trading-strategy
Unverified Arbitrage strategy on Crypto by tradingstrategy-ai. BotFinder score 18 out of 100.
Python framework for quantitative financial analysis and trading algorithms on decentralised exchanges
Source: github
BotFinder analysis pending.
trading-strategy
Trading Strategy framework for Python Trading Strategy framework is a Python framework for algorithmic trading on decentralised exchanges. - Download decentralised finance market data sets - Develop and backtest trading strategies in Jupyter Notebook - Live trade execution for onchain trading - Smart contract vault support for turning your trading strategy to a third-party investable vault The trading-strategy library provides data fetching for backtesting and live trading. 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 exam
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