Research / educational post on (1) payout handling A-vs-B and (2) position
sizing sensitivity, on a $1,500-target / $1,000-DD / $1,000-payout / $240-cost
account, using real ORB-fade strategies as the worked example.
On a small prop account, two decisions matter more than your strategy’s win rate: how you handle payouts, and how big you trade. We ran the full simulation on real data — the payout-handling choice swung net profit by up to 69%, and position sizing revealed a clear sweet spot where you keep ~84% of the maximum profit with a quarter of the capital and zero blown accounts. Here’s the math.
⚠️ Read this first
Prop-firm trading carries real risk and every firm’s rules differ. The numbers below are a historical simulation on past data — not a promise of future results, and not financial advice. The single most important variable is whether your firm freezes the trailing drawdown after a payout. If it does not, the “keep the account” approach described here does not work the same way. Read your firm’s rules carefully before applying any of this.
Two traders run the same strategy on the same prop account. One nets $8,920; the other nets $15,040. Then a third trader, trading the same strategy at a smaller size, nets “only” $12,760 — but does it with a single $240 account and never blows one, while the $15,040 trader burned through four accounts. On a small prop account, two decisions shape your result more than your win rate does: how you handle payouts, and how big you trade. This post works through both on real data.
The account we’re modelling
- Account cost: $240
- Profit target: $1,500 (unlocks withdrawals)
- Payout size: $1,000 per withdrawal
- Trailing drawdown: $1,000 from the highest end-of-day equity
- After a payout: the trailing drawdown freezes and restarts from the post-withdrawal balance
That last rule — the freezing drawdown — is what makes everything below work. When the drawdown freezes after a payout, a withdrawal doesn’t “use up” the account; it resets its risk budget to that of a fresh account, for free.
PART 1 — How you handle payouts
Approach A — take the payout and abandon. Trade to the $1,500 target, withdraw $1,000, walk away, buy a fresh $240 account. The common reasoning: “after pulling $1,000 there’s too little buffer left, so start fresh.”
Approach B — take the payout and keep going. Let equity reach $2,000, withdraw $1,000 (balance drops to $1,000), and because the drawdown freezes and restarts from $1,000, the account again has a full $1,000 of room beneath it. Keep trading the same account, taking payout after payout, and only buy a new one when an account actually blows.
The instinct behind Approach A is wrong under a freezing drawdown: after a payout, your account is mechanically identical to a brand-new one — except you didn’t pay $240 for it.
Results — same strategies, two payout approaches
Using two tracked ORB-fade strategies, normalised to fixed dollar amounts (win +$200 / loss −$240 for the half-target versions; win +$380 / loss −$240 for MGC full target), one trade per day:
| Strategy | Approach | Accounts | Payouts | NET |
|---|---|---|---|---|
| FDXS half | A — abandon | 5 | 4 | $2,800 |
| FDXS half | B — keep | 2 | 4 | $3,520 |
| MGC half | A — abandon | 12 | 9 | $6,120 |
| MGC half | B — keep | 3 | 11 | $10,280 |
| MGC full | A — abandon | 17 | 13 | $8,920 |
| MGC full | B — keep | 4 | 16 | $15,040 |
Approach B wins everywhere — by +26% (FDXS), +68% (MGC half), and +69% (MGC full). Two mechanisms drive it: you stop paying for accounts you don’t need (MGC full: 4 accounts instead of 17), and a good account keeps paying multiple times instead of being thrown away after one withdrawal.
