What is PropFate?
PropFate is a prop firm survival simulator. You upload historical trades, enter account rules, and run Monte Carlo simulations to estimate challenge pass, failure, and first payout paths.
It does not tell you what to trade. It shows how your existing trade distribution behaves under specific rule constraints.
Why PropFate exists
Many traders judge a challenge by account size, profit target, and fee. Those are not enough. Daily loss, max loss, trailing drawdown, minimum days, consistency rules, and first payout rules can change the real survival profile.
PropFate exists to turn a trade sample into a rule-aware risk estimate before another challenge fee is paid.
Is a 100k prop account really 100k?
No. The headline balance is not the amount you can lose. A 100k account with a 3k max loss gives you about 3k of practical risk room, before any trailing or daily rules are considered.
The useful question is not account size. It is how much adverse path your strategy can absorb before the rules fail the account.
Why first payout matters more than high returns
High returns in a backtest can hide the cost of retries, time, and failed funded paths. First payout is a stricter milestone because the account must pass rules, survive funded trading, and reach a withdrawable state.
A setup with lower theoretical return but better first payout probability may be a better fit for prop firm rules.
Why profitable backtests can fail prop firm rules
Backtests often focus on final profit. Prop firm accounts care about the path. One large loss day, a trailing drawdown touch, or a slow path to target can fail an otherwise profitable strategy.
PropFate checks the path against rule limits, not only whether the historical sample was profitable.
Disclaimer
PropFate is for educational, research, and simulation purposes only. It is not financial advice, trading advice, investment advice, or a guarantee of future results.
Prop firm rules may change. Always verify the rules directly with the firm before buying a challenge or making risk decisions.