Defensive Money Management Explained: How Risk Is Controlled

By Lawrence

Note: Feel free to email me with your feedback lawrence@daytradingbias.com

Many Ways to Skin a Cat

A lot of beginners get the right idea that there is definitely more than one way to profit from the markets they trade. The issue, however, is that not all these methods are suitable for retail traders due to various reasons.

I am going to cover several common daytrading styles (methods) of their strengths and weaknesses. My focus is the general statistical behaviour of these trading styles, not specific trading techniques. Afterwards I will explain why there is really only limited number of ways statistically that enable a retail trader to be practically successful.

The Most Common Styles of Trading

There are several well known trading styles (methods) that can consistently extract profit from the markets. They can be generalized into the following categories,

scalping
swing
market making
HFT

Scalping was the most common trading style among daytraders before the mid-2000s. It worked very well because as long as the traders are willing to focus on the order flow in the smallest possible timeframe (i.e. price action behaviour) and can read the intentions, then extracting $0.10 here and there on a stock, or 2 to 5 ticks on a future contract was a piece of cake. By repeating the process 10 to 100 times a day, the trader can make very decent profit everyday. This trading style requires the trader to fully focus on the markets they trade and it can be an exhausting routine if you have to do that again and again everyday. Thus, many daytraders who trade this style are younger adults who are talented in reading price actions. Since mid-2000s HFT started to eat into the profitability of these traders, making it very hard to trade this way, as a liquidity provider, so to speak.

The statistical characteristics of scalping is high winning probability (greater than 80% in general) and pretty much constant winning and losing amount.

As a retail trader, unless you are young, willing to join a prop firm and that you get it in the first few months, it will be a difficult path to walk thru. Worst yet, HFT bots are now invading this space, making it much more difficult to survive, let alone being successful.

Swing trading has been and still is the favourite trading style among the large hedge funds and size traders. Once certain backtested conditions are met, these market participants will enter the market. Just their presents in the market through their orders can at least temporarily abrupt the order flows in those markets. These players do not necessary have to flat out their positions at the end of a trading day, making it possible for them to pocket from biases that span over several trading days.

For retail traders who are well capitalized, this trading style is much preferred over scalping as they may have a day job to attend to. The main obstacle is that the trader has to have a winning formula that works and the willingness of the trader to stick to the plan all the time.

The characteristics of swing trading is good winning probability, not necessarily very high probability, with very good winner amount to loser amount ratio.

Market Making has been one of the most profitable trading activities. It is effectively doing everything a retail trader is told not to from well-known trading gurus and books. The idea of market making method is to profit from the mean reversion behaviour in financial markets due to imbalance in order flow at different price levels. As long as you can withstand the open losses in your book and average up/down properly, you can eventually come out ahead. Sometimes it happens within minutes, sometimes it happens by the end of a day, and sometimes it will take months before you can work out the cost of your inventories.

Sophisticated market making firms have many venues to hedge their positions to improve their odds of winning like using options and index derivatives to hedge against their portfolios. Lately, however, HFT bots have eaten into the profitability of these firms thus the landscape for this style is changing.

The characteristics of market making is that you cannot generate proper statistics on the performance in terms of units traded because positions are piled on to create the statistical advantage. Thus normal retail traders are rarely possible to trade like a market maker. The capital requirement for retail traders to achieve the same capacity as a market making firm will be many times the capital reserve of such a firm because the rules and regulations are much less generous on margin requirement for retail traders.

High Frequency Trading (HFT) is the latest hot article that flooded main stream media these 2 years. Many technically oriented beginners have the misconception that they can too, create their own HFT bots and print money easily. That is as naive as the previous generations of traders who thought they can create their own trading models easily and sit back to see the model telling them what to do in order to make money.

Unless you have the expertise in trading model development and that you have access to directly connected computers to the exchanges (for trading stocks/futures/etc.) or one of the market making banks (for forex trading) it is not possible for retail traders to compete in this area due to the connections they have are way slower than the ones used by their competitors (i.e. well funded hedge funds). Speed in HFT is measured in milliseconds and retail traders are at least 3 to 5 times slower when they are connected to their brokerage for automatic trading.

Not Many Viable Choices for Retail Traders

From the explanations in previous section, it is clear that retail traders do not have a lot of viable choices to choose from in terms of trading styles.

Going for scalping or swing trading are probably the only viable choices as the capital requirement for market making is most likely out of reach for many beginners and that HFT is technically out of reach for retail traders. If the person insists on daytrading only, then scalping and specialized swing trading that always exit before market close are the only routes left.

