# Thinking in probabilities

Updated: Jul 27

*5th January 2023*

This article is about thinking in probabilities and ties back to some work I showed previously about what can be achieved with a simple commitment to a series of __1:2 risk-to-reward trades.__

At the end of the day, what we do as traders is we play a probability game. We don't know what the outcome of any single trade will be beforehand, but we seek to try and identify setups that we believe will give us better than even odds of success.

In my experience, if you're getting 60% of your trades as winners, you're doing exceptionally well.

But even with a success rate below 50%, you can still make money in the markets if you are able to achieve an average return on your winners that is greater than the average loss on your losers. The key to this is that you MUST KEEP YOUR LOSERS SMALL. If there is a holy grail in trading, it is that cutting losses is at the heart of success. **The best loser wins**!

You need to go into each trade knowing that there are a range of possible outcomes, and you're essentially playing a probability game. Some trades are going to work out, and some are not. That's just how it is. When a loser comes along, cut it at a defined stop-loss level and move on. You're not going to win on all your trades, so accept that losses are a part of the business of trading, and they're the price of finding winners. Let the winners take care of themselves. You need to manage the losers. DO NOT RUN LOSING TRADES!

To illustrate the concept, I put together a spreadsheet a while ago that shows what is possible with a series of 100 trades with a 40% win rate and a 60% loss rate, and where you diligently achieve a 1:2 risk-to-reward ratio on winning trades, and where you risk 2% of capital on individual trades.

In the spreadsheet, I've assumed a starting capital of $100,000 (it could be 100,000 of whatever currency you choose). I assume each loser is capped at $2,000 (2% of capital) and that winners are locked in at $4,000 (4% of capital).

I've assumed that only 40% of trades work out as winners, while 60% end as losers. I've randomly distributed the wins and losses, and have ensured that there are a good few clusters of losses in the data set. To my mind, the way I've set this up actually leans quite negatively in terms of how there are more losers than winners (60 vs 40) and how I have leaned towards a number of losing clusters in the data set.

Notwithstanding this attempt to stress the data, it still shows that a return of 40% is possible after 100 trades.

The key is to accept the risk of 2% of capital on individual trades and to ensure that the losses are contained to 2% of capital. Allow winners to run to a point where they reach 4% of capital (1:2 RR).

This is actually so simple, yet it is not easy to achieve. Trading is simple, but not easy. If you can think in probabilities and not let your emotions get in the way, then trading success "should" be easy to achieve.

I'd challenge you at the start of 2023 to try this. Dedicate yourself to 100 trades where you act with total discipline. Look for high-probability setups. Risk 2% of capital on each trade and be disciplined about cutting losses. Take profits at 4% of capital (or run winners beyond that level if you wish) and see what happens. If you can do this with discipline, I guarantee you will be impressed by the results that are possible.