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QuantLab

Reproducible quantitative research platform for cryptocurrency trading research. See CLAUDE.md for full project intent, principles, and milestone roadmap.

Primary data source: Bybit V5 API (USDT Perpetual, starting with BTCUSDT 1h).

Setup

uv venv --python 3.12
source .venv/bin/activate
uv pip install -e ".[dev]"

Development

ruff check .
pytest

Status

Milestones 0-6 complete, Milestone 7 partial: bootstrap, Bybit read-only data client, dataset pipeline (raw -> normalized -> validated Parquet), backtest engine (fees/slippage, signal/execution-time separation, drawdown, evaluation metrics), baseline strategies (Buy & Hold, momentum, moving-average crossover, mean reversion, RSI), the research protocol (train/validation/test splitting, walk-forward windows, experiment record schema, reproducible seeding), classical ML (causal feature pipeline, Logistic Regression, LightGBM, XGBoost), and a PyTorch MLP classifier. LSTM/TCN/Transformer are not started (need sequence-windowed input). See docs/roadmap.md for full status.

LightGBM requires libomp on macOS: brew install libomp.

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Reproducible quantitative research platform for cryptocurrency trading research.

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