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.