Custom AI Strategy for FTMO Traders

FTMO rejects roughly 90% of challenge attempts — not because traders lack edge, but because they lack a rules-aware execution framework. The difference between a funded account and a failed attempt is rarely skill; it is discipline architecture built around FTMO’s specific constraints.

The FTMO challenge enforces a 10% maximum loss limit, a 5% daily loss limit, and a 10% profit target within a fixed calendar window. Those three variables interact in ways that punish generic strategies. A system calibrated for a retail account will blow an FTMO evaluation in days — sometimes hours — if it ignores the daily drawdown ceiling.

This page shows you exactly how to use Assistly’s AI to build a custom strategy engineered for FTMO’s ruleset — position sizing, session filters, risk-per-trade logic, and psychological checkpoints — so every trade decision aligns with the goal of getting funded and staying funded.

Why Generic Strategies Fail FTMO Evaluations

Most retail strategies are optimized for returns, not for drawdown control within a hard ceiling. A strategy with a 15% max drawdown historically is immediately disqualified by FTMO’s 10% account loss rule — regardless of its win rate or expectancy. The ruleset is the constraint function, and your strategy must be built inside it, not retrofitted to it.

The daily 5% loss limit is where most FTMO attempts collapse. A trader running 1% risk per trade can breach the daily limit in five consecutive losses — a sequence that occurs routinely in mean-reverting markets during high-volatility sessions. Without a hard daily stop and session-aware position sizing, a single bad morning erases the entire evaluation window.

The solution is not to trade less. It is to build a strategy where the rules are embedded into the decision logic — not treated as external guardrails you check after the fact.

• 10% max account drawdown: every position must be sized against this absolute ceiling
• 5% daily loss limit: requires a hard daily stop-loss equivalent before session open
• 10% profit target in 30 days: demands consistent execution, not hero trades
• Minimum 10 trading days: eliminates overnight luck strategies; requires repeatable edge
• No weekend holding restrictions: must factor swap costs and gap risk into exit logic

Building Your Risk Architecture Inside FTMO Limits

The starting point for any FTMO-compliant strategy is reverse-engineering your risk-per-trade from the daily loss limit — not from gut feel. On a $100,000 FTMO account, the daily ceiling is $5,000. If you plan to take a maximum of four trades per session, your per-trade risk budget is $1,250 or 1.25% — and that assumes every trade hits its stop, which means your actual operational risk should be lower to preserve buffer.

Position sizing must account for instrument volatility, not just pip distance to stop. A 20-pip stop on GBPUSD in the London open carries a dramatically different dollar risk than the same stop during Tokyo hours. Volatility-adjusted sizing — using ATR multiples rather than fixed pip stops — keeps your dollar risk consistent regardless of session or market condition.

Layer a session filter on top: FTMO accounts perform best when traders are selective about session overlap. The London-New York overlap (13:00–17:00 UTC) consistently delivers the highest liquidity and tightest spreads on major pairs. Concentrating exposure in that window reduces slippage drag on your profit target math.

You are a professional prop firm trading coach. Build me a complete FTMO-compliant trading strategy for a $100,000 challenge account. Apply these hard constraints: 10% max account drawdown, 5% daily loss limit, 10% profit target in 30 trading days, minimum 10 trade days. I trade EUR/USD and GBP/USD during the London-New York overlap session. My preferred setup is [describe your setup — e.g., liquidity sweeps / order blocks / breakout retest]. Provide: (1) exact risk-per-trade formula, (2) daily stop-loss rule, (3) position sizing calculation using ATR, (4) session entry filter, (5) trade journaling checkpoints I should review each evening to stay on pace for the profit target.

Session and Instrument Selection for FTMO Profit Targets

Hitting a 10% profit target in 30 days requires roughly 0.33% net gain per day — a modest number that becomes achievable only with consistent execution across the right instruments. FTMO’s most successful funded traders concentrate on two to three instruments with high daily range and tight spreads: EURUSD, GBPUSD, and XAUUSD account for a disproportionate share of funded account payouts.

