The goal is to take 3x the risk, so why does the realized profit only come out to 1.4x?
When you look at the chart, the target seems far away, but when you review the trade, the profit isn’t much. Sometimes it isn’t the entry that’s off—it's that most of the position was sold off early.
Here’s a hypothetical example: treat the loss of the initial whole position when exiting at the planned stop-loss as 1R. When price reaches the profit level of 1R, close 80% first; then close the remaining 20% at the 3R level. Ignoring fees, the total actual profit from the entire position is 0.8×1R + 0.2×3R = 1.4R, and it cannot be recorded as making 3R.
If the remaining 20% eventually comes back to the original stop-loss level and you exit there, using the same assumption for fills, the result would be 0.8R − 0.2R = 0.6R. Exiting in batches changes not only the distribution of returns, but also how you feel when drawdowns/retracements happen.
I won’t judge whether batch take-profit is good or bad based only on these two outcomes. Pre-committing partial profits may improve execution consistency, but it can also mean that a small number of big winners don’t make up for other losses. You need to compare the full results of the same set of trades under different exit rules—not just pick a few pretty examples.
CME’s Trading Mathematics course emphasizes how average profits and average losses affect a strategy’s outcome. When I review BTC, ETH, and SOL, I log each exit’s proportion, execution price, and fees. The target price is part of the plan; only the profit weighted by position size belongs to your account.
The second image is a screenshot of trade scenario materials, not my live trading record.
#Trading Review
$BTC $ETH $SOL
Tap my profile picture to view the live execution with orders
When you look at the chart, the target seems far away, but when you review the trade, the profit isn’t much. Sometimes it isn’t the entry that’s off—it's that most of the position was sold off early.
Here’s a hypothetical example: treat the loss of the initial whole position when exiting at the planned stop-loss as 1R. When price reaches the profit level of 1R, close 80% first; then close the remaining 20% at the 3R level. Ignoring fees, the total actual profit from the entire position is 0.8×1R + 0.2×3R = 1.4R, and it cannot be recorded as making 3R.
If the remaining 20% eventually comes back to the original stop-loss level and you exit there, using the same assumption for fills, the result would be 0.8R − 0.2R = 0.6R. Exiting in batches changes not only the distribution of returns, but also how you feel when drawdowns/retracements happen.
I won’t judge whether batch take-profit is good or bad based only on these two outcomes. Pre-committing partial profits may improve execution consistency, but it can also mean that a small number of big winners don’t make up for other losses. You need to compare the full results of the same set of trades under different exit rules—not just pick a few pretty examples.
CME’s Trading Mathematics course emphasizes how average profits and average losses affect a strategy’s outcome. When I review BTC, ETH, and SOL, I log each exit’s proportion, execution price, and fees. The target price is part of the plan; only the profit weighted by position size belongs to your account.
The second image is a screenshot of trade scenario materials, not my live trading record.
#Trading Review
$BTC $ETH $SOL
Tap my profile picture to view the live execution with orders
