Despite an abundance of proper information out there, the misconception that a high win rate is mandatory to make money trading stocks, is unwilling to die. Traders also struggle to set a reasonable risk per trade. In this article I will show you how your real world win rate allows you to calculate the correct maximum risk per trade.

Per definition, the win rate or hitting percentage is the percentage of trades closed at a profit. Aspiring traders often assume that a good trading system must have a high win rate while in reality this is simply not the case. It is almost impossible for new traders to find, or better yet identify, a proper trading system when they focus their attention on those with the highest win rate. The logic is simple, a system which closes trades at a profit 99% of the time must make you money over time, right?

Well, in reality such win rates are often achieved by following ill-advised behaviour such as averaging down or exiting trades at scratch wins slightly above breakeven. Averaging down, such as the case in a Martingale approach, creates a lot of small wins with the potential of experiencing a huge loss once the strategy fails. It’s like picking up pennies in front of a steamroller, once you slip it’s pretty much game over. Such systems are the perfect sales pitch. Closing out trades slightly above break even is also bad practice. It is much better to either allow a trade to hit your stop or profit target. Once you start setting logical stops, a stop loss hit becomes pecious feedback. The stock displayed weakness which renders the trading idea invalid. And it is the other way around with the price target. In between you must give the stock some room to move freely.

CONTENTS

## Each R-multiple (Risk Reward Ratio) comes with a minimum required win rate

The win rate is just one of the parameters which define risk and expectancy of outcome of your trading system. Your risk per trade (Stop loss) and the desired profit to risk ratio of your wins are equally important. A good way to classify various trading approaches is via a multiple of risk or short R-multiple. A 3R trade means that you aim to make a profit of at least 3 times your initial risk. If you are willing to risk 1.2% of your account balance per trade a 4R win equals a profit of 4.8%. If you run such a system you need a specific win rate in order to be profitable.

From the graph above it is clear that a perfect 3R system needs a winrate of >25% to make you money. If you are fine with winning less than what you risk per trade, or in other words running a <1R system, you would need a much higher win rate of above 50%.

Each combination of risk-multiple and breakeven win rate which follows the curve in the graph above represents a valid approach to the markets.

## Exploit the windows of opportunity for your setups

The foundation of each trading system are the setups you are running. Depending on your setup you likely have a different risk multiple of wins which you can nauturally achieve over time. If you are a growth stock or momentum swing or position trader you are bound to the typical waves or cycles of such stocks. Most growth stocks have swings of roughly 15 to 25% between consolidation areas. Each stock idea starts with evaluating proper stop loss and profit targets (R-Multiples) from the chart which then yield you a reasonable position size. Over time you will realize that most setups are best run with risk multiples between 1R and 4R, at least that is the case for all the setups I’ve been using over the years:

• Base breakouts
• Pocket Pivots
• Wyckofian retests
• Undercut and rallies
• Momentum gaps
• Quiet and tight pullbacks

There is no setup which has a constant win rate over time, they all fulfill a purpose and allow us to trade with en edge in a specific environment. Momentum gaps during earnings season, Undercut and rallies and Wyckofian retests during corrections and big market breaks, Quiet and tight setups and Pocket pivots on pullbacks in an uptrend. It is very important to only focus on the respective setups when the time is right in order to keep up the desired win rate. The setup specific win rates in the graph below are just a schematic representation to illustrate this idea. If you try to trade each setup all the time it will greaty impair your win rate.

In real trading there is no need for time dependent specific screening because when you do your normal routine and don’t search too hard for setups you will only find proper ones anyway. This means you’ll find proper quiet & tight pullbacks during regular pullbacks in a rally, earnings gaps early during earnings season and undercut setups after sell-offs. However if you try to find one stock for each setup all the time you are clearly forcing it and as a result you’ll trade out of sync as the winrate of that setup might be lowered in the current environment.

Your overall break even win rate across the aforementioned setups will land somewhere between 20% and 50% in real trading according to my experience. It often fluctuates between those percentages as the market environment transitions from one phase to the other, each with a favourable setup to trade. Earnings gaps have the highest winrate for me as I make sure to only trade the early and most scary ones.

## Probability of loosing streaks and drawdowns

Now that the direct relationship of R-multiple and win rate is clear, we have to dig a little deeper.

Depending on your R-multiple (win rate), game theory tells us that there is a certain probability that a losing streak will occur. Or in other words, there is a maximum losing streak that will likely show up when you make a specific number of trades. The numbers of trades or trading opportunities are simply the inverse of the that probability. The following graph shows that probability and the respective drawdown for a 3R system (25% winrate) when you risk 1.2% of account balance per trade.

Be aware that [ opportunities = 1/ probability decimal ].

So there is a specific probability of a losing streak happening which leads to a portfolio drawdown. The win rate determines the probability and the risk per trade determines the drawdown. So in practice it is much more convienent to directly link probability and drawdown as shown in the graph below:

The conclusion from that graph is that a 1R system is always better than a 2R system and a 2R is better than 3R and so on. This is true as the probability of a given losing streak and thus a deeper drawdown increases with the risk multiple of wins. From the graph it is clear that a 1R system has a 10% probability (equals 10 trading opportunities) of a 5% drawdown while a 4R system has a 10% probability of a 15% drawdown. If you run both with the same risk per trade (here 1.5%) the latter would create much larger drawdowns in real trading and thus can be seen as the more risky system.

The gain needed to recover from drawdowns can become enormous at higher levels as obvious from the following graph.

A portfolio drawdown of 5% requires a gain of 5.26% to get back to break even. A 15% drawdown already requires a gain of 17.6%. To dig your way out of a 60% hole you have to make a killing (150%). You see that it is a necessity to keep your drawdowns in check.

