{"repo":"coding-kitties/investing-algorithm-framework","free":true,"listed":false,"github":"https://github.com/coding-kitties/investing-algorithm-framework","clone":"git clone https://github.com/coding-kitties/investing-algorithm-framework.git","description":"Framework for quantitative trading. Complete framework for development, backtesting, and deploying automated trading algorithms and trading bots.","language":"Python","stars":1702,"topics":["trading-bot","cryptocurrency","algorithmic-trading","trade","python","trading","trading-strategies","backtesting","backtesting-trading-strategies","trading-bots"],"license":"Apache-2.0","category":"trading","readme_excerpt":"Investing Algorithm Framework The full quant workflow in one framework: build strategies, vector & event-driven backtest at scale, compare in a single dashboard, and deploy the winner 🚀 Proudly sponsored by Introduction v9.0.0 alpha is out! The pre-release of v9.0 is now available on PyPI as an alpha pre-release. Since pip doesn't install pre-releases by default, pin the version explicitly or pass --pre : You can find the blog post here: v9.0 Release. Investing Algorithm Framework is a Python framework that covers the entire quant workflow: define a strategy once, vector-backtest thousands of parameter variants to find promising signals, narrow down with a storage layer that ranks 10k+ results in milliseconds, validate the winners in a realistic event-driven simulation, compare everything in a single interactive HTML dashboard, and deploy the best performer live, all with the same TradingStrategy class, no code rewrites between stages. Most quant frameworks stop at \"here's your backtest result.\" You get a number, maybe a chart, and then you're on your own figuring out which strategy variant is actually better, whether the result is robust across time windows, and how to go from research to production. This framework closes that gap. Want to see this in practice? Check out the examples/tutorial/ : a series of runnable notebooks that walk you through every stage: defining a strategy, visualizing its signals, sweeping parameters across rolling windows, detecting overfitting wit","default_branch":null,"files":null,"tree":[],"storefront":"/r/coding-kitties","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/coding-kitties/investing-algorithm-framework/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}