Stock Trading Bot

Problem

Describe the user pain, gap, or technical challenge that motivated the work.

Solution

A Python stock trading bot adapted from the crypto bot, focused on regime-adaptive cross-sectional momentum, Webull account linking, Polygon data, risk controls, and Telegram-first operation.

Tech Stack

Python, Telegram Bot API, Webull, Polygon.io, yfinance, PostgreSQL, Backtesting

Features

• Cross-sectional momentum strategy for US equities
• Webull paper/live execution path with encrypted credential linking
• Polygon and yfinance data providers with local caching
• Telegram dashboard, watchlist, positions, trades, and performance commands
• Premarket scans, weekly momentum rebalance, session runner, reconciliation, and reports
• Risk tooling for ATR sizing, PDT awareness, loss limits, sector caps, correlation, and PEVL vetoes

Architecture & Development Process

Challenges

• Porting crypto bot architecture to equities while accounting for market hours and PDT constraints
• Testing survivorship-free momentum ideas with realistic costs and stress gates
• Keeping live execution aligned with the backtested rebalance and veto logic

Lessons Learned

• Equities automation needs market-calendar awareness and stricter operational reconciliation
• Stress gates and drawdown throttles are core strategy components, not optional overlays
• Paper trading and smoke tests should come before live deployment

Roadmap

• Expand paper-trading validation
• Improve live reconciliation UX
• Add more transparent reporting around regime gates