[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"similar-EliteQuant--EliteQuant":3,"tool-EliteQuant--EliteQuant":61},[4,18,26,36,44,53],{"id":5,"name":6,"github_repo":7,"description_zh":8,"stars":9,"difficulty_score":10,"last_commit_at":11,"category_tags":12,"status":17},4358,"openclaw","openclaw\u002Fopenclaw","OpenClaw 是一款专为个人打造的本地化 AI 助手，旨在让你在自己的设备上拥有完全可控的智能伙伴。它打破了传统 AI 助手局限于特定网页或应用的束缚，能够直接接入你日常使用的各类通讯渠道，包括微信、WhatsApp、Telegram、Discord、iMessage 等数十种平台。无论你在哪个聊天软件中发送消息，OpenClaw 都能即时响应，甚至支持在 macOS、iOS 和 Android 设备上进行语音交互，并提供实时的画布渲染功能供你操控。\n\n这款工具主要解决了用户对数据隐私、响应速度以及“始终在线”体验的需求。通过将 AI 部署在本地，用户无需依赖云端服务即可享受快速、私密的智能辅助，真正实现了“你的数据，你做主”。其独特的技术亮点在于强大的网关架构，将控制平面与核心助手分离，确保跨平台通信的流畅性与扩展性。\n\nOpenClaw 非常适合希望构建个性化工作流的技术爱好者、开发者，以及注重隐私保护且不愿被单一生态绑定的普通用户。只要具备基础的终端操作能力（支持 macOS、Linux 及 Windows WSL2），即可通过简单的命令行引导完成部署。如果你渴望拥有一个懂你",349277,3,"2026-04-06T06:32:30",[13,14,15,16],"Agent","开发框架","图像","数据工具","ready",{"id":19,"name":20,"github_repo":21,"description_zh":22,"stars":23,"difficulty_score":10,"last_commit_at":24,"category_tags":25,"status":17},3808,"stable-diffusion-webui","AUTOMATIC1111\u002Fstable-diffusion-webui","stable-diffusion-webui 是一个基于 Gradio 构建的网页版操作界面，旨在让用户能够轻松地在本地运行和使用强大的 Stable Diffusion 图像生成模型。它解决了原始模型依赖命令行、操作门槛高且功能分散的痛点，将复杂的 AI 绘图流程整合进一个直观易用的图形化平台。\n\n无论是希望快速上手的普通创作者、需要精细控制画面细节的设计师，还是想要深入探索模型潜力的开发者与研究人员，都能从中获益。其核心亮点在于极高的功能丰富度：不仅支持文生图、图生图、局部重绘（Inpainting）和外绘（Outpainting）等基础模式，还独创了注意力机制调整、提示词矩阵、负向提示词以及“高清修复”等高级功能。此外，它内置了 GFPGAN 和 CodeFormer 等人脸修复工具，支持多种神经网络放大算法，并允许用户通过插件系统无限扩展能力。即使是显存有限的设备，stable-diffusion-webui 也提供了相应的优化选项，让高质量的 AI 艺术创作变得触手可及。",162132,"2026-04-05T11:01:52",[14,15,13],{"id":27,"name":28,"github_repo":29,"description_zh":30,"stars":31,"difficulty_score":32,"last_commit_at":33,"category_tags":34,"status":17},1381,"everything-claude-code","affaan-m\u002Feverything-claude-code","everything-claude-code 是一套专为 AI 编程助手（如 Claude Code、Codex、Cursor 等）打造的高性能优化系统。它不仅仅是一组配置文件，而是一个经过长期实战打磨的完整框架，旨在解决 AI 代理在实际开发中面临的效率低下、记忆丢失、安全隐患及缺乏持续学习能力等核心痛点。\n\n通过引入技能模块化、直觉增强、记忆持久化机制以及内置的安全扫描功能，everything-claude-code 能显著提升 AI 在复杂任务中的表现，帮助开发者构建更稳定、更智能的生产级 AI 代理。其独特的“研究优先”开发理念和针对 Token 消耗的优化策略，使得模型响应更快、成本更低，同时有效防御潜在的攻击向量。\n\n这套工具特别适合软件开发者、AI 研究人员以及希望深度定制 AI 工作流的技术团队使用。无论您是在构建大型代码库，还是需要 AI 协助进行安全审计与自动化测试，everything-claude-code 都能提供强大的底层支持。作为一个曾荣获 Anthropic 黑客大奖的开源项目，它融合了多语言支持与丰富的实战钩子（hooks），让 AI 真正成长为懂上",150720,2,"2026-04-11T11:33:10",[14,13,35],"语言模型",{"id":37,"name":38,"github_repo":39,"description_zh":40,"stars":41,"difficulty_score":32,"last_commit_at":42,"category_tags":43,"status":17},2271,"ComfyUI","Comfy-Org\u002FComfyUI","ComfyUI 是一款功能强大且高度模块化的视觉 AI 引擎，专为设计和执行复杂的 Stable Diffusion 图像生成流程而打造。它摒弃了传统的代码编写模式，采用直观的节点式流程图界面，让用户通过连接不同的功能模块即可构建个性化的生成管线。\n\n这一设计巧妙解决了高级 AI 绘图工作流配置复杂、灵活性不足的痛点。用户无需具备编程背景，也能自由组合模型、调整参数并实时预览效果，轻松实现从基础文生图到多步骤高清修复等各类复杂任务。ComfyUI 拥有极佳的兼容性，不仅支持 Windows、macOS 和 Linux 全平台，还广泛适配 NVIDIA、AMD、Intel 及苹果 Silicon 等多种硬件架构，并率先支持 SDXL、Flux、SD3 等前沿模型。\n\n无论是希望深入探索算法潜力的研究人员和开发者，还是追求极致创作自由度的设计师与资深 AI 绘画爱好者，ComfyUI 都能提供强大的支持。其独特的模块化架构允许社区不断扩展新功能，使其成为当前最灵活、生态最丰富的开源扩散模型工具之一，帮助用户将创意高效转化为现实。",108322,"2026-04-10T11:39:34",[14,15,13],{"id":45,"name":46,"github_repo":47,"description_zh":48,"stars":49,"difficulty_score":32,"last_commit_at":50,"category_tags":51,"status":17},6121,"gemini-cli","google-gemini\u002Fgemini-cli","gemini-cli 是一款由谷歌推出的开源 AI 命令行工具，它将强大的 Gemini 大模型能力直接集成到用户的终端环境中。对于习惯在命令行工作的开发者而言，它提供了一条从输入提示词到获取模型响应的最短路径，无需切换窗口即可享受智能辅助。\n\n这款工具主要解决了开发过程中频繁上下文切换的痛点，让用户能在熟悉的终端界面内直接完成代码理解、生成、调试以及自动化运维任务。无论是查询大型代码库、根据草图生成应用，还是执行复杂的 Git 操作，gemini-cli 都能通过自然语言指令高效处理。\n\n它特别适合广大软件工程师、DevOps 人员及技术研究人员使用。其核心亮点包括支持高达 100 万 token 的超长上下文窗口，具备出色的逻辑推理能力；内置 Google 搜索、文件操作及 Shell 命令执行等实用工具；更独特的是，它支持 MCP（模型上下文协议），允许用户灵活扩展自定义集成，连接如图像生成等外部能力。此外，个人谷歌账号即可享受免费的额度支持，且项目基于 Apache 2.0 协议完全开源，是提升终端工作效率的理想助手。",100752,"2026-04-10T01:20:03",[52,13,15,14],"插件",{"id":54,"name":55,"github_repo":56,"description_zh":57,"stars":58,"difficulty_score":32,"last_commit_at":59,"category_tags":60,"status":17},4721,"markitdown","microsoft\u002Fmarkitdown","MarkItDown 是一款由微软 AutoGen 团队打造的轻量级 Python 工具，专为将各类文件高效转换为 Markdown 格式而设计。它支持 PDF、Word、Excel、PPT、图片（含 OCR）、音频（含语音转录）、HTML 乃至 YouTube 链接等多种格式的解析，能够精准提取文档中的标题、列表、表格和链接等关键结构信息。\n\n在人工智能应用日益普及的今天，大语言模型（LLM）虽擅长处理文本，却难以直接读取复杂的二进制办公文档。MarkItDown 恰好解决了这一痛点，它将非结构化或半结构化的文件转化为模型“原生理解”且 Token 效率极高的 Markdown 格式，成为连接本地文件与 AI 分析 pipeline 的理想桥梁。此外，它还提供了 MCP（模型上下文协议）服务器，可无缝集成到 Claude Desktop 等 LLM 应用中。\n\n这款工具特别适合开发者、数据科学家及 AI 研究人员使用，尤其是那些需要构建文档检索增强生成（RAG）系统、进行批量文本分析或希望让 AI 助手直接“阅读”本地文件的用户。虽然生成的内容也具备一定可读性，但其核心优势在于为机器",93400,"2026-04-06T19:52:38",[52,14],{"id":62,"github_repo":63,"name":64,"description_en":65,"description_zh":66,"ai_summary_zh":66,"readme_en":67,"readme_zh":68,"quickstart_zh":69,"use_case_zh":70,"hero_image_url":71,"owner_login":64,"owner_name":64,"owner_avatar_url":72,"owner_bio":73,"owner_company":74,"owner_location":74,"owner_email":74,"owner_twitter":74,"owner_website":74,"owner_url":75,"languages":74,"stars":76,"forks":77,"last_commit_at":78,"license":79,"difficulty_score":80,"env_os":81,"env_gpu":82,"env_ram":82,"env_deps":83,"category_tags":86,"github_topics":87,"view_count":32,"oss_zip_url":74,"oss_zip_packed_at":74,"status":17,"created_at":98,"updated_at":99,"faqs":100,"releases":101},6703,"EliteQuant\u002FEliteQuant","EliteQuant","A list of online resources for quantitative modeling, trading, portfolio management","EliteQuant 是一个专为量化建模、交易策略及投资组合管理打造的在线资源导航库。它并非单一软件，而是一份精心 curated 的清单，汇聚了从开源交易平台、回测系统、核心算法库到实时数据源等全方位的工具链接。\n\n在量化金融领域，开发者常面临工具分散、筛选成本高的问题。EliteQuant 通过整理如 Quantopian、vnpy、Backtrader 等知名项目，以及各类交易 API 和加密货币资源，帮助用户快速定位经过社区验证（通常拥有较高 GitHub 星标）的高质量开源方案，从而大幅降低技术选型的时间成本。\n\n这份资源列表特别适合量化研究员、金融工程师、算法交易开发者以及对金融科技感兴趣的学生使用。