If you are not a fit young adult with the intention to trade full time right off the start, then intense scalping may not be a viable choice either.

That leaves you to some kind of swing trading styles as the only remaining choice left.

Time to Remember the Lesson Learned

In last chapter I explained that there is no way you can tell if your historical performance is better than 50/50. That is the golden rule of survival – be skeptical of your performance in terms of winning percentage.

So, you may ask, then how will you ever create your own winning method?

The key is that you work on things that you can control. In this case, it is the amount of money you are going to win has to be consistently more than the amount of money you are going to lose.

It is time to use our trusted Monte Carlo simulator to visualize what I am talking about.

Here is the terminal equity graph of trading models (or method) that win at 50% (red line) and 60% (green line) of the time with winning and losing average are both $100. The rest of the settings are default. Both cases start with $10,000 capital.

Notice the huge contrast in performance between the two scenarios. When performance is dropped to 50% winning only, you will be subjected to 15% risk of the account being terminated from trading.

How do you know that your performance will stay at winning 60% of the time all the time?

Lesson 2: Controlling the Risk Can Boost Survival Rate and Performance at the Same Time

As oppose to focus on getting more winners than losers, if you choose to risk less in general, the results will be drastically different.

Using similar setup as the example above, if you focus on controlling the losers to average at $80 as oppose to $100, the resulting terminal equity graph will look like this.

At 60% winning rate (green line), you will be looking at 200% equity growth in the worst case scenario.

Even at 50% winning rate (red line), the terminal equity graph shows that you are still likely to come out ahead 98% of the time.

The bottom line as illustrated here is that if you want to achieve practical success in daytrading (or in fact any form of trading) as a retail trader, the second most important rule is to control the size of your losses. It may not be a consistently small amount, but it has to be under strict control based on the trading capital you have. The maximum size of a loss has to be something you can live with so that you will not be wiped out after a few bad trades or that you would not be able to trade afterwards.

Beginner Terminator – Increasing Stop Size

One of the well know pitfall in trading is volatility. When volatility increases, tight stops tend to be taken out quickly. Many traders will figure out that they have to adjust their stops to improve their odds in winning. That is wrong.

To properly adjust to bigger volatility, you cannot simply increase the stop size because it means without being aware of it, you are moving yourself from the better survival scenario (2nd chart) back to the one with way higher risk of failure (1st chart).

Instead, the first thing to do is to figure out if the potential setup is worth your while to take on the trading risk at all. If you cannot justify that the potential maximum loss on the trade based on your stop is at least smaller than the potential minimum profit you can get, it implies that you are betting on your setup to be better than 50/50 for that particular scenario.

If you are not sure about the odds (“sure” means you know either by hard numbers or from a successful career in trading that span many years), then simply pass the setup and look for a better opportunity because the markets you trade will still be there tomorrow, but taking on trades with negative expected outcomes implies your account may not last for long.

The Conservative Formula on Per Trade Risk and Initial Capital Requirement

Following is a very conservative formula that describe the relationship of initial capital and per trade risk.

Initial Capital x 20% X Acceptable Risk Per Trade (e.g. 1%) >= Average Loss

Given that,

Initial Capital x 80% > Margin Required

Thus if you know you are going to trade an instrument with the expectation that you are going to lose $100 on average per losing trade and your risk tolerance is 1%. Then the initial capital required is,

Initial Capital >= Average Loss / 20% / Acceptable Risk Per Trade = $100 / 0.20 / 0.01 = $50,000

By increasing the acceptable risk to 2%, the initial capital required drops down to $25,000

At 3% accepted risk, the initial capital drops further down to $16,666

It is not recommended to increase the acceptable risk to beyond 3% because it implies 3 times the likelihood you would kill your trading account quickly.

This formula works very well for both discretionary traders and mechanical traders.

For discretionary traders, as their trading performance fluctuates due to many factors, the formula can give them a guideline on how to control their position size based on accepted risk, not guess work or the unreliable statistics generated from the latest monthly statement.

For mechanical models, the capital requirement calculated by trading programs are determined by statistics generated from historical data, which does not take into account the potential of a trading model’s future performance in winning percentage could be drastically worse than expected. Thus using a conservative formula to determine the proper capital requirement is a better approach.

There is a lengthy discussion why the formula looks this way in my eBook Know your odds before you trade. I am not going to repeat it here.