Radium-Tech 0.0.4

Intuitive backtesting for quantitative trading strategies.

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 cadf_test, johansen_test
from radium.strategy import BollingerPair


# Alpha-vantage API Key
API_KEY = ''

# Creates equity, pair objects for visa and mastercard 2015-2021
equity1 = Equity('KO', '2016-01-01', '2021-01-01', API_KEY)
equity2 = Equity('SBUX', '2016-01-01', '2021-01-01', API_KEY)
pair = Pair(equity1, equity2)

# Visualise data
pair.plot_closed()

# Test for cointegration
cadf_test(pair)
johansen_test(pair)

# Hedge the pair
pair.hedge('OLS', 30)

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

# Evaluate strategy
CAGR = bollinger.CAGR
sharpe = bollinger.sharpe

print(f"Compound Annual Growth Rate: {CAGR}")
print(f"Sharpe ratio: {sharpe}")

Authors

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