
Every step of cracking a prop firm challenge, on one page. From choosing a firm โ understanding the rules โ passing the challenge โ protecting your funded account โ maximizing payouts โ scaling to multiple accounts โ a hub linking the key points of each step to 44 detailed articles. A realistic roadmap grounded in real EA backtests and primary overseas data (5-14% pass rates, ~7% reach payout).

Passing isn't the finish line in prop trading โ only about 7% of traders who reach Funded actually get paid (FPFX, 300,000 accounts). Explained with overseas data: the trailing-DD trap, the flow of your first payout, how consistency rules hold payouts hostage, scaling conditions, and how to maximize payouts.
![High-variance strategies are the ones suited to prop firms | Why you should deliberately NOT bring a low-variance edge like goto-bi trading [Opinion]](/og/en/prop-firm-high-variance-strategy-fit.png)
A prop firm's payoff is like a call option: losses are capped at the challenge fee, while the upside is large once funded. That's why a strategy's variance (volatility) becomes an asset. Meanwhile, a low-variance, high-win-rate edge like goto-bi trading doesn't need insurance โ you're better off running it with your own capital. This piece works through that structure.

A formula-based breakdown of lot calculation for prop firm accounts. Covers how to set your risk % (around 0.5% during evaluation), working backward from your stop-loss distance, why leverage isn't the same thing as risk, sizing by working backward from daily DD, calculating your tolerance for a losing streak, and the effective risk of correlated positions. Includes worked examples for $50K and $100K accounts.

Compares scaling plans that grow a funded account across the major firms: FTMO (4 months, +10% โ +25%, up to $2M), FundedNext (+40%, up to $4M), and the doubling model at The5ers Hyper Growth / Funded Trading Plus. Explains the mechanism where payout history counts as a requirement, and how to play it to maximize scaling.

A science-based look at prop trading psychology: the brain mechanism that makes you take on too much risk after a loss (cortisol +70%), peer-reviewed data showing that traders who trade more lose more, "if-then rules" that beat willpower, and how to avoid outcome bias by judging yourself on process. Reproducible fixes, not motivational talk.

An analysis of why traders fail prop challenges, based on primary overseas data and peer-reviewed research. Failure is 90% risk discipline and psychology, not strategy quality. Covers 15 common mistakes -- daily DD violations, revenge trading, misunderstanding trailing DD, and more -- plus how to raise your odds of survival. Also fact-checks the '94% fail' myth.

An analysis, using overseas data, of which trading styles pass prop evaluations more easily. Covers the strengths and weaknesses of trend-following, breakout, range, and mean-reversion strategies, cautions for scalping/swing trading, how to think about win rate ร RR, and prohibited strategies. Explains why disciplined, consistent execution of a validated edge matters more than which strategy you pick.

DarwinexZero (DXZ) runs on a completely different philosophy from a normal prop firm. We compare its DARWIN investor-funding model โ up to โฌ3M in capital for โฌ38/month โ against Fintokei for Japanese readers: the truth about the 15% split, and why it suits long-term career-focused traders.

Comparing Fintokei and FTMO across 7 axes: price, drawdown, profit split, Japanese-language support, news trading, weekends, and EA use. Whether you're chasing profit or peace of mind, this settles which one to pick using actual numbers.

A 20-point comparison of Japan-based Fundora and Japanese-trader-focused Fintokei. Covers practical differences like domestic Japanese bank withdrawals, cTrader-only trading, and LINE support, plus recommendations by use case.

A breakdown of prop firm DD rules by formula. Explains the differences between static, trailing, EOD, and daily (Balance/Equity-based) drawdown, with a table showing which of 18 firms use which type.