pqr 1.0.1

Lightweight library for backtesting factor strategies

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

MIT