无论是需要构建高频交易系统，还是进行策略回测与市场分析，都能在此找到对应的 Python、C# 或 R 语言支持工具。其独特之处在于不仅涵盖通用框架，还细分了针对加密货币、特定券商接口及可视化图表的专业资源，为不同技术栈的用户提供了清晰的学习与实践路径，是进入量化交易领域的实用入门指南。","# EliteQuant\nA list of online resources for quantitative modeling, trading, portfolio management \n\nThere are lots of other valuable online resources. We are not trying to be exhaustive. Please feel free to send a pull request if you believe something is worth recommending. A general rule of thumb for open source projects is having already received 100 stars on github.\n\n* [Quantitative Trading Platform](#quantitative-trading-platform)\n* [Trading System](#trading-system)\n* [Quantitative Library](#quantitative-library)\n* [Quantitative Model](#quantitative-model)\n* [Trading API](#trading-api)\n* [Data Source](#data-source)\n* [Cryptocurrency](#cryptocurrency)\n* [Companies](#companies)\n* [Fintech](#fintech)\n* [Websites Forums Blogs](#websites-forums-blogs)\n\n- - -\n\n## Quantitative Trading Platform\n\n* [awesome-quant](https:\u002F\u002Fgithub.com\u002Fwilsonfreitas\u002Fawesome-quant) - Awesome quant is another curated list of quant resources\n\n* [Quantopian](https:\u002F\u002Fwww.quantopian.com\u002F) - First Python-based online quantitative trading platform; its core library [zipline](https:\u002F\u002Fgithub.com\u002Fquantopian\u002Fzipline) and its performance evaluation library [pyfolio](https:\u002F\u002Fgithub.com\u002Fquantopian\u002Fpyfolio); and [alphalens](https:\u002F\u002Fgithub.com\u002Fquantopian\u002Falphalens)\n\n* [QuantConnect](https:\u002F\u002Fwww.quantconnect.com\u002F) - C# based online quantitative trading platform; its core library [Lean](https:\u002F\u002Fgithub.com\u002FQuantConnect\u002FLean)\n\n* [Quantiacs](https:\u002F\u002Fwww.quantiacs.com\u002F) - The Marketplace For Algorithmic Trading Strategies; its [Matlab and Python toolbox](https:\u002F\u002Fgithub.com\u002FQuantiacs)\n\n* [Numerai](https:\u002F\u002Fnumer.ai\u002F) - crowd-sourced trading strategies; its [Python API](https:\u002F\u002Fgithub.com\u002Fuuazed\u002Fnumerapi\u002F)\n\n* [Collective2](https:\u002F\u002Ftrade.collective2.com\u002F) - The platform that allows investors subscribe to top-traders; its [algotrades system](https:\u002F\u002Fwww.algotrades.net\u002F)\n\n* [ZuluTrade](https:\u002F\u002Fzulutrade.com) - The platform that allows investors subscribe to top-traders\n\n* [Tradingview](https:\u002F\u002Fwww.tradingview.com\u002Fchart\u002F) - It provides free widgets used for example [Huobi](https:\u002F\u002Fwww.hbg.com\u002Fzh-cn\u002Fexchange\u002F?s=eos_usdt)\n\n* [Investing.com](https:\u002F\u002Fwww.investing.com\u002Findices\u002Fus-spx-500-futures-commentary) - Real time multi-assets and markets\n* [KloudTrader Narwhal](https:\u002F\u002Fkloudtrader.com\u002FNarwhal) - Trading algorithm [deployment platform](https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=4hfSJ769bDk) with flat-rate commission-free brokerage \n\n## Trading System\n\n* [MetaTrader 5](https:\u002F\u002Fwww.metatrader5.com\u002F) - Multi-Asset trading system\n\n* [TradeStation](https:\u002F\u002Fwww.tradestation.com\u002F) - Trading system\n\n* [SmartQuant(OpenQuant)](http:\u002F\u002Fwww.smartquant.com\u002F) - C# Trading system\n\n* [RightEdge](https:\u002F\u002Fwww.rightedgesystems.com\u002F) - Trading system\n\n* [AmiBroker](https:\u002F\u002Fwww.amibroker.com\u002F) - Trading system\n\n* [Algo Terminal](https:\u002F\u002Fwww.algoterminal.com\u002F) - C# Trading system\n\n* [NinjaTrader](https:\u002F\u002Fninjatrader.com\u002F) - Trading system\n\n* [QuantTools](https:\u002F\u002Fquanttools.bitbucket.io\u002F) - Enhanced Quantitative Trading Modelling in R\n\n* [vnpy](https:\u002F\u002Fgithub.com\u002Fvnpy\u002Fvnpy) - A popular and powerful trading platform\n\n* [pyalgotrade](https:\u002F\u002Fgithub.com\u002Fgbeced\u002Fpyalgotrade) - Python Algorithmic Trading Library\n\n* [finmarketpy](https:\u002F\u002Fgithub.com\u002Fcuemacro\u002Ffinmarketpy) - Python library for backtesting trading strategies\n\n* [IBridgePy](http:\u002F\u002Fwww.ibridgepy.com\u002F) - A Python system derived from zipline\n\n* [Backtrader](https:\u002F\u002Fwww.backtrader.com\u002F) - Blog, trading community, and [github](https:\u002F\u002Fgithub.com\u002Fbacktrader\u002Fbacktrader)\n\n* [IbPy](https:\u002F\u002Fgithub.com\u002Fblampe\u002FIbPy) - Interactive Brokers Python API\n\n* [PyLimitBook](https:\u002F\u002Fgithub.com\u002Fdanielktaylor\u002FPyLimitBook) - Python implementation of fast limit-order book\n\n* [qtpylib](https:\u002F\u002Fgithub.com\u002Franaroussi\u002Fqtpylib) - Pythonic Algorithmic Trading via IbPy API and its [Website](https:\u002F\u002Fqtpylib.io\u002F)\n\n* [Quantdom](https:\u002F\u002Fgithub.com\u002Fconstverum\u002FQuantdom) - Python-based framework for backtesting trading strategies & analyzing financial markets [GUI]\n\n* [ib_insync](https:\u002F\u002Fgithub.com\u002Ferdewit\u002Fib_insync) - Python sync\u002Fasync framework for Interactive Brokers API\n\n* [rqalpha](https:\u002F\u002Fgithub.com\u002Fricequant\u002Frqalpha) - A popular trading platform\n\n* [bt](https:\u002F\u002Fgithub.com\u002Fpmorissette\u002Fbt) - flexible backtesting for Python\n\n* [TradingGym](https:\u002F\u002Fgithub.com\u002FYvictor\u002FTradingGym) - Trading and Backtesting environment for training reinforcement learning agent or simple rule base algo.