PART 2 — How big you trade
Payout handling is only half the picture. The size you trade — relative to the $1,000 drawdown — decides how often an account blows, and that changes everything. The key number is what we’ll call “losses-to-blow”: how many consecutive losses from the equity peak it takes to hit the drawdown limit. It’s simply $1,000 ÷ your loss size:
| Size (win / loss) | Losses-to-blow | Safety |
|---|---|---|
| +$100 / −$120 | 8.3 | Very safe |
| +$150 / −$180 | 5.6 | Safe |
| +$200 / −$240 | 4.2 | Medium |
| +$250 / −$300 | 3.3 | Risky |
| +$300 / −$360 | 2.8 | Very risky |
We ran the best strategy (MGC full target, Approach B) across these size levels. The win amount scales with size, keeping the strategy’s natural reward-to-risk ratio:
| Size (W/L) | Losses-to-blow | Accounts | Payouts | Blown | NET | ROI on cost |
|---|---|---|---|---|---|---|
| +$190 / −$120 | 8.3 | 1 | 8 | 0 | $7,760 | 32.3x |
| +$285 / −$180 | 5.6 | 1 | 13 | 0 | $12,760 | 53.2x |
| +$380 / −$240 | 4.2 | 4 | 16 | 3 | $15,040 | 15.7x |
| +$475 / −$300 | 3.3 | 6 | 22 | 5 | $20,560 | 14.3x |
| +$570 / −$360 | 2.8 | 10 | 24 | 9 | $21,600 | 9.0x |
What the size scan reveals
1. There is a risk cliff between 5.6 and 4.2 losses-to-blow. At the two smallest sizes (8.3 and 5.6 losses-to-blow), no account ever blew across the entire sample — the worst losing streak never reached the limit. From +$200/−$240 onward (4.2 losses-to-blow), accounts start dying. That transition is where the small-account model flips from “essentially un-blowable” to “expect to lose some accounts.”
2. Absolute profit keeps rising with size — but ROI collapses and accounts start burning. Going from +$190/−$120 to +$570/−$360 lifts net profit from $7,760 to $21,600 (+178%), but the return on the money you spend buying accounts falls from 32.3x to 9.0x, and blown accounts go from 0 to 9. You’re buying more absolute dollars by paying with far more risk and far less efficiency.
The sweet spot: +$285 / −$180
The standout configuration is +$285 / −$180 — about 1.4x the smallest size:
| Metric | +$285/−$180 (sweet spot) | +$380/−$240 (max profit-per-account) | +$570/−$360 (max absolute) |
|---|---|---|---|
| Net profit | $12,760 | $15,040 | $21,600 |
| Accounts bought | 1 | 4 | 10 |
| Accounts blown | 0 | 3 | 9 |
| ROI on account cost | 53.2x | 15.7x | 9.0x |
| Ruin risk | Very low | Medium | High |
At +$285/−$180 you capture roughly 84% of the maximum profit-per-account configuration’s net result, but with a quarter of the capital tied up in accounts and — critically — zero blown accounts in the sample. The 5.6 losses-to-blow margin was never breached. It is the cleanest balance of return and survival in the whole scan.
Putting both decisions together
The two findings compound. Approach B (keep the account) only reaches its full potential when accounts rarely blow — and accounts rarely blow when your size keeps losses-to-blow high. So the ideal small-account setup is:
- Confirm your firm freezes the drawdown after payout. Without this, neither finding holds. Verify it in writing before risking anything.
- Size so that losses-to-blow is at least ~5–6. That keeps you on the safe side of the risk cliff. With a $1,000 drawdown, that means a loss of roughly $170–180 or less. Above that, expect to start burning accounts.
- Use Approach B — keep the account, let it pay repeatedly. Under a frozen drawdown plus a safe size, a single account can produce a dozen-plus payouts without ever blowing. That’s where the 50x+ ROI on account cost comes from.
- Pick a strategy with fast payout speed. A higher reward-per-trade reaches the target in fewer trades, producing more payout cycles. The full-target version beat the half-target version despite a lower win rate, purely on cycling speed.
- Resist the urge to size up for bigger absolute dollars. The scan is unambiguous: pushing size lifts gross profit but destroys ROI and survival. More absolute dollars at 9x ROI with 9 blown accounts is a worse business than fewer dollars at 53x ROI with zero blow-ups.
The bottom line
On a small prop account with a freezing drawdown, your net profit is decided by two levers most traders never quantify. Payout handling alone is a 26–69% swing — keep the account, don’t abandon it. Position size sets your survival: stay on the safe side of the risk cliff (losses-to-blow around 5–6) and a single account can pay out a dozen times over without ever blowing, at 50x+ return on its cost. The temptation is always to size up for bigger headline numbers, but the math says the opposite: the most profitable small-account business is the one that survives, cycles, and compounds — not the one that swings for maximum dollars and burns accounts doing it.
The complete trade-by-trade simulation, with equity curves for every account under both approaches, and the full size-sensitivity scan, are in the downloadable spreadsheet accompanying this post.