The Prop Firm Landscape
Prop firms (proprietary trading firms) offer funded accounts to traders who pass their evaluation challenges. The model: you prove you can trade profitably within specific risk parameters, and they give you capital. You keep 80-90% of the profits.
For algo traders, this is an attractive proposition. Algorithms are consistent, rule-following, and emotionless — exactly what prop firm evaluations reward.
But not all algorithms work for prop firms. And not all prop firms work for algorithms.
Understanding Prop Firm Rules
Most prop firm evaluations share common rules:
- Profit target: Usually 8-10% of account size
- Max daily drawdown: Typically 4-5% of starting balance
- Max total drawdown: Usually 10-12% of starting balance
- Minimum trading days: 5-10 days minimum
- No overnight holds: Some firms restrict holding positions through market close
These rules fundamentally change which strategies are viable. A strategy that is profitable on a personal account might fail every prop firm evaluation if it violates drawdown limits.
Strategies That Pass Evaluations
Conservative Scalping (High Win Rate)
Profile: 70%+ win rate, small average winners, tight stops.
This is the most common algo approach for prop firms. The high win rate means consistent daily profits, which matters when you need to hit a profit target within a timeframe.
Key parameters:
- Average winner: 4-8 ticks on ES
- Average loser: 6-10 ticks on ES
- Risk per trade: 0.5-1% of account
- Trades per day: 3-8
Why it works for props: Consistent daily profits, low max drawdown, predictable equity curve.
Momentum Breakout (Lower Win Rate, Higher R:R)
Profile: 40-50% win rate, large average winners, moderate stops.
This approach takes fewer but larger trades. It is harder to pass evaluations quickly, but the funded account performance tends to be more sustainable long-term.
Key parameters:
- Average winner: 15-30 ticks on ES
- Average loser: 8-12 ticks on ES
- Risk per trade: 1-1.5% of account
- Trades per day: 1-3
Why it works for props: When it wins, it moves the equity curve significantly. Drawdowns are controlled by strict stops.
Strategies That Fail Evaluations
Grid/Martingale Systems
These double down on losing positions. They can show impressive win rates in backtesting, but a single adverse move can blow through daily drawdown limits instantly.
Do not use these for prop firm evaluations. The math eventually catches up.
High-Frequency Strategies
While HFT can be profitable, most prop firms have minimum holding time requirements or commissions structures that make high-frequency approaches unprofitable after costs.
Overnight Gap Strategies
Many prop firms prohibit holding positions through market close. Even firms that allow it often have tighter risk limits for overnight positions.
Compatible Prop Firms for Algo Trading
Not all prop firms support automated trading. Here is what to look for:
Must-haves:
- Explicit permission for automated/algorithmic trading in their rules
- NinjaTrader support (since that is our execution platform)
- API access or webhook support for order routing
- No restrictions on trade frequency (within reason)
Nice-to-haves:
- Trailing drawdown (instead of fixed from peak equity)
- Scaling programs that increase account size based on performance
- Reasonable reset fees if you fail an evaluation
Realistic Expectations
Here is what we see from GFREQ subscribers using our algorithms for prop firm evaluations:
- Pass rate: Roughly 40-60% of evaluation attempts pass on the first try
- Average time to pass: 15-25 trading days for a 30-day evaluation
- Most common failure reason: Daily drawdown limit hit during a volatile session
- Funded account retention: About 50% of traders who pass maintain their funded account for 3+ months
These numbers are honest. Anyone claiming 90%+ pass rates with algorithms is either cherry-picking data or overfitting to evaluation conditions.
The GFREQ Approach
Our algorithms are designed with prop firm rules as a constraint, not an afterthought:
- Daily max loss hard-coded: Algorithms shut down for the day if daily P&L hits -3% (below most firms' -4% to -5% limit)
- Position size adjusted: Automatically calculated based on account size and maximum risk per trade
- No overnight holds by default: All positions flatten before market close
- Minimum trade spacing: Prevents rapid-fire entries that could stack losses
Getting Started
- Choose a prop firm that explicitly allows algorithmic trading
- Start with their smallest account size evaluation
- Run the algorithm on a paper account with identical rules for at least 2 weeks first
- If paper results are within your risk tolerance, run the evaluation
- Expect to fail at least once. Budget for 2-3 evaluation attempts.
The math works in your favor long-term: if evaluations cost $200 each and funded accounts generate $2,000-5,000/month in your share of profits, one successful funded account pays for many failed evaluations.
Trading involves risk. Past performance does not guarantee future results. Only trade with capital you can afford to lose.