Defensive Money Management Explained (Part 9) – The Money Management Edge Part 2

By Lawrence


Index Page

Continue from Part 1

Money Management Edge Is A Function Of Leverage

In laymen’s term, money management edge is simply how much money you can afford to sink into a hole and how much time you can afford to wait for a position to turn profitable.

It may sound stupid to some but this is exactly how mega rich people can afford to invest in many things during the worse periods in history. First they do not need those money. Second they do not mind losing a little bit here and there on each individual investment. Third, all it takes is one investment out of many becoming profitable to enable the overall portfolio to become profitable.

When the same concept is applied to trading, it becomes a spectrum of strategies that most aggressive traders have ignored simply because of the requirement of reduced leverage and willingness to hold onto potential losing positions for a long time. The aggressive traders think that it is a waste of capital (and time) as they can make more money several times over.

Many aggressive traders failed to realize that it is just their biased opinions. The excitement they seek clouded their judgement. The high probability winning rate they enjoy cannot offset the significant drawdown they suffer from time to time. When complete cycles of performance are analyzed, most of the aggressive traders are not really doing that much better than those who take a balanced approach to money management and precision entry.

Only legendary traders (or lucky traders) can profit from short term optimized strategies and move onto another optimized strategy at the right time to avoid the inevitable. For mortals like us, we often have to wait until the currently employed strategy failing (i.e. the boat started to sink) before we realize it is time to make adjustments. By having a lower leverage, we are giving ourselves rooms to buffer the transitional period instead of suffering major equity drawdown.

Volatility Filter

Money management technique not only control the risk after you enter a trade, it can also be used as a filter to block you from taking a trade in the first place.

For example, you have a decent trading setup that you can pull in $200 on average per contract per trade. With 60% winners and $200 stop you should be doing great. But then the market enters a volatile period and you got whipsaw left and right. It takes almost no time that your profits are all wiped out.

Should you increase your stop size? The answer depends on your understanding of your trading setup.

If your method is designed with characteristics coming from certain volatility range, it is not likely going to work even if you increase the stop size. A good check on that is to apply a volatility filter on your model to see if your trading model suffers similarly in historical period where the volatility was as high as you are experiencing at the moment.

If you find out a simple filter on the volatility actually boost the performance of your model or method significantly, it is time to stop trading until volatility returning back to normal.

Another usage of volatility measure is the adjustment of trade size. When the expected risk (based on initial stop loss) is greater than your prescribed risk per trade calculated from your account size, it is time to reduce the trading size. If the trading size is reduced to nothing, stop trading is the smart and logical choice.

There are good reasons why stop trading is better than forcing trades to happen.

First, the extreme volatility may not last. It can be a few days to a few weeks. If you expanded your stop losses and force yourself to trade, before you get the chance to see the law of large numbers working in your favour, you may have suffered extreme losses already. When normal volatility is back, due to the fact that your account suffered significant drawdown, you will be forced to trade a smaller size to dig out of the hole. What is the point of taking on the extra risk in the first place?

Second, if the extreme volatility is here to stay, isn’t it reasonable to spend sometime to study the behavioural change? By customizing your strategy to deal with the change in characteristics, you are giving yourself a better chance to win the game. Rushing in with your existing method with a bigger stop loss is not the answer.

Learn The Money Management Effects Using Random Entries

Once you dig deep into refining your trading setup while all the money management rules are already in place, it becomes very difficult to see clearly which part of your trading method’s profitability comes from an edge with your entry, and which part actually comes from proper money management. It is not a problem if you are familiar with the behaviour of the market you are working on since you can easily guess how much the money management rules are contributing to the bottom line. If you are not familiar with the behaviour of the market you are trading, it is a good idea for you to take a step back and experiment with random entry models.

Using either random entries, or regular interval entries, on the market you are interested in, you can find out how far you can stretch the model using pure money management rules to make it profitable consistently. It can be done manually. You can also do it with optimization tools. The goal is to learn about the kind of money management rules that will likely give a strategy an easy way out without  an edge from entry at all.

From the experiment, you will learn a lot about the market you want to trade. You will gain insights how to protect yourself from volatile markets. It is not something I can simply give you a few quick rules and that you will remember. It is something better done by you so that it will become part of you.

I am going to use S&P Emini as an example here to illustrate the point. Most of the time, by using 2.5 times the 15-minute bar average range as your initial stop on trading models on 5-minute or smaller timeframes, you are giving yourself an edge of 60% chance where the position will go profitable some point in time within the next 2 hours. That is pure money management edge. As long as your pocket is deep enough, you stand to walk out with an extremely small positive expectancy. Thus if your trading system or method depends on a stop close to this size to turn a profit, your entry do not really have an edge by itself or its bias is not as strong as you think.

Note: This topic is running a bit long and boring but necessary because it presents the necessary building blocks going forward. e.g. proper average down is in fact a form of pure money management edge


  • MidKnight September 6, 2013 at 9:56 pm

    Not boring at all, keep’em coming!

  • mel September 7, 2013 at 11:06 am


  • MidKnight October 6, 2013 at 4:28 am

    Hi Lawrence,

    It would be great if you could finish series as you were about to start onto something that _really_ interests me.

    All my best,

    • Lawrence Chan October 6, 2013 at 9:06 pm

      It is quite complex to reduce the concept of averaging into several key factors with simple examples hence the delay. I prefer showing things that actually work.

  • mel October 6, 2013 at 11:28 pm

    If there is a way to have a kind of spread sheet to indicate where you are and how much and how to strategise to recover the losses will be great ! eg. now say if I am on a losing position, the spreadsheet can tell me how many lots to the next direction to recover X amount, then according to the actual trend direction, you take the move with the suggested quantum to recover as quickly as you can…

    • Lawrence Chan October 7, 2013 at 11:21 am

      You have the concept in reverse. Having such spreadsheet will help you clean out your account quickly.

      Average down into a position has to be planned – it must be part of your trading plan already.

      If you know you are in a losing position, you should cut the losses and move on. Again, this has to be in your trading plan.

  • omrangassan September 26, 2016 at 3:59 pm

    Thanx Lawrence for your ideas about the (average down).

    How may i contact you ? i wanna share some excel sheets with you about the right way to do averaging down ; statistically wise ! you’ll like.
    omrangassan @ hotmail dot com

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