FundedNext Calculator

FundedNext Pass Rate Calculator with 95% confidence intervals

Upload your EA backtests. Pass Lab simulates your trades against FundedNext's Stellar 2-step Phase 1 rules — including the 2026 XAUUSD leverage cut — using walk-forward Monte Carlo and bootstrap CIs. Audit-grade [low, high] range, not a marketing-grade point estimate.

Not affiliated with FundedNext. FXOptimize is an independent research and analytics tool. We use FundedNext's publicly documented rule structure to estimate historical pass rates from your backtest data. We are not endorsed by, partnered with, or otherwise affiliated with FundedNext.
Open Pass Lab →How it works
✓ Trade data never leaves your device✓ 2026 rules verified✓ Open methodology
Estimate your pass probability

Lower bound, not best case.

95% CI from 1,000 Monte Carlo simulations on the inputs below. Upload your real backtests for audit-grade precision →

Primary match · 95% CI lower bound
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Best case · 95% CI upper bound
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Lite estimate. Upload your MT4/MT5 backtest for audit-grade precision (walk-forward × Monte Carlo × bootstrap on real trade data).
FundedNext Stellar 2-Step Phase 1 rules baked in:Target +8%Max DD 10%Daily DD 5%5+ days · unlimited time

Lite estimate based on simplified inputs. Real-world pass rates depend on your actual trade distribution, news-trading rules, weekend holding, and per-firm consistency rules — all of which our audit-grade Pass Lab tool accounts for via real backtest data. CFTC Rule 4.41 hypothetical performance disclaimer applies.

Methodology

Why FundedNext needs a real pass-rate calculator

FundedNext's Stellar 2-step is structurally easier than FTMO 2-step on two dimensions: lower profit target (8% vs 10%) and weekend holding allowed. The 5% daily DD is the same, both are now unlimited time (FTMO removed its 30-day cap in 2026), and the 2026 leverage changes hit gold-heavy strategies hard.

"Easier on paper" doesn't tell you whether your specific portfolio passes. Your backtest's max-DD is post-hoc on the trade order that happened. FundedNext's daily-DD rule fires on whatever order trades land in real time. Path-dependence is what determines pass probability — not your headline backtest numbers.

Pass Lab fixes this with walk-forward windows × Monte Carlo trade-shuffling × bootstrap confidence intervals. You upload your actual MT4/MT5 backtests; the engine returns a 95% CI [low, high] for FundedNext alongside 7 other firms.

Rules

FundedNext Stellar 2-Step Phase 1 rules (verified May 2026)

RuleStellar 2-step Phase 1 ($100k account)
Profit Target8% of starting balance
Max Daily Loss5% of starting balance (static)
Max Total Loss10% of starting balance (static line, not trailing)
Min Trading Days5 days with at least one closed trade
Time LimitUnlimited
Weekend HoldingAllowed (challenge phase)
Forex Leverage1:100
Metals (XAUUSD) Leverage1:10 (cut from 1:50 in January 2026)
Indices Leverage1:30 (relaxed from 1:20 in 2026)

Source: FundedNext Help — Stellar 2-Step Rules (verified 2026-05-01).

Pay attention to the XAUUSD leverage cut. If your EA portfolio is gold-heavy, the 5x reduction in metals leverage materially affects how aggressively you can size positions. Pass Lab models the cut directly — your XAUUSD positions are constrained to the 1:10 leverage cap during simulation, which can push portfolios that previously fit FundedNext over to firms with more permissive metals leverage (FTMO 1:30, FundingPips 1:30, Goat 1:20).

Comparison

FundedNext vs FTMO — when does which win?

Three patterns dominate the cross-firm comparison:

Slow-burn portfolios with steady equity growth

Trend-followers and steady-winner portfolios that take 60+ days to compound 8% can pass either firm — both removed their time caps. FundedNext's lower 8% target (vs FTMO's 10%) is the meaningful structural edge here. Pass Lab typically surfaces FundedNext over FTMO for slow-burn portfolios on the target gap, not the time gap.