\n\n* [btgym](https:\u002F\u002Fgithub.com\u002FKismuz\u002Fbtgym) - Gym-compatible backtesting\n\n* [prophet](https:\u002F\u002Fgithub.com\u002FEmsu\u002Fprophet) - Python backtesting and trading platform\n\n* [OpenHFT](https:\u002F\u002Fgithub.com\u002FOpenHFT) - Java components for high-frequency trading\n\n* [libtrading](https:\u002F\u002Fgithub.com\u002Flibtrading\u002Flibtrading) - C API, low latency, fix support\n\n* [thOth](https:\u002F\u002Fgithub.com\u002Fvermosen\u002FthOth) - open-source high frequency trading library in C++ 11\n\n* [qt_tradingclient](https:\u002F\u002Fgithub.com\u002Fspinlockirqsave\u002Fqt_tradingclient_1) - multithreaded Qt C++ trading application, QuantLib-1.2.1, CUDA 5.0\n\n* [SubMicroTrading](https:\u002F\u002Fgithub.com\u002Fgsitgithub\u002FSubMicroTrading) - Java Ultra Low Latency Trading Framework\n\n* [WPF\u002FMVVM Real-Time Trading Application](https:\u002F\u002Fwww.codeproject.com\u002FArticles\u002F326641\u002FWPF-MVVM-Real-Time-Trading-Application) - Architechture\n\n* [TradeLink](https:\u002F\u002Fgithub.com\u002Fpracplayopen\u002Fcore)  - TradeLink, one of the earliest open source trading system\n\n* [Reactive Trader](https:\u002F\u002Fgithub.com\u002FAdaptiveConsulting) - using reactive Rx framework, includes [Reactive Trader](https:\u002F\u002Fgithub.com\u002FAdaptiveConsulting\u002FReactiveTrader) and [Reactive Trader Cloud](https:\u002F\u002Fgithub.com\u002FAdaptiveConsulting\u002FReactiveTraderCloud). The demo is [here](https:\u002F\u002Fweb-demo.adaptivecluster.com\u002F).\n\n* [QuantTrading](https:\u002F\u002Fgithub.com\u002Fletianzj\u002FQuantTrading) - Pure C# trading system\n\n* [StockTrading](https:\u002F\u002Fgithub.com\u002Fhoumie\u002FStockTrading) - C# system utilising WPF, WCF, PRISM, MVVM, Threading\n\n* [Quanter](https:\u002F\u002Fgithub.com\u002Fsuperquanter\u002Fquanter) - StockTrader\n\n* [StockSharp](https:\u002F\u002Fgithub.com\u002FStockSharp\u002FStockSharp) - C# trading system\n\n* [SharpQuant](https:\u002F\u002Fgithub.com\u002Fsmartquant\u002FSharpQuant.QuantStudio) - C# trading system\n\n* [QuantSys](https:\u002F\u002Fgithub.com\u002Fexl3\u002FQuantSys) - C# trading system\n\n* [StockTicker](https:\u002F\u002Fgithub.com\u002Fdanielmarbach\u002FStockTicker) - C# trading system\n\n* [gotrade](https:\u002F\u002Fgithub.com\u002Fcyanly\u002Fgotrade) - Electronic trading and order management system written in Golang\n\n* [gofinance](https:\u002F\u002Fgithub.com\u002Faktau\u002Fgofinance) - Financial information retrieval and munging in golang\n\n* [goib](https:\u002F\u002Fgithub.com\u002Fgofinance\u002Fib) - Pure Go interface to Interactive Brokers IB API \n\n* [Matlab Trading Toolbox](https:\u002F\u002Fwww.mathworks.com\u002Fproducts\u002Ftrading.html) - Official toolbox from Matlab; acommpanying [Introduction to Matlab Trading Toolbox](https:\u002F\u002Fwww.mathworks.com\u002Fmatlabcentral\u002Ffileexchange\u002F52588-automated-trading-system-development-with-matlab?focused=5253184&tab=example), and [webinar Automated Trading System Development with MATLAB](https:\u002F\u002Fwww.mathworks.com\u002Fvideos\u002Fautomated-trading-system-development-with-matlab-106851.html), and [webinar Automated Trading with MATLAB](https:\u002F\u002Fwww.mathworks.com\u002Fvideos\u002Fautomated-trading-with-matlab-81911.html), as well as [webinar A Real-Time Trading System in MATLAB](https:\u002F\u002Fwww.mathworks.com\u002Fvideos\u002Fa-real-time-trading-system-in-matlab-92900.html), [Automated Trading with Matlab](https:\u002F\u002Fwww.mathworks.com\u002Fvideos\u002Fautomated-trading-with-matlab-81911.html), [Commodities Trading with Matlab](https:\u002F\u002Fwww.mathworks.com\u002Fvideos\u002Fcommodities-trading-with-matlab-81986.html), [Cointegration and Pairs Trading with Econometrics Toolbox](https:\u002F\u002Fwww.mathworks.com\u002Fvideos\u002Fcointegration-and-pairs-trading-with-econometrics-toolbox-81799.html)\n\n* [Matlab risk management Toolbox](https:\u002F\u002Fwww.mathworks.com\u002Fproducts\u002Frisk-management.html) - Official toolbox from Matlab\n\n* [Matlab Walk Forward Analysis Toolbox](https:\u002F\u002Fwfatoolbox.com\u002F) - toolbox for walk-forward analysis\n\n* [IB4m](https:\u002F\u002Fgithub.com\u002Fsoftwarespartan\u002FIB4m) - matlab interface to interactive broker\n\n* [IB-Matlab](https:\u002F\u002Fundocumentedmatlab.com\u002Fib-matlab\u002F) - introduction to another matlab interface to interactive broker and [demo video](https:\u002F\u002Fundocumentedmatlab.com\u002Fib-matlab\u002Freal-time-trading-system-demo)\n\n* [openAlgo Matlab](https:\u002F\u002Fgithub.com\u002Fmtompkins\u002FopenAlgo\u002Ftree\u002Fmaster\u002FMatlab) - openAlgo's Matlab library\n\n* [MatTest](https:\u002F\u002Fgithub.com\u002Fedisonhyc\u002FMatTest) - Matlab backtest system\n\n## Quantitative Library\n\n* [Quantlib](https:\u002F\u002Fwww.quantlib.org\u002F) - famous C++ library for quantitative finance; tranlated into other langugages via Swig\n\n* [TA-Lib](https:\u002F\u002Fgithub.com\u002Fmrjbq7\u002Fta-lib) - Python wrapper for TA-Lib\n\n* [DX Analytics](https:\u002F\u002Fdx-analytics.com\u002F) - Python-based financial analytics library\n\n* [FinMath](http:\u002F\u002Ffinmath.net\u002F) - Java analytics library\n\n* [OpenGamma](https:\u002F\u002Fopengamma.com\u002F) - Java analytics library named STRATA\n\n* [Quantiacs](https:\u002F\u002Fgithub.com\u002FQuantiacs) - [Matlab](https:\u002F\u002Fgithub.com\u002FQuantiacs\u002Fquantiacs-matlab) toolbox\n\n* [pyflux](https:\u002F\u002Fgithub.com\u002FRJT1990\u002Fpyflux) - Open source time series library for Python\n\n* [arch](https:\u002F\u002Fgithub.com\u002Fbashtage\u002Farch) - ARCH models in Python\n\n* [flint](https:\u002F\u002Fgithub.com\u002Ftwosigma\u002Fflint) - A Time Series Library for Apache Spark\n\n* [Statsmodels](https:\u002F\u002Fwww.statsmodels.org) - Statsmodels’s Documentation\n\n\n## Quantitative