Would You Pass FTMO? Simulate Before You Pay (2026)

This guide covers FTMO’s CFD evaluation routes. FTMO has announced futures trading (currently in beta); details are being finalized — see our upcoming coverage.

The server-rendered comparison below holds region, simulated account size, and first evaluation stage constant. It owns current price and rule facts; the article owns the replay method and verdict. Start with the exact program rather than a firm-wide average, because 1-Step and 2-Step use materially different loss-floor and completion mechanics.

What the Pre-Purchase Test Can—and Cannot—Prove

A useful simulation is a counterfactual audit. It takes trades you actually placed and asks what the selected rule engine would have done at each timestamp. It can reveal a daily equity breach, a static or trailing loss-floor breach, an incomplete objective, a concentration condition, or insufficient evidence. The result belongs to that program version, account scope, strategy version, and historical window.

For a compact view of exact provider terminology before you configure the test, use the prop-firm rules reference. Treat the current FTMO dashboard and agreement as controlling at purchase and phase transition.

Step 1: Choose the Exact FTMO Contract

“FTMO rules” is not a single configuration. Record the program ID, phase, region, simulated account size, platform/account type, and catalog verified date. For September 2026, FTMO’s public CFD objectives distinguish these first-stage mechanics:

• 1-Step: one evaluation phase, a daily-equity rule, an end-of-day trailing maximum-loss floor, and a Best Day completion condition.
• 2-Step: a Challenge followed by Verification, a daily-equity rule, a static maximum-loss floor, and minimum trading days in each evaluation phase.
• Both: no maximum evaluation time in the current public CFD rules. The old 30-day and 60-day countdowns are obsolete.

The exact percentages, current fee, supported platforms, payout timing, and verified date belong to the canonical component above. If a value shows Not verified, stop and check the official contract; do not fill the gap from memory.

Step 2: Build Replay-Grade Evidence

Closed-trade P&L alone may be insufficient. FTMO’s Maximum Daily Loss uses equity, including open positions, swaps, and commissions, across a CE(S)T daily boundary. A spreadsheet that only sums end-of-day closed trades can miss an intraday violation and return a false pass.

Freeze one strategy version and collect:

• Account and source identity, with no mixed accounts or reset periods.
• Entry and exit timestamps, direction, quantity, instrument, and execution IDs.
• Realized P&L, commissions, swaps, and funding where relevant.
• Intraday equity observations or enough execution detail to reconstruct open P&L at each rule check.
• Trading-day boundaries in the program’s required timezone.
• The exact setup/risk version that was active for every included trade.

Reconcile the source before scaling anything. Missing fees, duplicated partial closes, mixed currencies, or timezone drift can move the first breach. If you need to cap risk before a new replay, the risk-per-trade framework shows how to define a testable policy without pretending one percentage fits every strategy.

Step 3: Replay the Event Order, Not Just Daily Totals

1. Initialize the exact phase. Do not carry balance, days, or loss-floor state from Challenge into Verification or from an evaluation into the later account.
2. Sort every relevant event. Entries, exits, partials, commissions, swaps, and equity marks must use one normalized timeline.
3. Apply the daily boundary. Calculate the active daily-loss limit from the program definition and the correct CE(S)T reset state.
4. Update equity after each event. Test the daily limit and the correct static or end-of-day trailing maximum-loss floor.
5. Model completion conditions. Profit objective, minimum trading days, Best Day, and closed-position requirements are separate from terminal breaches.
6. Stop impossible branches. Once the path violates a terminal rule, later historical trades no longer belong to that counterfactual account state.

Order matters. A profitable close later in the day cannot erase an earlier equity breach. Reaching a profit target does not automatically complete a phase if another objective remains unsatisfied or positions are still open. The simulation must use the provider’s consequence, not a convenient pass/fail shortcut.

Step 4: Read the Result as a State, Not a Prediction

The most useful outputs are the first binding constraint and the minimum buffer—not a made-up pass probability. A path that clears a floor by a tiny amount is operationally different from one with meaningful room, even if both receive the same historical completion label.

Step 5: Repeat Without Cherry-Picking

One good month is not a probability model. Select several non-overlapping periods before looking at their outcomes, keep the strategy and rule snapshot fixed, and report every result. Include different observed volatility and trading-frequency conditions if the same strategy version was actually active.

There is no universal minimum of 30, 60, or 90 days and no defensible conversion from “three passing windows” to a future pass rate. More evidence helps only when it is comparable. If the strategy changed, start a new version; if a period lacks required intraday data, mark that test incomplete rather than borrowing confidence from another period.

Where Even a Correct Replay Stops

A deterministic rule replay is strongest at contract compatibility and weakest at unobserved future behavior. It does not know how you will react to purchase pressure, whether spreads and slippage will match the historical venue, whether the live regime will resemble the sample, or whether the provider will change rules before purchase.

• Execution gap: compare the evaluation platform’s current costs and execution conditions with the historical source.
• Behavior gap: define pre-trade risk, daily stop, and allowed setups before purchase; do not optimize them after seeing each failed window.
• Contract gap: snapshot the current program at purchase and repeat the rule validation at every phase change.
• Evidence gap: a replay without open-equity information cannot certify an equity-based daily rule.

Fix the First Binding Rule—Then Retest

Do not respond to a breach by shrinking every trade until the old period passes. That is in-sample optimization. Diagnose the event and decide whether the proposed control belongs to the strategy:

• If exposure clusters across correlated instruments, test an account-level open-risk cap.
• If a single session produces the daily breach, test a session stop or setup gate.
• If the maximum-loss floor binds across ordinary variance, the contract may be a poor fit for this strategy.
• If the objective remains incomplete without a breach, do not manufacture urgency; current CFD evaluations have no maximum completion time.
• If the result depends on one outlier day, review concentration and the exact program’s completion conditions.

Version the change, practice it prospectively, and test it on evidence not used to design the fix. The post-failure diagnosis guide uses the same first-binding-rule discipline after a real attempt.

Run the Full FTMO Evidence Cycle in TSB

TSB’s advantage is not a decorative pass/fail badge. The Prop Firm Challenge Tracker owns the exact account, program, phase, start balance, live objectives, and remaining buffers. The Retrospective Backtester replays a frozen setup version against owned-account evidence. AI Coach then routes the result through data quality, plan compliance, setup risk, market regime, rule testing, and setup decay, linking supported findings back to the underlying trades.

TSB has processed 600K+ imported trades across its import history, and the source registry recognizes 328 exact broker, exchange, platform, and prop-export profiles. Those figures mean imported trades and recognized routes—not users, universal compatibility, or trades analyzed by Coach. Verify your exact route and reconcile a sample before asking personalized questions.

Track the exact FTMO phase Replay a frozen strategy version Turn the result into Current Focus

Bottom Line

A good FTMO simulation does not say you are destined to pass. It tells you whether one exact, fully evidenced historical path would have completed one exact program version; where it first failed; and how much recorded room remained. That is enough to prevent a blind purchase and focus practice on the real constraint.

Choose the program, freeze the evidence, replay every rule in order, repeat on untouched periods, and preserve unknowns. If you proceed, use the rules-first FTMO execution plan without changing the parameters that earned the replay result.

Disclosure: Trader’s Second Brain is our product. The FTMO cards render server-side from the canonical program catalog; current values may refresh, missing values show Not verified, and a catalog conflict triggers editorial review. The headline, replay method, and verdict do not update automatically. FTMO sources and local product contracts were checked on September 10, 2026. See our editorial methodology.