20 results for “topic:qlib”
[🔥updating ...] AI 自动量化交易机器人(完全本地部署) AI-powered Quantitative Investment Research Platform. 📃 online docs: https://ufund-me.github.io/Qbot ✨ :news: qbot-mini: https://github.com/Charmve/iQuant
Qlib-Server is the data server system for Qlib. It enable Qlib to run in online mode. Under online mode, the data will be deployed as a shared data service. The data and their cache will be shared by all the clients. The data retrieval performance is expected to be improved due to a higher rate of cache hits. It will consume less disk space, too.
qlib助手, 每日自动预测a股 👇
Qbot 微信小程序: 自选基金/股票助手、策略选股、股票盯盘、量化投研智库
Introduction to the decoupling solutions of qlib, an open-source software library for signal processing and machine learning.
基于微软QLib框架构建的一站式量化因子研究与策略回测解决方案，通过Streamlit提供友好的Web界面，降低量化研究的技术门槛。
Quant Trading with Microsoft Qlib (https://github.com/microsoft/qlib)
AutoQuant is an out-of-the-box quantitative investment platform.
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监控全球流动性，新闻分析，链上鲸鱼流动方向，基于deepseek r1 AI agent + qlib 多币种，4小时低频量化交易系统Global liquidity & on-chain whale monitoring. 4h low-frequency quant trading system powered by DeepSeek R1 AI Agent + Qlib.
🚀 Professional quantitative trading research platform with ML-powered backtesting, multi-source options analysis, portfolio management, and interactive Plotly visualizations. Built on qlib with CLI interface.
An advanced, production-ready quantitative trading system built on top of Microsoft Qlib
AI-powered Quantitative Investment Research Platform.
A queue abstraction library to support leasing and buffering in Elixir.
📊 Empower your quantitative research with Qlib, a comprehensive library for AI-driven stock market analysis and prediction.
使用rust处理qlib所需数据
Microsoft Qlib MCP Server - 让 AI Agent 直接调用 Qlib 做量化研究。支持数据查询、因子分析、策略回测。
一个面向 A 股研究流程的 Qlib 工作台，支持收盘后数据校验、滚动训练、推荐日报、复盘回测和 ClawTeam 任务编排。
Autonomous quant factor R&D with Claude Code + Qlib + RD-Agent. Replaces OpenAI with Claude subagents + Codex CLI.
End-to-end quantitative trading system for Taiwan stocks — DoubleEnsemble model, 300+ factors, Walk-Forward backtesting, React dashboard