Model\n\n* [awesome-deep-trading](https:\u002F\u002Fgithub.com\u002Fcbailes\u002Fawesome-deep-trading) - A list of machine learning resources for trading\n\n* [Awesome-Quant-Machine-Learning-Trading](https:\u002F\u002Fgithub.com\u002Fgrananqvist\u002FAwesome-Quant-Machine-Learning-Trading) - Another list of machine learning resources for trading\n\n* [awesome-ai-in-finance](https:\u002F\u002Fgithub.com\u002Fgeorgezouq\u002Fawesome-ai-in-finance) - A collection of AI resources in finance\n\n* [deepstock](https:\u002F\u002Fgithub.com\u002Fkeon\u002Fdeepstock) - Technical experimentations to beat the stock market using deep learning\n\n* [qtrader](https:\u002F\u002Fgithub.com\u002Ffilangel\u002Fqtrader) - Reinforcement Learning for Portfolio Management\n\n* [stockPredictor](https:\u002F\u002Fgithub.com\u002FNazanin1369\u002FstockPredictor) - Predict stock movement with Machine Learning and Deep Learning algorithms\n\n* [stock_market_reinforcement_learning](https:\u002F\u002Fgithub.com\u002Fkh-kim\u002Fstock_market_reinforcement_learning) - Stock market environment using OpenGym with Deep Q-learning and Policy Gradient\n\n* [deep-algotrading](https:\u002F\u002Fgithub.com\u002FLiamConnell\u002Fdeep-algotrading) - deep learning techniques from regression to LSTM using financial data\n\n* [deep_trader](https:\u002F\u002Fgithub.com\u002Fdeependersingla\u002Fdeep_trader) - Use reinforcement learning on stock market and agent tries to learn trading. \n\n* [Deep-Trading](https:\u002F\u002Fgithub.com\u002FRachnog\u002FDeep-Trading) - Algorithmic trading with deep learning experiments\n\n* [Deep-Trading](https:\u002F\u002Fgithub.com\u002Fha2emnomer\u002FDeep-Trading) - Algorithmic Trading using RNN\n\n* [100 Day Machine Learning](https:\u002F\u002Fgithub.com\u002FAvik-Jain\u002F100-Days-Of-ML-Code) - Machine Learning tutorial with code\n\n* [Multidimensional-LSTM-BitCoin-Time-Series](https:\u002F\u002Fgithub.com\u002Fjaungiers\u002FMultidimensional-LSTM-BitCoin-Time-Series) - Using multidimensional LSTM neural networks to create a forecast for Bitcoin price\n\n* [QLearning_Trading](https:\u002F\u002Fgithub.com\u002Fucaiado\u002FQLearning_Trading) - Learning to trade under the reinforcement learning framework\n\n* [bulbea](https:\u002F\u002Fgithub.com\u002Fachillesrasquinha\u002Fbulbea) - Deep Learning based Python Library for Stock Market Prediction and Modelling \n\n* [PGPortfolio](https:\u002F\u002Fgithub.com\u002FZhengyaoJiang\u002FPGPortfolio) - source code of \"A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem\"\n\n* [gym-trading](https:\u002F\u002Fgithub.com\u002Fhackthemarket\u002Fgym-trading) - Environment for reinforcement-learning algorithmic trading models\n\n* [Thesis](https:\u002F\u002Fgithub.com\u002Fpnecchi\u002FThesis) - Reinforcement Learning for Automated Trading\n\n* [DQN](https:\u002F\u002Fgithub.com\u002Fjjakimoto\u002FDQN) - Reinforcement Learning for finance\n\n* [Deep-Trading-Agent](https:\u002F\u002Fgithub.com\u002Fsamre12\u002Fdeep-trading-agent) - Deep Reinforcement Learning based Trading Agent for Bitcoin\n\n* [deep_portfolio](https:\u002F\u002Fgithub.com\u002Fdeependersingla\u002Fdeep_portfolio) - Use Reinforcement Learning and Supervised learning to Optimize portfolio allocation.\n\n* [Deep-Reinforcement-Learning-in-Stock-Trading](https:\u002F\u002Fgithub.com\u002Fshenyichen105\u002FDeep-Reinforcement-Learning-in-Stock-Trading) - Using deep actor-critic model to learn best strategies in pair trading\n\n* [Stock-Price-Prediction-LSTM](https:\u002F\u002Fgithub.com\u002FNourozR\u002FStock-Price-Prediction-LSTM) - OHLC Average Prediction of Apple Inc. Using LSTM Recurrent Neural Network\n\n* [DeepDow](https:\u002F\u002Fgithub.com\u002Fjankrepl\u002Fdeepdow) - Portfolio optimization with deep learning\n\n* [Personae](https:\u002F\u002Fgithub.com\u002FCeruleanacg\u002FPersonae) - Quantitative trading with deep learning\n\n* [tensortrade](https:\u002F\u002Fgithub.com\u002Ftensortrade-org\u002Ftensortrade) - Reinforcement learning and trading\n\n* [stockpredictionai](https:\u002F\u002Fgithub.com\u002Fborisbanushev\u002Fstockpredictionai) - AI models such as GAN and PPO applied to stock markets\n\n* [machine-learning-for-trading](https:\u002F\u002Fgithub.com\u002Fstefan-jansen\u002Fmachine-learning-for-trading) - Machine learning for algorithmic trading book\n\n* [algorithmic-trading-with-python](https:\u002F\u002Fgithub.com\u002Fchrisconlan\u002Falgorithmic-trading-with-python) - Algorithmic Trading with Python book (2020)\n\n* [machine-learning-asset-management](https:\u002F\u002Fgithub.com\u002Ffirmai\u002Fmachine-learning-asset-management) - Machine Learning in Asset Management by [firmai.org](https:\u002F\u002Fwww.firmai.org\u002F)\n\n## Trading API\n\n* [Interactive Brokers](https:\u002F\u002Fwww.interactivebrokers.com) - popular among retail trader\n\n* [Bloomberg API](https:\u002F\u002Fwww.bloomberg.com\u002Fprofessional\u002Fsupport\u002Fapi-library\u002F) - from Bloomberg\n\n## Data Source\n\n* [Quandl](https:\u002F\u002Fwww.quandl.com\u002F) - free and premium data sources\n\n* [iex](https:\u002F\u002Fiextrading.com\u002Ftrading\u002Fmarket-data\u002F) - free market data\n\n* [one tick](https:\u002F\u002Fwww.onetick.com\u002F) - historical tick data\n\n* [iqfeed](https:\u002F\u002Fwww.iqfeed.net\u002F) - real time data feed\n\n* [quantquote](https:\u002F\u002Fquantquote.com\u002F) - tick and live data\n\n* [algoseek](https:\u002F\u002Fwww.algoseek.com\u002F) - historical intraday\n\n* [EOD data](https:\u002F\u002Feoddata.com\u002F) - historical data\n\n* [EOD historical data](https:\u002F\u002Feodhistoricaldata.com\u002F) - historical