Lightweight library for backtesting factor strategies
Project description
pqr
pqr is a python library for backtesting factor strategies. It is built in top of numpy, so it is fast and memory efficient, but provides pandas interface to make usage more convenient and verbose.
Installation
Use the package manager pip to install pqr.
pip install pqr
Quickstart
import pandas as pd
import pqr
prices = pd.read_csv("prices.csv", parse_dates=True)
momentum = pqr.compose(
# picking
pqr.freeze(pqr.filter, universe=prices > 10),
pqr.freeze(pqr.look_back, period=12, agg="pct"),
pqr.freeze(pqr.lag, period=1),
pqr.freeze(pqr.hold, period=12),
pqr.freeze(pqr.quantiles, min_q=0.7, max_q=1),
# allocation
pqr.ew,
# evaluation
pqr.freeze(pqr.evaluate, universe_returns=pqr.to_returns(prices)),
)
# returns series of returns of 30% ew momentum 12-1-12 strategy for stocks > 10$
momentum(prices)
Documentation
The official documentation is hosted on readthedocs.org: https://pqr.readthedocs.io/en/latest/
Contributing
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.
Please make sure to update tests and documentation as appropriate.
License
Release history Release notifications | RSS feed
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