Static vs trailing drawdown: the measured pass-rate gap across 8 prop firm rule sets
Free prop-firm calculators overwhelmingly simulate a static drawdown floor. Many of the most popular evaluations — Apex, Topstep, MyFundedFutures — don't use one. This study holds one realistic trader profile constant and simulates it against eight real rule sets, then re-simulates each firm with only the drawdown mechanism swapped to static. The difference between those two numbers is the price of the trailing rule itself — isolated from every other variable.
Key findings
Where trailing binds, it costs 14–16 percentage points of pass probability. The same trader passes Apex's rule set 75.4% of the time under its real intraday trailing floor — and 91.5% under a static floor with every other rule identical. The trailing mechanism alone costs 16.1 points. MyFundedFutures' end-of-day variant costs 14.1 points (81.3% → 67.2%).
Trailing is not always the binding rule. At Topstep the swap changed the result by 0.0 points — because the 2% daily loss limit and the 50% consistency requirement eliminate or block paths before the trailing floor ever matters at this profile. The drawdown label on the marketing page doesn't tell you which rule will actually end your evaluation.
The rule set changes your optimal risk size. Halving risk from 1.0% to 0.5% per trade lifts the Topstep pass rate from 24.9% to 69.6% (+44.7 points). The identical change at FTMO adds only 9.2 points (90.5% → 99.7%). Under tight daily and trailing rules, position size is the dominant lever — bigger than any strategy tweak.
Table 1 — Eight firms, one trader, drawdown mechanism isolated
Reference profile: 52% win rate · 1.6R avg win · 1R avg loss · 4 trades/day (Poisson) · 1.0% risk per trade · 0.05R cost. Each firm simulated under its verified 2026-07 rules (target, daily and total drawdown, min/max days, freeze, consistency), then under a static-floor counterfactual that changes only the drawdown mode. Two-step programs additionally compose funded probability as phase-1 × phase-2, a phase-2 failure meaning a full paid restart.
| Firm · program | Drawdown rule | Pass — actual | Pass — static CF | Trailing cost | Funded prob. |
|---|---|---|---|---|---|
| FTMO · 2-Step | static 10% | 90.5% | 90.5% | 0.0 (control) | 84.3% |
| FTMO Swing · 2-Step | static 10% | 90.5% | 90.5% | 0.0 (control) | 84.3% |
| FundedNext · Stellar 2-Step | static 10% | 91.4% | 91.4% | 0.0 (control) | 84.6% |
| Apex · Futures Eval | trail intraday 6% + freeze | 75.4% | 91.5% | −16.1 pts | 75.4% |
| Topstep · Combine | trail EOD 4% + freeze | 24.9% | 24.9% | 0.0 — daily 2% binds first | 24.9% |
| Funding Pips · 2-Step | static 10% | 91.9% | 91.9% | 0.0 (control) | 86.1% |
| The5ers · High Stakes | static 10% | 91.9% | 91.9% | 0.0 (control) | 86.1% |
| MyFundedFutures · Starter | trail EOD 4% + freeze | 67.2% | 81.3% | −14.1 pts | 67.2% |
Static-rule firms show a zero gap by construction — their real rule is the counterfactual; they serve as controls and as the baseline pass rates for this profile. Every firm name deep-links to the free engine with that rule set pre-loaded, so any cell can be reproduced against your own statistics in one click.
The Topstep zero is a finding, not a failure of the thesis. Its trailing floor is real — but at this profile the path dies (or the pass is blocked) at the 2% daily limit or the 50% consistency check before the floor is reached. Rules interact; the only honest way to know your binding constraint is to simulate the full rule set against your own numbers.
Table 2 — Same rules, different risk size: the interaction that matters most
Evaluation pass probability for three rule archetypes as risk per trade scales, all other stats held at the reference profile:
| Rule archetype | 0.5% risk | 1.0% risk | 1.5% risk | 2.0% risk |
|---|---|---|---|---|
| FTMO — static floor | 99.7% | 90.5% | 76.6% | 56.1% |
| Topstep — EOD trailing + 2% daily | 69.6% | 24.9% | 21.4% | 6.0% |
| Apex — intraday trailing | 95.4% | 75.4% | 59.6% | 49.0% |
Read the columns vertically: at 2% risk the same trader is a coin-flip at FTMO, a near-lock-out at Topstep, and a coin-flip-minus at Apex. Read the rows horizontally: the static account degrades gracefully as risk grows; the tight-rule accounts fall off a cliff. Risk size and rule set are not independent inputs — they are one joint decision.
Methodology — everything needed to reproduce this
- Engine: PropSurvival Quant Decision Engine v1.0 — the same
runPropAtRiskMonte Carlo that powers the free in-browser tool, executed unmodified. Per-path, trade-by-trade, day-by-day evaluation of daily loss, total drawdown (static / EOD-trailing / intraday-trailing, with freeze-at-initial), time windows, and consistency at pass. - Determinism: seeded PRNG (mulberry32, seed 12345), re-seeded identically before every cell so all regimes see the same random stream. Rerunning the study yields these exact numbers. 20,000 paths per cell; trade counts Poisson-distributed.
- Counterfactual definition: identical rule object with
ddMode → staticand freeze off; daily limit, consistency, targets and time windows unchanged. This is the same isolation the in-app Rule Impact analysis performs after each run. - Two-step composition: funded = P(phase 1) × P(phase 2), phase 2 simulated under its own target and window with the firm's drawdown rules — the conservative reading (a phase-2 failure restarts at a fresh fee).
- Rule sources: the 8 presets as verified 2026-07 and dated in the public verification log; modeling simplifications (e.g. Apex's 30% consistency applied at pass for conservatism, unlimited periods modeled as 60 days) are disclosed per-preset in the engine.
- Limitations: one profile cannot represent all traders — gaps grow with risk size and trade frequency and shrink toward zero for low-volatility styles. That is precisely why the engine is free: run your own statistics rather than trusting any fixed table, including this one.
Data license: CC BY 4.0 — reproduce the tables freely with attribution to PropSurvival and a link to this page.
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PropSurvival is independent analytical software and is not affiliated with, endorsed by, or sponsored by any firm named above. Rule descriptions reflect our verification dated above; firms change rules without notice — each firm's own documentation is always the final authority. Pass probabilities are model outputs for a stated profile, not predictions or guarantees. Nothing here is investment advice.