If there is a key concept that leads to trading success, it’s the understanding, integration and application of the Expectancy Return:
(Average Dollar Win x Win Rate) – (Average Dollar LosS x Loss rate)
- A$Win = the average of the dollars won in our winning trades
- Win Rate = the total number of winning trades/sum total of all trades
- A$Loss= the average of the dollars lost in our losing trades
- Loss Rate = the total number of losing trades/sum total of all trades
The reason why the formula is important is because trading is a probability game. We don’t know what will happen; we make best guesses and create scenarios that are neutral, scenarios that favour our trade and scenarios that are unfavourable. Even then, the fact that a scenario is favourable in any particular trade does not mean that for that trade we will be successful. If we have an edge, it will mean that over a large sample size, we will have a positive return.
That edge is expressed in the Expectancy Return.
There are certain key elements we need to bear in mind:
- The Win Rate alone means little. A trader can have a Win Rate of 90% and still produce a negative expectancy. Let’s say a trader has a 90% Win Rate, and an average dollar win of $10; and he has an average dollar loss of $100. Given these numbers, the trader will lose over time.
- The important relationship is the relationship of the two sides of the equation. The greater the difference between the average dollar win over the average dollar loss, the lower the Win Rate can be over the Loss Rate.
- Generally, the shorter the time frame, the higher the Win Rate, and the lower the average dollar win. Successful scalpers, for example, produce a high win rate with a lower dollar win punctuated by some very large losses that happen infrequently.
- Since we are unsure of what the future will bring, the standard by which to judge when to take profits is governed by our stop loss, our expectancy return and our Maximum Adverse Excursion.
This brings me to my final point. It’s important to keep records and statistics of our trading. Without them it would be impossible to maximise our return. For example, let’s say you consistently use 40 points stops and take 17 points profits; and let’s say that while you have not lost your shirt, you are exactly making a fortune.
To work out what you need to change means you need data. You need to know the frequency distribution of your profits and losses and of course the win and loss rates. Armed with this information, you will be able to judge whether you would be better off taking fewer profits i.e. letting the profits run and have fewer winners and more frequent losses; or reduce the size of the stops, have more frequent but smaller losers etc. The point is we need information in the form of records to make an informed decision.