AI-Powered Stock Trading Automation

Overview

This project is a stock trading automation platform that integrates Interactive Brokers (IBKR) with Python, SQL, custom Tkinter UI, APIs, and AI models. The system is designed to move from raw public information to live trading decisions with minimal manual intervention.

For confidentiality, I don’t share the specific mechanics of the strategy or the exact signals it uses. At a high level, the system ingests public data, runs it through AI models to interpret the information, develops a trading plan, and then executes orders automatically in a very short amount of time. The focus of this project is on automation, reliability, and performance.

High-Level Flow

• Pulls public market and contextual data via APIs.
• Processes and stores data using SQL for structured access and logging.
• Uses AI models to interpret information and generate trading insights.
• Translates insights into orders and sends them to IBKR via their API.
• Monitors positions, basic risk parameters, and status through a custom Tkinter UI.

Key Skills & Tools

• Python – core application logic and automation.
• IBKR API – order routing, account data, and position management.
• SQL – storing configuration, logs, and historical data.
• CustomTkinter – building a modern, desktop-style control panel UI.
• APIs & AI – integrating external data and AI models for decision support.