data\n\n* [intrinio](https:\u002F\u002Fintrinio.com\u002F) - financial data\n\n* [arctic](https:\u002F\u002Fgithub.com\u002Fmanahl\u002Farctic) - High performance datastore from [Man AHL](https:\u002F\u002Fwww.ahl.com\u002F) for time series and tick data \n\n* [SEC EDGAR API](https:\u002F\u002Fsec-api.io\u002F) -- Query company filings on SEC EDGAR\n\n## Cryptocurrency\n\n* [Blockchain-stuff](https:\u002F\u002Fgithub.com\u002FXel\u002FBlockchain-stuff) - Blockchain and Crytocurrency Resources\n\n* [cryptrader](https:\u002F\u002Fcryptotrader.org\u002F) - Node.js Bitcoin bot for MtGox\u002FBitstamp\u002FBTC-E\u002FCEX.IO; [cryptrade](https:\u002F\u002Fgithub.com\u002Fdonfanning\u002Fcryptrade) \n\n* [BitcoinExchangeFH](https:\u002F\u002Fgithub.com\u002FBitcoinExchangeFH\u002FBitcoinExchangeFH) - Cryptocurrency exchange market data feed handler \n\n* [hummingbot](http:\u002F\u002Fhummingbot.io) - free [open source](https:\u002F\u002Fgithub.com\u002FCoinAlpha\u002Fhummingbot\u002F) crypto trading bot that supports both DEXes and CEXes\n\n* [blackbird](https:\u002F\u002Fgithub.com\u002Fbutor\u002Fblackbird) - C++ trading system that does automatic long\u002Fshort arbitrage between Bitcoin exchanges\n\n* [Peatio](https:\u002F\u002Fwww.peatio.tech) - An open-source crypto currency exchange on [github](https:\u002F\u002Fgithub.com\u002Fpeatio\u002Fpeatio)\n\n* [Qt Bitcoin Trader](https:\u002F\u002Fgithub.com\u002FJulyIGHOR\u002FQtBitcoinTrader) - Qt C++ Bitcoin trading\n\n* [ccxt](https:\u002F\u002Fgithub.com\u002Fccxt\u002Fccxt) - A JavaScript \u002F Python \u002F PHP cryptocurrency trading library with support for more than 130 bitcoin\u002Faltcoin exchanges\n\n* [r2](https:\u002F\u002Fgithub.com\u002Fbitrinjani\u002Fr2) - Qan automatic arbitrage trading system powered by Node.js + TypeScript\n\n* [bcoin](https:\u002F\u002Fgithub.com\u002Fbcoin-org\u002Fbcoin) - Javascript bitcoin library for node.js and [browsers](https:\u002F\u002Fbcoin.io\u002F)\n\n* [XChange](https:\u002F\u002Fgithub.com\u002Fknowm\u002FXChange) - Java library providing a streamlined API for interacting with 60+ Bitcoin and Altcoin exchanges\n\n* [Krypto-trading-bot](https:\u002F\u002Fgithub.com\u002Fctubio\u002FKrypto-trading-bot) - Self-hosted crypto trading bot (automated high frequency market making) in node.js, angular, typescript and c++\n\n* [freqtrade](https:\u002F\u002Fgithub.com\u002Ffreqtrade\u002Ffreqtrade) - Simple High Frequency Trading Bot for crypto currencies\n\n* [Gekko](https:\u002F\u002Fgithub.com\u002Faskmike\u002Fgekko) - A bitcoin trading bot written in node\n\n* [viabtc_exchange_server](https:\u002F\u002Fgithub.com\u002Fviabtc\u002Fviabtc_exchange_server) - A trading engine with high-speed performance and real-time notification\n\n* [catalyst](https:\u002F\u002Fgithub.com\u002Fenigmampc\u002Fcatalyst) - An Algorithmic Trading Library for Crypto-Assets in Python [Enigma](https:\u002F\u002Fenigma.co\u002F)\n\n* [buttercoin](https:\u002F\u002Fgithub.com\u002Fbuttercoin\u002Fbuttercoin) - Opensource Bitcoin Exchange Software\n\n* [zenbot](https:\u002F\u002Fgithub.com\u002FDeviaVir\u002Fzenbot) - A command-line cryptocurrency trading bot using Node.js and MongoDB.\n\n* [tribeca](https:\u002F\u002Fgithub.com\u002Fmichaelgrosner\u002Ftribeca) - A high frequency, market making cryptocurrency trading platform in node.js\n\n* [rbtc_arbitrage](https:\u002F\u002Fgithub.com\u002Fhstove\u002Frbtc_arbitrage) - A gem for automating arbitrage between Bitcoin exchanges.\n\n* [automated-trading](https:\u002F\u002Fgithub.com\u002Fbevry-trading\u002Fautomated-trading) - Automated Trading: Trading View Strategies => Bitfinex, itBit, DriveWealth\n\n* [gocryptotrader](https:\u002F\u002Fgithub.com\u002Fthrasher-\u002Fgocryptotrader) - A cryptocurrency trading bot and framework supporting multiple exchanges written in Golang\n\n* [btcrobot](https:\u002F\u002Fgithub.com\u002Fphilsong\u002Fbtcrobot) - Golang bitcoin trading bot\n\n* [bitex](https:\u002F\u002Fgithub.com\u002Fblinktrade\u002Fbitex) - Open Source Bitcoin Exchange; and its [front-end](https:\u002F\u002Fgithub.com\u002Fblinktrade\u002Ffrontend)\n\n* [cryptoworks](https:\u002F\u002Fcryptoworks.co\u002F) - A cryptocurrency arbitrage opportunity calculator. Over 800 currencies and 50 markets; [cryptocurrency-arbitrage](https:\u002F\u002Fgithub.com\u002Fmanu354\u002Fcryptocurrency-arbitrage)\n\n* [crypto-exchange](https:\u002F\u002Fgithub.com\u002Fpassabilities\u002Fcrypto-exchange) - list of crypto exchanges to interact with their API's in a uniform fashion\n\n* [bitcoin-abe](https:\u002F\u002Fgithub.com\u002Fbitcoin-abe\u002Fbitcoin-abe) - block browser for Bitcoin and similar currencies\n\n* [MultiPoolMiner](https:\u002F\u002Fgithub.com\u002FMultiPoolMiner\u002FMultiPoolMiner) - Monitors crypto mining pools in real-time in order to find the most profitable for your machine. Controls any miner that is available via command line\n\n* [tai](https:\u002F\u002Fgithub.com\u002Ffremantle-capital\u002Ftai) - An open source, composable, real time, market data and trade execution toolkit. Written in Elixir\n\n* [crypto-signal](https:\u002F\u002Fgithub.com\u002FCryptoSignal\u002Fcrypto-signal) - Technical signals for multiple exchanges\n\n## Companies\n\nNot trying to be exhaustive\n\n* [Sell Side](https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FList_of_investment_banks)\n\n* [FIA PTG](http:\u002F\u002Fwww.marketswiki.com\u002Fwiki\u002FPrincipal_Traders_Group) and [FIA Europe](https:\u002F\u002Fwww.fia.org\u002Fepta-membership)\n\n* [Allston Trading](http:\u002F\u002Fwww.marketswiki.com\u002Fwiki\u002FAllston_Trading,_LLC)\n\n* [CTC](http:\u002F\u002Fwww.marketswiki.com\u002Fwiki\u002FChicago_Trading_Company)\n\n* [Citadel](https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FCitadel_LLC)\n\n* [D.E. Shaw](https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FD._E._Shaw_%26_Co.)