Automated Stock Trading System

I run a trading desk and I’m ready to hand-off the routine work to code. My goal is a fully automated stock-trading workflow that draws on modern AI/LLM techniques and talks seamlessly to Excel, my preferred front-end for quick checks and ad-hoc tweaks.

Here’s what I need the solution to cover:

• Market analysis – real-time data ingestion, pattern recognition, and signal generation driven by an LLM or other AI models.
• Trade execution – automated order placement and management through a broker API with tight latency control and clear error handling.
• Performance reporting – instant P&L, risk metrics, and strategy diagnostics pushed into dynamic Excel dashboards for daily review.

I’m open on the tech stack as long as it supports Python-based AI libraries (e.g., TensorFlow, PyTorch, LangChain) and connects smoothly to both Excel (via VBA or the Python Excel add-ins) and mainstream brokerage APIs. If you have proprietary shortcuts or pre-trained models that can speed things up, all the better.

Acceptance criteria
1. A script or containerised app that runs end-to-end in a test environment, from data pull to trade confirmation.
2. Back-test results for at least six months of historical data showing the signals behave as intended.
3. An Excel workbook that refreshes automatically and presents key performance metrics.
4. Clear setup documentation so I can maintain and extend the system without chasing you down.

If this sounds like your wheelhouse, let’s discuss your approach and timeline.