Gold (XAUUSD) deserves specific attention for FTMO traders. Its average daily range of 150–200 pips creates large profit potential per trade, but its volatility also means stop placement must be wider — typically 20–40 pips minimum — to avoid noise-driven exits. FTMO’s spread costs on XAUUSD are higher than major FX pairs, so factor that explicitly into your expectancy calculation.

Avoid diversifying across six or seven instruments during the challenge phase. Each additional instrument requires monitoring, increases cognitive load, and introduces uncorrelated drawdown events that can stack against your daily limit simultaneously. Depth in two instruments beats width across eight.

• EURUSD: tightest spreads, highest liquidity, best for technical precision strategies
• GBPUSD: wider daily range, suits momentum and breakout setups
• XAUUSD: highest per-trade profit potential, requires wider stops and explicit spread accounting
• Avoid exotic pairs during challenge phase — spread costs erode tight profit margins
• Limit active instruments to two during evaluation; expand post-funding

Managing the Psychological Pressure of the FTMO Clock

The 30-day evaluation window creates a time pressure that distorts decision-making in predictable ways. Traders who are behind pace on day 20 begin overtrading and widening risk — the exact behavior that triggers the daily loss limit and ends the evaluation. The pressure response is not a character flaw; it is a structural feature of time-constrained targets. The fix is a pacing dashboard built into your daily routine.

Track your current account balance, daily P&L, and days remaining every morning before you open a chart. If you are 6% toward your target with 15 days left, your required daily pace is 0.27% — well within reach with a single quality trade. That framing eliminates urgency bias. If you are 2% toward your target with 5 days left, the honest answer is to stop trading, protect your account, and restart — not to gamble for a comeback.

Treat each evaluation day as an independent unit. A loss day is not a deficit to recover; it is a closed event. The only question is whether you are within daily and total limits heading into the next session.

Scaling to a Funded Account: What Changes Post-Challenge

Passing the FTMO challenge is the entry point, not the destination. The funded account operates under the same drawdown rules but adds a profit-split dynamic — FTMO pays out 80% of profits, scaling to 90% under their scaling plan. The scaling plan requires hitting 10% profit in four consecutive months without breaching drawdown limits, which means the strategy that passed the challenge must also be sustainable over a four-month horizon.

Post-funding, the primary adjustment is reducing risk-per-trade slightly to protect your funded status. Many traders who pass at 1.5% risk-per-trade scale back to 0.8–1.0% on the funded account. The math still delivers strong returns — 0.8% per trade at a 55% win rate and 1.5R average winner produces approximately 6–8% monthly expectancy — while dramatically reducing the probability of a catastrophic drawdown event.

Use the funded phase to build a verifiable track record. FTMO’s scaling plan and the broader prop firm ecosystem reward documented consistency. Every funded month is auditable proof of edge that can be used to access larger capital allocations across multiple prop firms simultaneously.

I have passed the FTMO challenge and now hold a $100,000 funded account. Help me adapt my challenge strategy for long-term funded account sustainability. My challenge strategy used 1.5% risk per trade on EURUSD and GBPUSD during the London-New York overlap. I want to: (1) reduce risk to protect funded status while maintaining 6–8% monthly expectancy, (2) build a pacing system to qualify for FTMO's scaling plan in four consecutive months, (3) create a monthly review checklist that flags strategy drift early. Provide specific numbers, not general advice.

Using Assistly to Build Your Complete FTMO Strategy

Assistly’s AI strategy builder is pre-configured to handle constraint-based trading frameworks — exactly the structure FTMO evaluations require. Instead of starting from a blank prompt, you input your account size, target profit, evaluation window, and preferred instruments, and the AI generates a rules-complete strategy document covering position sizing, session filters, daily stop protocols, and trade review checkpoints.

The output is not a generic trading plan. It is a parameterized system where every rule traces back to a specific FTMO constraint. Change the account size from $25,000 to $200,000 and the position sizing logic updates automatically. Swap EURUSD for XAUUSD and the ATR-based stop calculations adjust for that instrument’s volatility profile.

Traders who document their strategy before the evaluation outperform those who improvise. The documentation forces clarity — you cannot write down a vague rule and execute it consistently. Assistly turns the strategy-building process into a structured output you can follow, review, and refine after each trading day.