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Building a trading bot with ChatGPT (for a prop firm)
You can build a working futures trading bot with ChatGPT, and plenty of people are. What ChatGPT is genuinely good at is turning a plain-English strategy into Python, wiring up a broker API, and writing the backtest harness. What it cannot do is invent an edge or respect a prop firm rulebook it has never read. This is the overview: what the model does for you, where it falls down, and the rules your bot has to obey to survive a funded account.
I run an automated futures bot myself, built and backtested with AI and streamed live, so this is the version that accounts for the part most tutorials skip: the firm.
What ChatGPT actually builds well
Give it a clear strategy and ChatGPT will write the order logic, connect to a futures API like Tradovate or Rithmic or a bridge, structure the data feed, and scaffold a backtest. It is fast at the plumbing. Treat it as an engineer who codes exactly what you specify, including your mistakes, not as a strategist who decides what to trade.
The workflow that works: describe the strategy in precise rules, have it generate the code in small pieces you can read, and test each piece. Vague prompts get vague bots.
Where it falls down
It will confidently write a backtest with lookahead bias, no slippage model, and position sizing that ignores the drawdown. It does not know your prop firm's rules unless you tell it, and it will happily build a strategy that violates the trailing drawdown or the consistency rule. The edge is yours to bring. The model only implements it, and it implements bugs just as fast as features.
Assume every number it gives you is optimistic until you have checked the backtest by hand for the usual traps.
The part the tutorials skip: the firm rules
A bot that passes a backtest still has to pass a funded account, and that is a different test. Your bot has to respect the firm's drawdown type, end-of-day or intraday, the consistency rule on payout, the flat-by time, and whether the firm even allows bots at all. Most futures firms ban or restrict fully automated trading on the funded account.
Encode the firm's rules as hard constraints before you go live, or the firm's risk engine will encode them for you by closing the account. Our automation rules page lists which firms allow bots, which only allow it on the eval, and which ban it outright.
Backtest the way the firm scores you
Backtest against the firm's actual constraints, not just profit. Cap the equity curve at the firm's drawdown number, model the payout gates and the flat-by time, and count the resets you would have bought. A strategy that is net profitable but breaches the drawdown once a month fails a prop account even though the backtest looks green.
That is the difference between a bot that backtests well and a bot that survives a funded account. Claude is also strong for this kind of build, so use whichever model you have access to. The prop-firm constraints you encode matter more than the model you pick.
FAQ
Can ChatGPT build a profitable trading bot?
ChatGPT can build the bot, but not the edge. It is good at turning a defined strategy into working code, the API wiring, and the backtest. It cannot invent a profitable strategy or guarantee one works live, and it does not know your prop firm's rules unless you encode them.
Can you run a ChatGPT-built bot on a prop firm?
Only where the firm allows automation, and only if the bot respects the firm's rules. Many futures firms ban fully automated trading on the funded account, so check the automation rules per firm before you build.
Is ChatGPT or Claude better for building a trading bot?
Both work. ChatGPT is the more common starting point; Claude tends to handle long, multi-file codebases and refactors well. The build process, and the prop-firm rules your bot must respect, are the same either way.