## How to calculate a reasonable maximum risk per trade

So a reasonable maximum risk per trade for your individual system can be calculated when the win rate and your trading opportunities per year are know or can be estimated.

Max Risk % = 100* {1 – EXP [ (Ln (1/(1-Drawdown)) * Ln (1-Win rate)) / Ln (Opportunities) ]}

Variables:

Drawdown as decimal (example: 0.2 decimal means 20%)

Win rate as decimal

Opportunities as a whole number

Ln is the natural logarithm (Can be calculated in MS Excel or a similar tool)

EXP is the e-function eX

Imagine you want to trade in a way that your maximum drawdown during the year doesn’t exceed 20%.

Now let’s assume the win rate of your system has been around 38% in real trading.

You also know that your system typically gives you roughly 333 trading opportunities per year.

In that case your variables are as follows:

Drawdown = 20% = 0.2 decimal

Opportunities= 333

Win rate = 38% = 0.38 decimal

The equation now tells you how much you should risk per trade so that you don’t lose more than 20% when the largest likely losing streak, for your amount of trading opportunties, hits you.

Max Risk = 100* {1 – EXP [ (Ln (1/(1-0.2)) * Ln (1-0.38)) / Ln (333) ]} = 1.82%

For that system one should not risk more than 1.82% of the account balance per trade if the max drawdown must not exceeed 20% in real trading.

Here are my own numbers for just the quiet & tight setup (#QTS) (I track each setup individually and thus have variying max risks)

## Putting it all together

Once you have your maximum trade risk calculated that way you can use it to determine a reasonable position size with the help of a logical bottom up position sizing technique. In real trading you have to account for single stock black swan events so there is a real chance that events can happen which violate your maximum trade risk. However the max risk calculated by the equation outlined above will be alright. If you are not sure you can just double or triple the opportunities to even account for the extrmely unlikely losing streaks.

It is clear from the equation and graph above that a 1R or even 0.5R system is superior to a 2R or even 3R system due to the higher win rate which allows to go with a lower risk per trade.

So the question is why don’t we just trade that way?

As a matter of fact it is very hard (impossible) to find setups with a win rate above 50% even if you try to gain less than what you are willing to risk (<1R). Chances are high that there simply is no price setup which works more than 50% of the time and occurs frequently enough to make you money.

It is much more easy for us traders to pick something with a lower win rate even if it means that you need to gain a multiple of the risk on each trade. Once a stock is fast growing and making progress on the s-curve (technological adoption) thus gaining market share, it develops a trend which lasts for a while. This trend allows us to trade 3R or similar systems profitable despite having a low win rate. It also is much more in sync with how the market operates as we can capture most of the price progress between consolidation areas with reasonable stop loss levels.

I am not sure of you noticed this but it is the very definition of trend following. You try over and over again and the trend allows you create a winning system with just the few trades which have a real price expansion. Whenever you trade with a win rate below 50% aka a risk multiple above 1R you are practically a trend follower in almost all cases, if you like it or not.

Here’s how this all translates to real stocks trading:

1. You find a nice chart with good fundamentals
2. You check if the stock yields a proper risk multiple by evaluating proper stop loss and profit target levels
3. You trade that setup for a while with a very low risk per trade and try to exit trades at either the stop loss or goal R-multiple, avoiding break even trades or scratch wins. Proactive scale-outs into strength anyone?
4. You check if you can trade this setup profitable via the real R-multiple and win rate and if there is enough cushion before it would turn unprofitable. Don’t let a bad setup unknowingly dilute your overall performance.
5. Once you have an idea of the win rate you can increase the mximum trade risk up to a reasonable amount via the equation in this article.
6. You do this for all setups individually and you only trade the best of them. Less is more.

## Are those techniques really needed to win the game that is the stock market?

Are you overwhelmed now and not sure if all that effort towards win rate and maximum trade risk is really needed to make it? The stock market is an extremely competitive environment and the following analogy could help you better understand the importance of my various stock market techniques.

The game of basketball evolved a lot and the NBA (National Basketball Association) always had a fable for statistics. I’d say there is no other game in the world which is optimized and supported by statistics like the NBA is today.

The very basic is that each offensive player has sweet spots from where the odds of a made field goal increase above their average. If you want to win you have to make sure that each player only shoots the ball from their sweet spots. However you can’t just stand at that spot waiting for the pass to score an easy basket. Defenders of the opposing team will challenge the shot and they will certainly try to force the player in a position far away from their statistical sweet spot.

To draw the analogy to trading you have to realize that the offensive players are your setups each with a preferred sweet spot. If the player shoot whenever and wherever he gets the ball, his overall field goal percentage (win rate) will suffer big time.

The defenders of the opposing team try to make sure that we lose by forcing us to take bad shots over and over again. In trading the opposing team is represented by the market or in other words, the collective mind of all participating traders.

In order to win the game you must develop the skills to get the ball at the right time in the right spot (market timing) and then shoot and release with proper form automatically from muscle memory (technical execution of trades). Once the ball is in the air torwards the basket you can’t do anything to influence the outcome anymore (sit tight in your trade and let the market do the magic). However you should not freeze but go and try to position yourself for the rebound and thus increasing the odds of another proper follow up shot (Exit trade at stop loss and position yourself to try again on the next proper setup).

If you do all this you will hear that satisfying swoosh sound more regularly and as a result you will start to win games eventually.

But never forget that defense is the best offense, so make sure to play hard on the defensive end as well.

If you want to win in the game of stocks you better bring your A-game.