\n\n* [DRW](http:\u002F\u002Fwww.marketswiki.com\u002Fwiki\u002FDRW)\n\n* [Flow Traders](https:\u002F\u002Fwww.flowtraders.com\u002F)\n\n* [GTS](http:\u002F\u002Fwww.gtsx.com\u002F)\n\n* [HRT](https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FHudson_River_Trading)\n\n* [IMC](https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FIMC_Financial_Markets)\n\n* [Infinium](http:\u002F\u002Fwww.marketswiki.com\u002Fwiki\u002FInfinium_Capital_Management,_LLC)\n\n* [Jane Street](https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FJane_Street_Capital)\n\n* [Jump Trading](http:\u002F\u002Fwww.marketswiki.com\u002Fwiki\u002FJump_Trading_LLC)\n\n* [Millennium](https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FMillennium_Management,_LLC)\n\n* [Optiver](https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FOptiver)\n\n* [Quantlab Financial](https:\u002F\u002Fwww.quantlab.com\u002F)\n\n* [Renaissance](https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FRenaissance_Technologies)\n\n* [Bridgewater Associates](https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FBridgewater_Associates)\n\n* [Man Group](https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FMan_Group), [AHL](https:\u002F\u002Fwww.ahl.com\u002F)\n\n* [SIG](https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FSusquehanna_International_Group)\n\n* [Tower Research](https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FTower_Research)\n\n* [Tradebot Systems](https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FTradebot)\n\n* [Two Sigma](https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FTwo_Sigma)\n\n* [Virtu Financial](https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FVirtu_Financial)\n\n* [XR Trading](http:\u002F\u002Fwww.xrtrading.com\u002F)\n\n* [XTX Markets](https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FXTX_Markets)\n\nCommodity Focused\n\n* [Cargill](https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FCargill)\n\n* [Glencore](https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FGlencore)\n\n* [Mercuria](https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FMercuria_Energy_Group)\n\n* [Trafigura](https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FTrafigura)\n\n* [Vigor](https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FVitol)\n\n## Fintech\n\n* [Alpaca](https:\u002F\u002Fwww.alpaca.ai\u002F)\n\n* [Knesho](https:\u002F\u002Fwww.kensho.com\u002F)\n\n* [Neotic](https:\u002F\u002Fneotic.ai\u002F)\n\n* [Numerai](https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FNumerai)\n\n* [Symphony](https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FSymphony_Communication)\n\n## Websites Forums Blogs\n\n* [Top Geeky Quant Blogs](https:\u002F\u002Falphaarchitect.com\u002F2014\u002F10\u002F13\u002Ftop-geeky-quant-blogs\u002F#.VECOwfldV8E) - A quant blogs check out list\n\n* [Quantocracy](https:\u002F\u002Fquantocracy.com\u002F) - Aggregation of news on quants\n\n* [seekingalpha](https:\u002F\u002Fseekingalpha.com\u002F) - Seeking Alpha community\n\n* [Quantivity](https:\u002F\u002Fquantivity.wordpress.com\u002F) - quantitative and algorithmic trading\n\n* [Wilmott](https:\u002F\u002Fwww.wilmott.com\u002F) - quantitative finance community forum\n\n* [Elitetrader](https:\u002F\u002Fwww.elitetrader.com\u002F) - trading forum\n\n* [nuclearphynance](https:\u002F\u002Fwww.nuclearphynance.com\u002F) - quantitative finance forum\n\n* [Investopedia](https:\u002F\u002Fwww.investopedia.com\u002F) - The Encyclopedia of investments\n\n* [Quantpedia](https:\u002F\u002Fwww.quantpedia.com\u002F) - The Encyclopedia of Quantitative Trading Strategies\n\n* [EpChan](https:\u002F\u002Fepchan.blogspot.com\u002F) - Dr. Ernie Chan's blog\n\n* [Quantinsti](https:\u002F\u002Fquantra.quantinsti.com\u002F) - Quant Institute\n\n* [QuantStart](https:\u002F\u002Fwww.quantstart.com\u002F) - Michael Halls-Moore's quantstart, quant trading 101; its Python backtest platform [qstrader](https:\u002F\u002Fgithub.com\u002Fmhallsmoore\u002Fqstrader) and [qsforex](https:\u002F\u002Fgithub.com\u002Fmhallsmoore\u002Fqsforex)\n\n* [Algotrading 101](https:\u002F\u002Falgotrading101.com\u002F) - Algo trading 101\n\n* [Systematic Investor](https:\u002F\u002Fsystematicinvestor.github.io\u002F)\u002F[old version](https:\u002F\u002Fsystematicinvestor.wordpress.com\u002F) - [Michael Kapler](https:\u002F\u002Fwww.linkedin.com\u002Fin\u002Fmichael-kapler-mmf-cfa-92a1a02\u002F?ppe=1)'s blog, one of the best R quantitative blog; [Systematic Investor Toolkit](https:\u002F\u002Fgithub.com\u002Fsystematicinvestor\u002FSIT)\n\n* [R-Finance](https:\u002F\u002Fgithub.com\u002FR-Finance) - R-Finance repository. It has backtest [quantstrat](https:\u002F\u002Fgithub.com\u002FR-Finance\u002Fquantstrat), [trade blotter](https:\u002F\u002Fgithub.com\u002FR-Finance\u002Fblotter), famous [performance analytics](https:\u002F\u002Fgithub.com\u002FR-Finance\u002FPerformanceAnalytics) package, and package [portfolio analytics](https:\u002F\u002Fgithub.com\u002FR-Finance\u002FPortfolioAnalytics), [portfolio attribution](https:\u002F\u002Fgithub.com\u002FR-Finance\u002FPortfolioAttribution).