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What lot size gives the best odds of passing?

Enter your edge — win rate, reward:risk, trades a day — and pick your firm, or set custom rules for any challenge. We run thousands of simulated attempts against its real daily-loss and max-drawdown rules, then show the risk per trade with the highest pass odds — and the leaner size that gets you nearly the same for less blow-up risk.

§ Monte Carlo engine·8 challenge presets·Scroll to model
FTMO·daily 5%max 10%target 10%
Firm DD model
Fixed floor from the start balance.

Translate to lots · optional

Use my real trades · block bootstrapOpen

Paste your real per-trade results in R (a 2.3R winner, a full -1 loss, a -0.6partial, and so on). The sim resamples them in blocks so your actual losing streaks stay intact, instead of assuming every trade is independent. The win rate and R above are read from these while they’re here. 8+ trades needed.

Best odds to pass
1.10%per trade
≈ $1,100 risk · 1.10 lots
82%
Pass
0%
Daily breach
11%
Max breach
Leaner · ≈ same odds
0.90%per trade
≈ $900 risk · 0.90 lots
79%
Pass
0%
Daily breach
8%
Max breach

Risk 1.10% (~$1,100) per trade gives the best raw odds — 82% of simulated attempts pass. But you don't need to size that big: 0.90% (~$900) passes 79% of the time — nearly the same — for less blow-up risk. Over-sizing rarely buys better odds; it mostly raises the chance of a breach.

Best-odds pass rate is 82% on your point estimate, 13% at the low end of a 50-trade sample. The tighter that gap, the more your sample backs the number.

Pass odds vs. risk per trade

Every size from 0.1% to 3% of the account, 3,000 simulated attempts each.

PassDaily breachMax breach
0.1% risk3.0% risk

§ Next step

Run this on your real trades, automatically.

You just sized one edge by hand. TradeTrove logs every trade, tracks your live daily-loss across a real challenge, and re-runs this Monte Carlo on your actual results — across FTMO, The5ers, FundingPips, FundedNext and Alpha Capital.

Start a free 14-day trial

§How this works (and what it can’t do)

We walk calendar days against the firm’s real rules — the daily-loss limit resets each morning, the max-drawdown floor sits static or trails your peak, and the profit target only counts after the minimum trading days. Sweeping risk per trade from small to large traces the trade-off: too small and you run out of days before the target; too large and you breach. The peak of that curve is the sweet spot.

By default each trade is an independent draw on your win rate, which understates reality — real losing streaks cluster and hit the floors harder than scattered losses do. Paste your actual results and it switches to a block bootstrap, resampling your sequence in chunks so those streaks survive; treat the independent-draw odds as the optimistic end. Because the block length is itself a free parameter, we sweep it and report how pass odds move rather than commit to one. The sample-size field widens a confidence band around the answer, and the firm DD model control lets you model a trailing account — intraday-peak (stricter) versus end-of-day.

It still assumes the future resembles the input and ignores slippage, fees and news lockouts — a planning aid for sizing, not a promise of a payout. It is informational only; TradeTrove never places trades.

Want this run automatically on your actual logged trades, with live daily-loss tracking across a real challenge? Start a free 14-day trial — full journal, all 5 firms, Monte Carlo risk-of-ruin, AI weekly review.