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Intuitive backtesting for quantitative trading strategies.

Project description

Radium

Radium-Tech is a Python package providing an intuitive backtesting and visualisation platform for quantitative trading strategies.

Main Features

In current version Radium-Tech can:

  • Plot price data for multiple equities.
  • Regress hedge ratios and price spread for a pair of equities.
  • Conduct tests for cointegration on pairs of equities.
  • Backtest a Bollinger Band strategy.

Future versions aim to add additonal mean-reversing strategies.

Where to get it

The latest public version of Radium-Tech is avaliable on Python Package Index (PyPI)

pip install Radium-Tech

Dependencies

Radium-Tech requires:

  • numpy
  • pandas
  • matplotlib
  • statsmodels
  • requests

An Alpha-Vantage free API key is also required for equity data.

Documentation

Official documentation for Radium-Tech is hosted on readthedocs.io: https://radium-tech.readthedocs.io/en/latest/

They can be downloaded in PDF form: https://radium-tech.readthedocs.io/_/downloads/en/latest/pdf/

Example

An example full backtest cycle can be found in Radium-Tech/Examples/bollinger.py

from radium import Equity, Pair
from radium.pair import johansen_test
from radium.strategy import BollingerPair

# Alpha-vantage API Key
API_KEY = ''

# Creates equity, pair objects for visa and mastercard 2015-2021
visa = Equity('V', '2015-01-01', '2021-01-01', API_KEY)
mastercard = Equity('MA', '2015-01-01', '2021-01-01', API_KEY)
v_ma = Pair(visa, mastercard)

# Visualise data
v_ma.plot()

# Test for cointegration
johansen_test(v_ma)

# Backtest Bollinger band strategy on pair
entry_z = 1
exit_z = 0
lookback = 30
v_ma_bollinger = BollingerPair(v_ma, entry_z, exit_z, lookback)

# Evaluate strategy
sharpe = v_ma_bollinger.sharpe()
ann_returns = v_ma_bollinger.ann_returns()

print(f"Sharpe ratio: {sharpe}")
print(f"Annualised returns: {ann_returns}")

Authors

Radium-Tech is developed by Ivan Erlic and Callum Rai of University College London.

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