cjelsa/trading-strategy

Python framework for quantitative financial analysis and trading algorithms on decentralised exchanges

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 trading strategies as on-chain smart contracts where users can invest and withdraw with their wallets

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. See example notebooks.

• Write algorithmic trading strategies for decentralised exchange

Getting started

See the Getting Started tutorial and the rest of the Trading Strategy documentation.

Prerequisites

• Python 3.10

Installing the package

Note: Unless you are an experienced Python developer, try the Binder cloud hosted Jupyter notebook examples first.

You can install this package with

poetry:

poetry add trading-strategy

pip:

pip install trading-strategy 

Documentation

• Read Trading Strategy documentation.
• Documentation Github repository.

Community

• Trading Strategy website

• Blog

• Twitter

• Discord

• Telegram channel

• Changelog and version history

Read more documentation how to develop this package.

License

GNU AGPL 3.0.