Algorithmic trading and quantitative financial analysis framework for decentralised exchanges and blockchains
Project description
Trading Strategy framework for Python
Trading Strategy framework is a Python framework for algorithmic trading on decentralised exchanges. It is using backtesting data and real-time price feeds from Trading Strategy Protocol.
Use cases
-
Analyse cryptocurrency investment opportunities on decentralised exchanges (DEXes)
-
Creating trading algorithms and trading bots that trade on DEXes
-
Deploy investable trading strategies as on-chain smart contracts
Features
-
Supports multiple blockchains like Ethereum mainnet, Binance Smart Chain and Polygon
-
Access trading data from on-chain decentralised exchanges like SushiSwap, QuickSwap and PancakeSwap
-
Integration with Jupyter Notebook for easy manipulation of data
-
Utilise Python quantita frameworks like Backtrader and QSTrader to create, analyse and backtest DEX trading algorithms
Example and getting started
See the Getting Started notebook and the rest of the Trading Strategy documentation.
Prerequisites
Python 3.9+
Installing the package
Note: Unless you are an experienced Python developer, the suggested usage of Trading Algorithm framework is using Google Colab hosted environments.
You can install this package with poetry
or pip
poetry add trading-strategy
pip install trading-strategy
For QSTrader based trading algorithm support you need to install the related optional dependencies:
poetry add trading-strategy[qstrader]
Documentation
Community
Read more documentation how to develop this package.
License
GNU AGPL 3.0.
Project details
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