644 stars · Apache-2.0 · 0.4.5 (2025-07-23)
Factor analysis for trading signals: does this feature actually predict returns, before a strategy is built on it.
▶Repo detailsthe review · specs · pros & cons · install
What it is
A maintained continuation of Quantopian's Alphalens, kept alive by Stefan Jansen. It takes a factor — any number you compute per instrument per day — and reports the returns, the ranking, the turnover and the decay that follow from it.What it is good for. Anybody researching trading signals. It sits before the backtester, not after it. A backtest tells you what one set of rules did. This tells you whether the underlying signal carries information at all, which is a cheaper and more honest question to ask first.For ScalpingMate this is the step that belongs before any strategy work on EURUSD. Test the signal, then build.
- Answers the cheap question before you spend weeks on the expensive one.
- Its charts are the standard vocabulary of factor research, so the output is easy to discuss with anybody in the field.
- Apache-2.0, so there is no licence trap in commercial use.
- It was built around daily stock data. Applying it to intraday currency data means reshaping your inputs yourself.
- Version 0.4.6 on PyPI dates from June 2025, and the last code landed on 15 December 2025 — a little over eight months ago. It is a maintained fork of a finished project, not a fast-moving one.
- The output takes some learning. The charts assume you already know what a quantile spread is.
source venv/bin/activate pip install alphalens-reloaded # Documentation: https://alphalens.ml4trading.io