\n\n* [quantmod](https:\u002F\u002Fwww.quantmod.com\u002F) - R modelling and trading framework\n\n* [r programming](http:\u002F\u002Fwww.r-programming.org\u002Fpapers) - Guy Yollin's R backtesting\n\n* [Seer Trading](http:\u002F\u002Fwww.seertrading.com\u002F) - R Backtest and live trading\n\n* [Trading with Python](https:\u002F\u002Ftradingwithpython.blogspot.com\u002F)\n\n* [python programming finance](https:\u002F\u002Fpythonprogramming.net\u002Ffinance-tutorials\u002F) - python finance tutorial and quantopian toturial\n\n* [python for finance](https:\u002F\u002Fwww.pythonforfinance.net\u002F) - python finance\n\n* [Quant Econ](https:\u002F\u002Fquantecon.org\u002F) - open source python and julia codes for economic modeling; and lectures\n\n* [JuliaQuant](https:\u002F\u002Fgithub.com\u002FJuliaQuant) - Quantitative Finance in Julia\n\n* [Portfolio Effect](https:\u002F\u002Fwww.portfolioeffect.com\u002F) - real time portfolio and risk management\n\n* [quant365](http:\u002F\u002Fwww.quant365.com\u002F) - Henry Moo's blog and trading system; including Sentosa, [pysentosa binding](https:\u002F\u002Fgithub.com\u002Fhenrywoo\u002Fpysentosa), rsentosa binding and [qblog](https:\u002F\u002Fgithub.com\u002Fhenrywoo\u002Fqblog).\n\n* [hpc quantlib](https:\u002F\u002Fhpcquantlib.wordpress.com\u002F) - HPC + QuantLib\n\n* [Quant Corner](https:\u002F\u002Fquantcorner.wordpress.com\u002F)\n\n* [quantstrat trader](https:\u002F\u002Fquantstrattrader.wordpress.com\u002F) - Backtesting trading ideas with R [QuantStrat](https:\u002F\u002Fgithub.com\u002FR-Finance\u002Fquantstrat) package\n\n* [Backtesting Strategies](https:\u002F\u002Ftimtrice.github.io\u002Fbacktesting-strategies\u002F) - Backtesting in R; codes at [Github](https:\u002F\u002Fgithub.com\u002Ftimtrice\u002Fbacktesting-strategies)\n\n* [The Quant MBA](https:\u002F\u002Fthequantmba.wordpress.com\u002F) - good quant blog\n\n* [Foss Trading](http:\u002F\u002Fblog.fosstrading.com\u002F) - Algorithmic trading with free open source software\n\n* [Gekko Quant](http:\u002F\u002Fgekkoquant.com\u002F) - Quantitative Trading\n\n* [Investment Idiocy](https:\u002F\u002Fqoppac.blogspot.com\u002F) - Systematic Trading, Quantitative Finance, Investing, Financial Activism, Economic decision making by Robert Carver; [his book](https:\u002F\u002Fwww.amazon.com\u002FSystematic-Trading-designing-trading-investing\u002Fdp\u002F0857194453) and [his Python library](https:\u002F\u002Fgithub.com\u002Frobcarver17\u002Fpysystemtrade)\n\n* [Quantifiable Edges](https:\u002F\u002Fquantifiableedges.com\u002Fblog\u002F)\u002F[old version](https:\u002F\u002Fquantifiableedges.blogspot.com\u002F) - Assessing market action with indicators and history\n\n* [My Simple Quant](http:\u002F\u002Fmysimplequant.blogspot.com\u002F) - Market analysis utilizing historical, back-tessted data\n\n* [Vix and more](https:\u002F\u002Fvixandmore.blogspot.com\u002F) - discussions on Vix\n\n* [Timely Portfolio](https:\u002F\u002Ftimelyportfolio.blogspot.com\u002F) - Strategies and tests in R\n\n* [Quantitative Research and Trading](https:\u002F\u002Fjonathankinlay.com\u002F)\n\n* [Qusma](https:\u002F\u002Fqusma.com\u002F) - Quantitative Systematic Market Analysis\n\n* [return and risk](http:\u002F\u002Fwww.returnandrisk.com\u002F) - Quantitative finance, analysis, and applications\n\n* [Physics of Finance](https:\u002F\u002Fphysicsoffinance.blogspot.com\u002F) - Inspiration from physics for thinking about economics, finance and social systems\n\n* [Quantum Financier](https:\u002F\u002Fquantumfinancier.wordpress.com\u002F) - algorithmic trading\n\n* [Trading the Odds](http:\u002F\u002Fwww.tradingtheodds.com\u002F) -- market timing & quantitative analysis\n\n* [CSSA](https:\u002F\u002Fcssanalytics.wordpress.com\u002F) - new concepts in quantitative research\n\n* [The Practical Quant](https:\u002F\u002Fpracticalquant.blogspot.com\u002F)\n\n* [Tr8dr](https:\u002F\u002Ftr8dr.github.io\u002F) - strategies, statistics, computer science, numerical techniques\n\n* [Deniz's Note](https:\u002F\u002Fdenizstij.blogspot.com\u002F) - blog of a quant Deniz Turan\n\n* [Quant at risk](http:\u002F\u002Fwww.quantatrisk.com\u002F) - quantitative analysis and risk management\n\n* [Quant Blog](https:\u002F\u002Fletianzj.github.io\u002F) - Quantitative trading, portfolio management, and machine learning, with [source codes on Github](https:\u002F\u002Fgithub.com\u002Fletianzj\u002FQuantResearch)\n\n* [The R Trader](https:\u002F\u002Fwww.thertrader.com\u002F) - Using R in quant finance\n\n* [rbresearch](https:\u002F\u002Frbresearch.wordpress.com\u002F) - Using R for trading strategy ideas in FX and equity markets\n\n* [NaN Quantivity](https:\u002F\u002Fquantlife.wordpress.com\u002F) - quant trading, statistical learning, coding and brainstorming\n\n* [Factor Investing](https:\u002F\u002Ffactorinvestingtutorial.wordpress.com\u002F) - blog on wordpress\n\n* [Meb Faber Research](https:\u002F\u002Fmebfaber.com\u002F)\n\n* [Big Mike Trading](https:\u002F\u002Fwww.youtube.com\u002Fuser\u002FBigMikeTrading\u002Fvideos) - Youtube chanel in quant trading\n\n* [Mechanical Markets](https:\u002F\u002Fmechanicalmarkets.wordpress.com\u002F)\n\n* [Humble Student of the Markets](https:\u002F\u002Fhumblestudentofthemarkets.blogspot.com\u002F)\n\n* [Predict Stock Prices Using RNN](https:\u002F\u002Flilianweng.github.io\u002Flil-log\u002F2017\u002F07\u002F08\u002Fpredict-stock-prices-using-RNN-part-1.html)\n\n* [BlackArbs](http:\u002F\u002Fwww.blackarbs.com\u002Fblog) - blog and [machine learning notebooks on Github](https:\u002F\u002Fgithub.com\u002FBlackArbsCEO\u002FAdv_Fin_ML_Exercises)\n","# EliteQuant\n量化建模、交易和投资组合管理的在线资源列表\n\n还有许多其他有价值的在线资源。我们并不追求面面俱到。如果您认为有值得推荐的内容，请随时提交拉取请求。对于开源项目，一个通用的经验法则是已经在 GitHub 上获得了 100 颗星。