Python Backtesting library for trading strategies
$ npx skills add mementum/backtraderAlternatives
Compare similar skills by workflow fit, trust score, quality, GitHub adoption, maintenance, and install readiness.
Current skill
An extension for Nautilus Trader
Python Backtesting library for trading strategies
$ npx skills add mementum/backtrader基于Python的开源量化交易平台开发框架
$ npx skills add vnpy/vnpylow code backtesting library utilizing pandas and technical analysis indicators
$ npx skills add jrmeier/fast-tradeTradingAgents: Multi-Agents LLM Financial Trading Framework
$ npx skills add TauricResearch/TradingAgentsQUANTAXIS 支持任务调度 分布式部署的 股票/期货/期权 数据/回测/模拟/交易/可视化/多账户 纯本地量化解决方案
$ npx skills add yutiansut/QUANTAXISOpen-source Rust framework for building event-driven live-trading & backtesting systems
$ npx skills add barter-rs/barter-rs30天掌握量化交易 (持续更新)
$ npx skills add Rockyzsu/stock🔎 📈 🐍 💰 Backtest trading strategies in Python.
$ npx skills add kernc/backtesting.py天勤量化开发包, 期货量化, 实时行情/历史数据/实盘交易
$ npx skills add shinnytech/tqsdk-pythonefinance 是一个可以快速获取基金、股票、债券、期货数据的 Python 库,回测以及量化交易的好帮手!🚀🚀🚀
$ npx skills add Micro-sheep/efinance$ npx skills add refraction-ray/xalphaFinRL®-Meta: Dynamic datasets and market environments for FinRL.
$ npx skills add AI4Finance-Foundation/FinRL-MetaAKQuant is a high-performance quantitative research and trading framework built on Rust and Python! 开源量化回测框架
$ npx skills add akfamily/akquant台灣股市股票價格擷取 (含即時股票資訊) - Taiwan Stock Opendata with realtime
$ npx skills add mlouielu/twstockFramework for quantitative trading. Complete framework for development, backtesting, and deploying automated trading algorithms and trading bots.
$ npx skills add coding-kitties/investing-algorithm-frameworkdj-stripe automatically syncs your Stripe Data to your local database as pre-implemented Django Models allowing you to use the Django ORM, in your code, to work with the data making it easier and faster.
$ npx skills add dj-stripe/dj-stripeHow to choose
Use an alternative when it has a clearer install path, higher trust score, fresher maintenance, or better platform fit for your current agent stack. Keep Prediction Market Backtesting if it already passes your workflow test and repository review.
Next step
Open the compare page, test the install commands in a sandbox, and check each repository before using a skill in production.