Introduction

Artificial intelligence has made big strides in generating code — but can it build a fully functional, professional trading strategy? We put ChatGPT to the test by asking it to create a complex NinjaTrader 8 strategy with real-world features: moving average crossovers, limit entries, multiple profit targets, a trailing stop, and strict trading rules.

What the AI Delivered

ChatGPT generated a complete strategy class with clearly organized code, user-adjustable parameters, and in-code comments explaining each block. It implemented:

• Properly structured crossover logic with entry filtering.
• Limit order entries based on the bar’s close.
• Multi-target exits with scaling logic.
• A dynamic trailing stop activating after the first profit target.
• Output logging for fill status and trade tracking.

It even showed awareness of NinjaTrader features like OCO groups and partial exits.

Where It Fell Short

Despite impressive effort, several issues emerged:

• Partial fill handling was weak. The AI assumed full fills and didn’t adjust targets when entry size was reduced.
• Multi-target logic was fragile. Orders weren’t always coordinated properly, risking mismatches or oversizing.
• Trailing stops were imprecise, sometimes updating unnecessarily or misapplying logic to short trades.
• Platform quirks were overlooked, like entry order expiry and OCO ID requirements.
• No post-trade resets, meaning leftover flags could cause faulty behavior on the next trade.

While the strategy compiled and ran, it wasn’t robust enough for live trading without significant debugging.

Why It Struggled

The main reasons? The complexity of real trading logic, lack of execution feedback during code generation, and the nuance required by NinjaTrader’s API — especially around order handling and execution flow.

Final Takeaways

AI can absolutely accelerate strategy development, especially for drafting logic and boilerplate. But it’s not yet ready for hands-off deployment. If you’re a trader or developer:

• Use ChatGPT as a jump-start, not a final solution.
• Always backtest thoroughly and review the logic line by line.
• Break complex strategies into steps when prompting AI.

This test highlights how far AI has come — and where it still needs human collaboration. With expert oversight, tools like ChatGPT can become valuable coding assistants in the trading world.