bill
d794910697
Two-person trading team setup: Bill (quant/algorithmic) and Colette (market observer). Includes phase-by-phase curriculum, separate sprint tracks, trade journal templates, roadmap to prop firm challenge, and agent handoff documentation. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
1.6 KiB
1.6 KiB
Bill — Sprint 01: Market Data Infrastructure
Track: Quant / Algorithmic — Phase 1 Duration: 2 weeks Goal: Get a working data pipeline and understand the data landscape before building anything on top of it.
Tasks
Environment Setup
- Create Python virtual environment in
~/trading/bill/scripts/ - Install:
yfinance pandas pandas-ta matplotlib sqlite3 requests - Verify TradingView Pine Script editor opens (Chart → Pine Editor)
Data Pipeline
- Write a script that pulls daily OHLCV for a list of tickers via yfinance
- Store results in SQLite or Parquet in
~/trading/bill/backtests/data/ - Handle edge cases: missing data, stock splits, delisted tickers
- Pull at least 5 years of history for SPY, QQQ, and 3 tickers of your choice
TradingView Orientation
- Write a basic Pine Script indicator (start with a simple EMA crossover)
- Understand how TradingView alerts work and what webhook delivery looks like
- Explore the built-in Strategy Tester — understand what the equity curve and metrics mean
Research
- Survey free vs paid data sources (yfinance limitations, Alpaca, Polygon.io)
- Understand what a prop firm's execution environment looks like — do they support algos?
- Read one article on walk-forward validation vs simple train/test split
Deliverable
A script (fetch_data.py) that:
- Takes a list of tickers and a date range
- Fetches OHLCV from yfinance
- Saves to local storage
- Prints a summary: rows fetched, date range, any gaps flagged
Notes
(add as you go)