Algo trading in funded accounts

1. yeah it works fine, the account blowing comes from your strategy's drawdown not from the algo itself. you need to design the bot around the prop firm's max daily loss and max overall drawdown rules, not the other way round. 2. ran bots on a couple of prop accounts. results were mixed, one passed and one got chopped up by a ranging market for three weeks until it hit the daily limit. automation doesn't fix a bad edge, just executes it faster. 3. if you already know python, skip c++ and just learn mql5 directly. the syntax is close enough that you'll pick it up in a few weeks. the hard part isn't the language, it's the metaeditor environment and broker-specific quirks. 4. plenty of people do it, but most keep quiet about it because prop firms don't love bots hammering their servers. read the terms carefully, some have rules about latency or tick frequency. 5. manual passing is mostly risk management. cut your size way down, aim for 0.5% risk per trade, and don't touch the account on days you're down more than 1%. passing is boring, you're not trying to make money, you're trying to not lose it.

The algo part is the easy half — the hard half is that a funded account is a constraint-satisfaction problem, not a profit-maximization one. Your strategy doesn't need a great Sharpe, it needs a drawdown profile that fits inside the firm's max daily loss and max overall drawdown with margin to spare. Two things people underestimate: (1) backtest max drawdown is one path, not a distribution — run the same strategy across shuffled/alternative orderings and size off the worst realistic streak of consecutive losses, not the single backtest number; (2) daily-loss rules are hit by floating drawdown too, so a position sized for 'I'll cut at -1%' can still breach the daily cap on a gap or a fast move before your stop logic runs. Size so that even an instant gap against you stays inside the cap. Also check the firm's rules on news trading, holding over weekends, and consistency requirements (some penalize one day carrying most of the profit) — those kill more algo passes than the strategy itself does. On MQL5 vs Python: coming from Python, MQL5 syntax will feel awkward for about a week and then it's fine — it's worth learning if you want to run bots natively in MT5 on a cheap VPS. The alternative is running the logic in Python and bridging to MT5, but that adds a moving part that can fail silently mid-session, which is exactly what you don't want on an account with hard loss limits. For prop-firm work I'd keep the whole loop inside one process.

oprietary firm algorithms are specifically designed to filter out erratic manual execution and emotional drawdown. Since you mentioned you currently struggle with breaking even and blowing accounts, your primary bottleneck isn't the code or the platform—it's risk management. Regarding your tech stack, if you already know Python, you don't need to learn full C++ just to pick up MQL5; focus directly on MQL5's built-in functions since its syntax is procedural and object-oriented enough to bridge easily. To pass a funded account evaluation manually or automatically, you must implement a strict mathematical risk framework—such as sizing positions using Average True Range (ATR) and capping every single trade's risk at 1% of total capital. Shift your focus away from chasing high-volatility breakouts and toward strict drawdown limits, and your consistency will follow. 📊📈🛡️