Day 1 - Algo Trading
Day 1.
I’ve been building a trading bot designed to trade while I’m at work. My work hours cause me to miss a lot of the best intraday moves, so the idea was to create something that could identify and manage opportunities without me needing to sit in front of the chart all day.
I’m a Computer Science student, so this is both a passion project and a learning project. It combines automation, strategy logic, realtime data, Discord alerts, risk management, machine learning filters, and an OpenAI powered advisor layer.
Right now the bot is focused on NQ scalping using an ATM-style setup of about 3.0 points risk for 5.0 points reward.
The edge is not just about calling entries. The bigger focus is automated management:
- Profit protection
- Smart scale-ins
- Management at 25%, 50%, 75%, and 100% progress to target
- ML-based filtering
- Adaptive feedback from trade results and market conditions
I’m not trying to give away the full strategy logic, but the goal is to test whether the system can consistently manage trades better than I can manually.
The challenge starts today: 5 profitable days in a row with zero human interference.
I’m open to answering some questions about the stack and how I got started but, this post is for journaling for the most part!