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
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Analyse cryptocurrency investment opportunities on decentralised exchanges (DEXes)
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Creating trading algorithms and trading bots that trade on DEXes
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Deploy trading strategies as on-chain smart contracts where users can invest and withdraw with their wallets
Features
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Supports multiple blockchains like Ethereum mainnet, Binance Smart Chain and Polygon
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Access trading data from on-chain decentralised exchanges like SushiSwap, QuickSwap and PancakeSwap
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Integration with Jupyter Notebook for easy manipulation of data. See example notebooks.
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Write algorithmic trading strategies for decentralised exchange
Getting started
See the Getting Started tutorial and the rest of the Trading Strategy documentation.
Prerequisites
Python 3.9+
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
Community
Read more documentation how to develop this package.
License
GNU AGPL 3.0.
Project details
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