Aggressive portfolios that hit target fast

Portfolios that compound 10%+ in 2 weeks pass FTMO Phase 1 quickly, and the 2-step structure protects you in Phase 2 (5% target). FundedNext's 8% target is also fast, but you still need 5 trading days minimum and time isn't a constraint either way. Pass Lab usually returns near-tied CIs for fast-compounding portfolios — pick whichever has the better profit split for the funded stage.

Gold-heavy strategies post-2026 leverage cut

Mean-reversion XAUUSD EAs that depend on 1:50 leverage to size positions are now seeing materially reduced position sizes on FundedNext. FTMO's 1:30 metals leverage and FundingPips' 1:30 are now MORE permissive than FundedNext for gold. Pass Lab will rank FTMO/FundingPips above FundedNext for gold-heavy portfolios when the leverage difference matters.

FAQ

Frequently asked questions

What's my actual pass probability for FundedNext Stellar 2-step?

Pass Lab gives you a 95% confidence interval based on walk-forward Monte Carlo simulation against FundedNext's exact Stellar 2-step Phase 1 rules. Upload your MT4/MT5 backtests at fxoptimize.com/pass-lab/ and get an audit-grade [low, high] range. The primary match is selected on the lower bound, not the point estimate.

Did FundedNext change their leverage in 2026?

Yes. In January 2026 FundedNext cut XAUUSD (gold) leverage from 1:50 to 1:10 — a 5x reduction in margin efficiency. Indices leverage was relaxed from 1:20 to 1:30. Forex remains 1:100. Pass Lab's FundedNext Stellar profile reflects current 2026 caps.

How does FundedNext Stellar compare to FTMO?

Stellar 2-step has an 8% target (vs FTMO's 10%), 5 min trading days (vs FTMO's 4), both unlimited time (FTMO removed its 30-day cap in 2026), same 5% daily DD, same 10% static total DD. The lower target makes FundedNext typically easier than FTMO 2-step for slow-burn portfolios. Pass Lab compares both side-by-side and surfaces whichever has the higher CI lower bound for your specific portfolio.

Does FundedNext Stellar use trailing or static drawdown?

Static drawdown — the 10% total loss line is fixed at starting balance regardless of equity peaks. More permissive than trailing-EoD (FTMO 1-step) and significantly more permissive than trailing-intraday (the strictest variant). Mean-reversion and grid EAs that recover from large drawdowns survive static rules.

How does Pass Lab calculate the FundedNext confidence interval?

Walk-forward windows of 60 days (FundedNext has unlimited time so we cap at 60 days) slid across your backtest with 30-day stride. Per-window Monte Carlo: 1,000 iterations with within-day shuffled trade order. Bootstrap 5,000 resamples to compute 95% CI. Sample-size guard requires ≥12 windows. Full methodology here.

What typically causes FundedNext challenge failures?

In backtest simulation, FundedNext Stellar 2-Step Phase 1 fails cluster into two modes. First, the 5% daily DD on the EoD-anchored floor catches portfolios that combine a 2-3% intraday excursion with overnight gap risk — particularly XAUUSD strategies after FundedNext's 2026 metals leverage cut from 1:200 to 1:20. Second, the 10% trailing-end-of-day total DD will fire on recovery legs for grid or mean-reversion EAs: even though the floor only advances at EoD (not intraday), once it's set high enough, a drawdown trough below the trail breaches it. Portfolios with concentrated XAUUSD exposure should pay particular attention to the new leverage ceiling — Pass Lab models the 1:20 cap and will flag leverage-limit breaches that would have passed under the pre-2026 catalog.

Is this tool affiliated with FundedNext?

No. FXOptimize and Pass Lab are independent. We have no affiliate relationship with FundedNext or any other propfirm. Pass Lab models FundedNext's published rules accurately because the brand requires audit-grade fidelity. The cross-firm comparison is symmetric — Pass Lab surfaces FundedNext when your portfolio fits FundedNext best, and other firms when those fit better.

Calculate your FundedNext pass probability now

Upload your MT4/MT5 backtests. Pass Lab simulates against FundedNext Stellar 2-step plus 7 other propfirms simultaneously. Get a 95% CI per firm and an audit-grade backtest match.

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