Python Backtesting library for trading strategies
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Updated
Aug 19, 2024 - Python
Python Backtesting library for trading strategies
Open source software that helps you create and deploy high-frequency crypto trading bots
Algorithmic trading and quantitative trading open source platform to develop trading robots (stock markets, forex, crypto, bitcoins, and options).
🔎 📈 🐍 💰 Backtest trading strategies in Python.
stock股票.获取股票数据,计算股票指标,识别股票形态,综合选股,选股策略,股票验证回测,股票自动交易,支持PC及移动设备。
Find your trading edge, using the fastest engine for backtesting, algorithmic trading, and research.
Open source crypto trading bot
modular quant framework.
Hikyuu Quant Framework 基于C++/Python的极速开源量化交易研究框架,同时可基于策略部件进行资产重用,快速累积策略资产。
A curated list of insanely awesome libraries, packages and resources for systematic trading. Crypto, Stock, Futures, Options, CFDs, FX, and more | 量化交易 | 量化投资
Algorithmic Trading in Python with Machine Learning
A high-frequency trading and market-making backtesting and trading bot in Python and Rust, which accounts for limit orders, queue positions, and latencies, utilizing full tick data for trades and order books, with real-world crypto market-making examples for Binance Futures
Python Crypto Bot (PyCryptoBot)
📈 Get real-time stocks from TradingView
fastquant — Backtest and optimize your ML trading strategies with only 3 lines of code!
Python AutoML for Trading Systems and Sports Betting
Backtest 1000s of minute-by-minute trading algorithms for training AI with automated pricing data from: IEX, Tradier and FinViz. Datasets and trading performance automatically published to S3 for building AI training datasets for teaching DNNs how to trade. Runs on Kubernetes and docker-compose. >150 million trading history rows generated from +…
Open-source Rust framework for building event-driven live-trading & backtesting systems
A nimble options backtesting library for Python
Stock Indicators for .NET is a C# NuGet package that transforms raw equity, commodity, forex, or cryptocurrency financial market price quotes into technical indicators and trading insights. You'll need this essential data in the investment tools that you're building for algorithmic trading, technical analysis, machine learning, or visual charting.
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