QUANTAXIS 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/QUANTAXISAlternatives
Compare similar skills by workflow fit, trust score, quality, GitHub adoption, maintenance, and install readiness.
Current skill
基于Python的开源量化交易平台开发框架
QUANTAXIS 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/QUANTAXIS30天掌握量化交易 (持续更新)
$ npx skills add Rockyzsu/stock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-pythonTradingAgents: Multi-Agents LLM Financial Trading Framework
$ npx skills add TauricResearch/TradingAgents中国的Quant相关资源索引
$ npx skills add thuquant/awesome-quant$ npx skills add refraction-ray/xalphaFinRL®-Meta: Dynamic datasets and market environments for FinRL.
$ npx skills add AI4Finance-Foundation/FinRL-Meta开放式的缠论python实现框架,支持形态学/动力学买卖点分析计算,多级别K线联立,区间套策略,可视化绘图,多种数据接入,策略开发,交易系统对接;
$ npx skills add Vespa314/chan.pyQlib is an AI-oriented Quant investment platform that aims to use AI tech to empower Quant Research, from exploring ideas to implementing productions. Qlib supports diverse ML modeling paradigms, including supervised learning, market dynamics modeling, and RL, and is now equipped with https://github.com/microsoft/RD-Agent to automate R&D process.
$ npx skills add microsoft/qlibHikyuu Quant Framework 基于C++/Python的超高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。
$ npx skills add fasiondog/hikyuu缠中说禅技术分析工具;缠论;股票;期货;Quant;量化交易
$ npx skills add waditu/czscFree trading strategies for Freqtrade bot
$ npx skills add freqtrade/freqtrade-strategiesA vector index built on TurboQuant, written in Rust with Python bindings
$ npx skills add RyanCodrai/turbovecSimple connector to Binance Public API
$ npx skills add binance/binance-connector-pythonCryptocurrency Exchange REST API SDK Wrapper Implemented With the golang, Supporting OKX, Binance
$ npx skills add nntaoli-project/goexPython wrapper for TA-Lib (http://ta-lib.org/).
$ npx skills add TA-Lib/ta-lib-pythonHow 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 Vnpy 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.