You should use a stop loss on every trade you ever place. You should have this protective stop in the market at all times - Good Till Cancelled (GTC). If you do not, there’s a damn good chance you’ll face financial ruin.

Let’s run some experiments in excel in the trading universe, to illustrate why you should use a stop loss always, on every trade you ever take.

Lets assume you traded whatever you wanted, and didn’t use a stop loss at all. And you completed 50, 100 or 200 or even 1000 trades. (In the real world you can’t afford to do this - the drawdown and risk of ruin will kill you.) Do NOT do ever trade this way!!!

If your exit strategy was half arsed or had say no strategy at all, you would probably get some big wins, some big losses and lots of trades around the mean, around breakeven.

Using the random number generator in excel we can run this experiment. We did so and recorded 1000 fictional trades.

From this record of 1000 trade results, we then did a bin analysis in excel as Akram Najjar shows in his books “Practical Monte Carlo Simulation with Excel”.

And by following Akram’s methods you might come up with a Pareto chart for the no-stop-loss case, something like this:

On this Pareto chart, the histogram, shows you had some big win trades, some big loss trades, and lots of trades in the middle. Also from the Bin Analysis you can calculate the % Cumulative / Cumulative Frequency Distribution as shown by the orange line.

You should also use the Descriptive Analysis Pack in excel, generate and then review it’s output:

But you are not done yet, you need to calculate your specific trading statistics from this set of trades as well:

These statistics then summarise your no-stop-loss trading performance. Note that:

• your average wins and losses are similar, borne out by the Win/Loss ratio about 1.0,
• your % wins are about 50%, and
• your overall performance is about breakeven (a small loss per trade in this example).

You can then also use the Pareto Chart statistics / table in a Monte Carlo simulation to look at your probabilistic future if you blindly went ahead in this fashion for the rest of your career.

So let’s run that Monte Carlo simulation assuming a starting equity of $25,000, and using 0.5% risk per trade. What’s your probabilistic future universe look like?

Well its bleak, with financial ruin your fate. You have P95 maximum Drawdown of 61.8%. I.e. One of your next 20 years will be this bad. If you experienced 61.8% drawdown this would require you to back that up with a 162% return to get back to breakeven. It’s probably safe to assume you may not be that trader.

Additionally, most likely your Compound Annual Growth Rates will never be positive at all, i.e. negative, with a P5 = -13.8% and P50 of -1.9%. The probability of you making no money / no profit at all ever is over 58%.

If this set of no-stop-loss trades represents your future then you have no future, and it’s entirely likely you’ll face financial ruin in leveraged products. You will be doomed to failure, and will become just another statistic in the long list of traders that went bust.

So where to from here?

The Case for a Stop Loss

Well, use a stop loss. Let’s take the same distribution of results, but let’s trtuncate / cap every loss at -1R, negative one unit of R.

Using Akram Najjar books “Practical Monte Carlo Simulation with Excel” we generate a new Pareto Chart. And by moving all those big loss trades into the -1R Bin, your new Pareto chart now looks like this.

Your descriptive statistics output then calculates out as being:

And your trade statistics calculate to the following:

Now take a close look. You now have a positive expectancy trading system with:

• Your win to loss ratio is much healthier at almost 2.
• Your average expectancy is better at 0.37 R per trade.
• And your % wins are still about 50%. (Sorry can’t fix everything!)

As a trader you want your trading results distribution to have fat right hand side tails. The 1R stop loss distribution pushes towards this. Note that you have much better kurtosis and skewness by using a 1R stop loss. (see Howard Bandy’s books for further discussion on trading statistics).

So now let’s run that Monte Carlo simulation again, using our 1R stop loss scenario this time, assuming again a starting equity of $25,000, and using 0.5% risk per trade. What’s your probabilistic universe look like?

Well it improves a lot. Your P95 maximum Drawdown is now -8.4%. This requires you to back that up with only a 9.2% return to get back to breakeven. And that 9% return back to breakeven is much more likely with your P5 and P50 values of CAGR being positive (and much better than your maximum drawdown).

Side by Side Summary - 1R Stop Versus No Stop Loss

So here’s how these two scenarios line up against each other:

Which column do you want to live in as a trader: the no-stop-loss one, or the 1R stop loss column?

Use a stop loss always – cap all your losses at 1R always. Move all those potential big losses trades into the -1R bin!!!

But before you go out there and assume a 1R stop loss will save you from anything you do in the markets, and anything the market throws at you – think again. It may not be so.

Your long term trading performance & results are directly dependent upon the distribution of your trades - not our fictional ones.

If your trading performance has a negative expectancy, and/or doesn’t have a high enough win/loss ratio, and/or too many losers (too high % losses), the probability of success will become stacked against you again - even with a -1R stop loss in use. Financial ruin may still be your fate even with a 1R stop loss.

If you risk too much of your trading equity on every trade (% per trade), you may also face financial ruin.

Good trading risk management is more complicated than just using a 1R stop loss GTC. It’s only the first step - but it is a critical one to embrace.

To get you thinking: to stand a chance of success, your performance target should perhaps be the trading license conditions that Chris Shea sets out in his book “Licensed to Profit”. You may want to consider Chris’ recommendations.

More later.

Trade small to survive.

And if you have questions - send us an email, or contact us on BlueSky (here).