Quantitative research toolkit in Python.
Helpers for the research workflow: loading market data, computing signals, running backtests, and analyzing results. Used in notebooks and batch research jobs across the OG Capital research team.
pip install -e .Requires Python 3.11+.
from quant_research import data, signals, backtest
bars = data.load_bars("BTC-USD", "2024-01-01", "2024-12-31")
sig = signals.momentum(bars, window=20)
result = backtest.run(bars, sig, capital=100_000)
print(result.sharpe, result.max_drawdown)Internal component. Research-grade code — not hardened for production use.