Tag Archive for: Targets

Should you take profit or let your trade run?

Should You Take 1R or Let It Run?

Most new traders focus almost entirely on entries. They refine confirmations, tweak structure rules, and optimise timing. But very quickly you realise something more important. Your exit strategy determines your expectancy.

Let’s walk through a clean example using simple numbers. No complicated formulas. Just clear logic.

We will assume the same core distribution throughout so every strategy is compared fairly.

The Starting Distribution

Across a large sample of trades:

  • 40% lose and hit full stop at -1R
  • 30% reach 1R but fail to extend further
  • 30% extend beyond 1R and can reach 1.5R

This is the raw behaviour of your system before deciding how to exit.

Now let’s compare four exit strategies using this same base data.

Strategy 1: Fixed 1R Take Profit

In this model you close the entire position at 1R. No partials. No trailing. No runners.

Using the base distribution:

  • 60% of trades reach at least 1R
  • 40% lose -1R

So expectancy is:

  • 60% × +1R = +0.60R
  • 40% × -1R = -0.40R

Total = +0.20R per trade

This is clean and efficient. Your edge here is accuracy. You monetise the fact that most trades reach 1R.

Strategy 2: 50% Partial at 1R, Runner to 1.5R

This is the classic hybrid approach.

When price hits 1R:

  • Close 50% for +0.5R
  • Move stop to break even

If the trade extends to 1.5R:

  • Remaining half earns +0.75R
  • Total win = +1.25R

If price reverses after 1R:

  • Remaining half stops at break even
  • Total win = +0.5R

Using our distribution:

  • 30% hit 1.5R → +1.25R
  • 30% stall after 1R → +0.5R
  • 40% lose → -1R

Now calculate:

  • 30% × 1.25R = +0.375R
  • 30% × 0.5R = +0.15R
  • 40% × -1R = -0.40R

Total = +0.125R per trade

Still profitable. But lower than the simple 1R model.

Why? Because only 30% of trades meaningfully extend. The runner frequency is not high enough to compensate for halving position size.

Strategy 3: Full Position Runner to 1.5R

Now we remove partials. The entire position aims for 1.5R.

If price reaches 1R but fails to continue, you move stop to break even and make nothing.

Distribution becomes:

  • 30% hit 1.5R → +1.5R
  • 30% reach 1R but reverse → 0R
  • 40% lose → -1R

Expectancy:

  • 30% × 1.5R = +0.45R
  • 30% × 0R = 0
  • 40% × -1R = -0.40R

Total = +0.05R per trade

You increased reward size but reduced realised wins. That trade off reduced expectancy.

Strategy 4: Structure Based Trailing

Now we remove the artificial 1.5R cap. Instead of targeting a fixed multiple, you trail behind structure and allow the market to decide.

To keep assumptions realistic, let’s use this distribution:

  • 40% lose → -1R
  • 30% reach 1R and then stop at break even → 0R
  • 20% trend moderately → +1.5R
  • 10% become strong runners → +2.5R

Now calculate:

  • 20% × 1.5R = +0.30R
  • 10% × 2.5R = +0.25R
  • 30% × 0R = 0
  • 40% × -1R = -0.40R

Total = +0.15R per trade

This improves on partials and fixed 1.5R runners, but still does not beat the simple 1R model under these conditions.

Comparing All Four

Using consistent assumptions:

  • Fixed 1R → +0.20R
  • Partials + 1.5R cap → +0.125R
  • Full 1.5R runner → +0.05R
  • Structure trailing → +0.15R

Under this distribution, the simplest strategy wins.

What This Teaches a New Trader

Risk reward ratio alone means nothing. A 1:1.5 target is not automatically superior to 1:1. What matters is how often price actually extends.

Your optimal exit depends on the behaviour of your market.

In rotational conditions:

  • Moves stall quickly
  • Pullbacks are deep
  • Extensions are limited

That profile favours harvesting 1R consistently.

In strong trending conditions:

  • Pullbacks are shallow
  • Structure stair steps cleanly
  • Large extensions are common

That profile favours structure based trailing and uncapped runners.

The mistake is using the same exit logic in both environments.

How to Decide With Data

Track one simple metric over your next 50 trades:

Maximum favourable excursion measured in R.

If most trades rarely exceed 1.5R before reversing, fixed 1R exits are likely optimal.

If a meaningful percentage regularly reach 2R or more, you may be capping your distribution too early.

The goal is not to maximise reward on a single trade. The goal is to optimise your overall distribution.

Sometimes the ordinary 1R is the most efficient solution.

Sometimes the market is offering a trend and you need to step aside and let it pay you.

The numbers will tell you which environment you are in.

The hardest skill in trading is knowing when you’re done for the day.

I used to think the hard part of trading was finding good entries.

It isn’t.

The hardest part is knowing when to stop.

Most of my worst trading days didn’t start badly. They started fine. A clean first trade. Sometimes even a small win. Enough to feel engaged, alert, involved.

And then that quiet thought appears.

There’s probably another one.

Sometimes the trigger is a loss. You feel sharp, focused, convinced you can get it back. Other times it’s a win. Confidence creeps in. You feel aligned with the market, like you’ve found the rhythm.

Both states are dangerous.

The market doesn’t know how your day is going. It doesn’t care if you’re up, down, or flat. Every trade is a new decision, but your state of mind carries forward whether you want it to or not.

What I eventually realised is this: stopping isn’t about discipline. It’s about self-awareness.

The real question isn’t whether another setup exists. It’s whether I’m still trading the plan, or trading the emotional residue of the last trade.

Some days I stop after one trade. Not because the day is “done,” but because I am. Focus softens. Patience shortens. I start justifying trades that look acceptable rather than obvious.

That shift is subtle. And once it happens, it rarely reverses.

I still have clear rules for entries. But I also have rules for exiting the day. Daily loss limits. Maximum number of trades. And one rule that’s harder to quantify but easier to feel.

My emotional tone.

If I feel rushed, reactive, or slightly irritated, I’m finished. Even if the chart still looks clean. Especially if it does.

That’s the uncomfortable truth most traders avoid. Overtrading usually doesn’t come from desperation alone. It comes after we’ve already had enough. Enough information. Enough opportunity. Enough exposure.

We just don’t want to admit it.

The best traders I know don’t trade more. They trade less. They treat mental capital as something that can be depleted, not ignored. Protecting it matters more than squeezing another trade out of the session.

Some of my most profitable weeks include days where I stopped before noon. No revenge trades. No boredom trades. No “just one more” because price happened to be moving.

Walking away early never feels productive. It feels unfinished. Like leaving something on the table.

But trading isn’t about finishing the day. It’s about returning tomorrow with clarity intact.

Knowing when you’re done for the day won’t show up on a chart. There’s no indicator for it. But it’s one of the few skills in trading that compounds quietly, day after day.

And once you learn it, everything else gets easier.