for your comment :o) Indeed you hit the nail on the head here. Let me now state some points to help you better understand the issue:

      1. Anything is possible : There is no way to prove that any long term return is NOT possible, however during the past 25 years the return to draw down ratios which have been achieved have been quite modest and in line with certain thresholds (as discussed on a few posts). The fact that you have profitable simulations does NOT mean that something has already been achieved, for something to be realistic it needs to happen in reality and this hasn’t happened yet (we don’t have a 25 year record with profit to draw down ratios that exceed the historical achievements).

      2. Simulations are just simulations: The fact that you have obtained systems or portfolios that would have theoretically obtained a certain amount of profit in the past does NOT mean that you will do so in the future (or that you did in the past, remember that there is ALWAYS hindsight in design). What the simulations do is merely put some thresholds around your expectations so that you can evaluate if you’re following them or not when trading into the future. For example a properly evaluated portfolio with an average compounded yearly profit to maximum draw down ratio of 7 does NOT mean that this is achievable or that you will get to it but through Monte Carlo simulations you know that your portfolio has a chance to deliver this while it remains above X worst case scenario. Backtesting provides you with the means to encase the expectations of your strategy around a draw down framework, however – as I said above – realistic is only realistic until it is achieved in reality. We obviously intend to challenge market performance thresholds but to say we have already got the “holy grail” is a huge exaggeration, right now we merely know how to determine if we’re still on the road to achieve this or not (simulations and Monte Carlo determined worst case scenarios). Decades of live trading will determine how and if we succeed and how our methods will face real challenges.

      3. Never measure absolute returns but ratios. As I mentioned on the post the inherent market limitations are NOT related to absolute profit but to profit to draw down ratios. For example someone can potentially achieve average yearly returns in the order of 100-150% but the worst case scenarios are bound to be very large and therefore the probability to recover from a failure will be low. When comparing two performers never compare their absolute profit figures but their profit to draw down ratios.

      I hope this helps you with your questions Jeff :o) Thank you very much again for posting,

      Best Regards,


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