How to Pass the FTMO Challenge in 2026: Complete Strategy Guide

The FTMO Challenge has three key rules:

Daily Loss Limit (5%): On a $100K account, you cannot lose more than $5,000 in a single day. This includes unrealized losses. This is the #1 reason traders fail.

Max Drawdown (10%): Your account cannot drop more than $10,000 below your starting balance at any point. This is cumulative across the entire challenge.

Profit Target (10% Phase 1, 5% Phase 2): You need to profit $10,000 in Phase 1 and $5,000 in Phase 2. No time limit (since 2024).

If your profit target is $10,000 and max drawdown is $10,000, you have a 1:1 target-to-risk ratio at the account level. This means you need a strategy with positive expectancy and strict risk management.

Ideal approach: risk 0.5-1% per trade ($500-$1,000 on a $100K account). At 1% risk with a 2:1 reward ratio and 45% win rate, expectancy is $350/trade. You'd need ~29 trades to hit the target.

Worst approach: risk 3-5% per trade hoping to hit the target fast. One bad day and you've used up your entire daily loss limit.

The 5% daily loss limit is a hard stop. Here's how to manage it:

Rule of 3: Never risk more than 1.5% of your account on a single day. That gives you room for 3 losing trades before you're at 90% of your daily limit.

Stop trading at 3%. If you've lost 3% of your account value today, stop. You still have 2% buffer, but continuing to trade while frustrated will likely push you over.

Use PropJournal alerts. Set Telegram notifications at 70% ($3,500 loss) and 90% ($4,500 loss) of your daily limit.

Based on research across Reddit communities and prop trading forums, traders who pass consistently share these habits:

1. Trade journal — Every single trade is reviewed, not just losing ones 2. Real-time compliance tracking — Not spreadsheets updated after the fact 3. Session discipline — Trading only during specific sessions where their strategy works best 4. Position sizing calculator — Risk per trade is fixed at 0.5-1%, never adjusted emotionally 5. Post-trade AI analysis — Understanding WHY trades won or lost, not just logging the numbers