filib 0.1.0

Factor Investing Library

Factor Investing LIBrary is a lightweight algorithmic trading Python library built for easy testing of predictive factors and portfolio rebalance via Oanda. Inspired by and compatible with Quantopian Open Source.

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Installation

Install with pip:

$ pip install filib

Check requirements.txt for dependencies.

Usage

Write and execute a script based on following template:

from filib.oanda import Oanda  # Currently only Oanda is available
from filib.helpers import *    # Optional functions, useful for factor generation


class MyFactors(Oanda):

    def momentum(self):  # Hypothesis: there is persistence in an asset's performance
        factor = self.returns
        split = [-1, -.003, .003, 1]  # List of thresholds or int to split equally
        return factor, split  # Always return atleast factor and follow this order

    def relative_strenght_index(self):
        import pandas as pd
        import pandas_ta as ta  # Sample Technical Analysis Library
        factor = pd.DataFrame({
            instrument: self.price_data[instrument].ta.rsi(length=14)
            for instrument, _ in self.price_data
        }) * -1  # Short low factor values and long high factor values
        split = [-100, -70, -30, 0]
        return factor, split

    def big_mac_index(self):
        import quandl  # Sample Financial, Economic and Alternative Data Library
        iso_codes = get_iso_codes(self.price_data)
        codes = [f'ECONOMIST/BIGMAC_{COUNTRY}.5' for COUNTRY in iso_codes]
        factor = quandl.get(codes).dropna(how='all', axis=1)
        factor.columns = [iso_codes[c.split('_')[1].split()[0]] for c in factor]
        factor.index = factor.index.tz_localize('UTC')  # Convert time zone to UTC
        return factor  # If not specified split = 3 by default


if __name__ == "__main__":

    strategy = MyFactors(  # Initialize strategy
        instruments = ['EUR_USD', 'GBP_USD', 'USD_JPY', 'AUD_USD', 'NZD_USD',
                       'USD_CAD', 'USD_CHF', 'USD_NOK', 'USD_SEK'],  # Define universe
        granularity = 'D',    # Time range between rebalancing and between each candle
        count = 500,          # Number of historical candles to return for analysis
        symbol = 'USD',       # Optional, specify symbol to arrange your price data
        periods = (1, 2, 3),  # Optional, specify periods to analyze factor decay
        split = 3,            # Number of quantiles to split your combined factor data
        accountID = '',       # Your Oanda's account ID for creating orders
        target = .8,          # Set portfolio value target
        long_short = True,    # Trade only top and bottom quantile of combined factor
    )

    strategy.performance()  # Check performance of your factors combined together
    strategy.performance('momentum')  # Check performance for individual factors
    [strategy.performance(factor) for factor in strategy.factors]

    strategy.rebalance()  # Generate orders needed to rebalance your portfolio
    strategy.rebalance(live=True)  # Actually place orders
    # PLEASE USE AT YOUR OWN RISK - THIS CAN TRADE REAL MONEY - NO WARRANTY IS GIVEN

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.