\n\n* [量化交易平台](#quantitative-trading-platform)\n* [交易系统](#trading-system)\n* [量化库](#quantitative-library)\n* [量化模型](#quantitative-model)\n* [交易 API](#trading-api)\n* [数据源](#data-source)\n* [加密货币](#cryptocurrency)\n* [公司](#companies)\n* [金融科技](#fintech)\n* [网站、论坛、博客](#websites-forums-blogs)\n\n- - -\n\n## 量化交易平台\n\n* [awesome-quant](https:\u002F\u002Fgithub.com\u002Fwilsonfreitas\u002Fawesome-quant) - Awesome quant 是另一个精选的量化资源列表\n\n* [Quantopian](https:\u002F\u002Fwww.quantopian.com\u002F) - 第一个基于 Python 的在线量化交易平台；其核心库 [zipline](https:\u002F\u002Fgithub.com\u002Fquantopian\u002Fzipline) 和绩效评估库 [pyfolio](https:\u002F\u002Fgithub.com\u002Fquantopian\u002Fpyfolio)；以及 [alphalens](https:\u002F\u002Fgithub.com\u002Fquantopian\u002Falphalens)\n\n* [QuantConnect](https:\u002F\u002Fwww.quantconnect.com\u002F) - 基于 C# 的在线量化交易平台；其核心库 [Lean](https:\u002F\u002Fgithub.com\u002FQuantConnect\u002FLean)\n\n* [Quantiacs](https:\u002F\u002Fwww.quantiacs.com\u002F) - 算法交易策略市场；其 [Matlab 和 Python 工具箱](https:\u002F\u002Fgithub.com\u002FQuantiacs)\n\n* [Numerai](https:\u002F\u002Fnumer.ai\u002F) - 大众外包的交易策略；其 [Python API](https:\u002F\u002Fgithub.com\u002Fuuazed\u002Fnumerapi\u002F)\n\n* [Collective2](https:\u002F\u002Ftrade.collective2.com\u002F) - 允许投资者订阅顶级交易员的平台；其 [algotrades 系统](https:\u002F\u002Fwww.algotrades.net\u002F)\n\n* [ZuluTrade](https:\u002F\u002Fzulutrade.com) - 允许投资者订阅顶级交易员的平台\n\n* [Tradingview](https:\u002F\u002Fwww.tradingview.com\u002Fchart\u002F) - 提供免费的小部件，例如用于 [火币](https:\u002F\u002Fwww.hbg.com\u002Fzh-cn\u002Fexchange\u002F?s=eos_usdt)\n\n* [Investing.com](https:\u002F\u002Fwww.investing.com\u002Findices\u002Fus-spx-500-futures-commentary) - 实时多资产和多市场信息\n* [KloudTrader Narwhal](https:\u002F\u002Fkloudtrader.com\u002FNarwhal) - 交易算法 [部署平台](https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=4hfSJ769bDk)，提供统一费率的免佣金经纪服务\n\n## 交易系统\n\n* [MetaTrader 5](https:\u002F\u002Fwww.metatrader5.com\u002F) - 多资产交易系统\n\n* [TradeStation](https:\u002F\u002Fwww.tradestation.com\u002F) - 交易系统\n\n* [SmartQuant(OpenQuant)](http:\u002F\u002Fwww.smartquant.com\u002F) - C# 交易系统\n\n* [RightEdge](https:\u002F\u002Fwww.rightedgesystems.com\u002F) - 交易系统\n\n* [AmiBroker](https:\u002F\u002Fwww.amibroker.com\u002F) - 交易系统\n\n* [Algo Terminal](https:\u002F\u002Fwww.algoterminal.com\u002F) - C# 交易系统\n\n* [NinjaTrader](https:\u002F\u002Fninjatrader.com\u002F) - 交易系统\n\n* [QuantTools](https:\u002F\u002Fquanttools.bitbucket.io\u002F) - R语言中的增强型量化交易建模\n\n* [vnpy](https:\u002F\u002Fgithub.com\u002Fvnpy\u002Fvnpy) - 一款流行且功能强大的交易平台\n\n* [pyalgotrade](https:\u002F\u002Fgithub.com\u002Fgbeced\u002Fpyalgotrade) - Python算法交易库\n\n* [finmarketpy](https:\u002F\u002Fgithub.com\u002Fcuemacro\u002Ffinmarketpy) - 用于回测交易策略的Python库\n\n* [IBridgePy](http:\u002F\u002Fwww.ibridgepy.com\u002F) - 基于zipline的Python系统\n\n* [Backtrader](https:\u002F\u002Fwww.backtrader.com\u002F) - 博客、交易社区及[github](https:\u002F\u002Fgithub.com\u002Fbacktrader\u002Fbacktrader)\n\n* [IbPy](https:\u002F\u002Fgithub.com\u002Fblampe\u002FIbPy) - 互动经纪商Python API\n\n* [PyLimitBook](https:\u002F\u002Fgithub.com\u002Fdanielktaylor\u002FPyLimitBook) - 快速限价订单簿的Python实现\n\n* [qtpylib](https:\u002F\u002Fgithub.com\u002Franaroussi\u002Fqtpylib) - 通过IbPy API进行Python式算法交易，其[官网](https:\u002F\u002Fqtpylib.io\u002F)\n\n* [Quantdom](https:\u002F\u002Fgithub.com\u002Fconstverum\u002FQuantdom) - 基于Python的交易策略回测与金融市场分析框架[GUI]\n\n* [ib_insync](https:\u002F\u002Fgithub.com\u002Ferdewit\u002Fib_insync) - 用于互动经纪商API的Python同步\u002F异步框架\n\n* [rqalpha](https:\u002F\u002Fgithub.com\u002Fricequant\u002Frqalpha) - 一款流行的交易平台\n\n* [bt](https:\u002F\u002Fgithub.com\u002Fpmorissette\u002Fbt) - 灵活的Python回测工具\n\n* [TradingGym](https:\u002F\u002Fgithub.com\u002FYvictor\u002FTradingGym) - 用于训练强化学习智能体或简单规则算法的交易与回测环境。\n\n* [btgym](https:\u002F\u002Fgithub.com\u002FKismuz\u002Fbtgym) - 兼容Gym的回测工具\n\n* [prophet](https:\u002F\u002Fgithub.com\u002FEmsu\u002Fprophet) - Python回测与交易平台\n\n* [OpenHFT](https:\u002F\u002Fgithub.com\u002FOpenHFT) - 高频交易用Java组件\n\n* [libtrading](https:\u002F\u002Fgithub.com\u002Flibtrading\u002Flibtrading) - C API，低延迟，支持FIX协议\n\n* [thOth](https:\u002F\u002Fgithub.com\u002Fvermosen\u002FthOth) - 开源C++11高频交易库\n\n* [qt_tradingclient](https:\u002F\u002Fgithub.com\u002Fspinlockirqsave\u002Fqt_tradingclient_1) - 多线程Qt C++交易应用，QuantLib-1.2.1，CUDA 5.0\n\n* [SubMicroTrading](https:\u002F\u002Fgithub.com\u002Fgsitgithub\u002FSubMicroTrading) - Java超低延迟交易框架\n\n* [WPF\u002FMVVM实时交易应用](https:\u002F\u002Fwww.codeproject.com\u002FArticles\u002F326641\u002FWPF-MVVM-Real-Time-Trading-Application) - 架构设计\n\n* [TradeLink](https:\u002F\u002Fgithub.com\u002Fpracplayopen\u002Fcore) - TradeLink，最早的开源交易系统之一\n\n* [Reactive Trader](https:\u002F\u002Fgithub.com\u002FAdaptiveConsulting) - 使用响应式Rx框架，包括[Reactive Trader](https:\u002F\u002Fgithub.com\u002FAdaptiveConsulting\u002FReactiveTrader)和[Reactive Trader Cloud](https:\u002F\u002Fgithub.com\u002FAdaptiveConsulting\u002FReactiveTraderCloud)。演示可在[这里](https:\u002F\u002Fweb-demo.adaptivecluster.com\u002F)查看。\n\n* [QuantTrading](https:\u002F\u002Fgithub.com\u002Fletianzj\u002FQuantTrading) - 纯C#交易系统\n\n* [StockTrading](https:\u002F\u002Fgithub.com\u002Fhoumie\u002FStockTrading) - 利用WPF、WCF、PRISM、MVVM、多线程技术的C#系统\n\n* [Quanter](https:\u002F\u002Fgithub.com\u002Fsuperquanter\u002Fquanter) - 股票交易者\n\n* [StockSharp](https:\u002F\u002Fgithub.com\u002FStockSharp\u002FStockSharp) - C#交易系统\n\n* [SharpQuant](https:\u002F\u002Fgithub.com\u002Fsmartquant\u002FSharpQuant.QuantStudio) - C#交易系统\n\n* [QuantSys](https:\u002F\u002Fgithub.com\u002Fexl3\u002FQuantSys) - C#交易系统\n\n* [StockTicker](https:\u002F\u002Fgithub.com\u002Fdanielmarbach\u002FStockTicker) - C#交易系统\n\n* [gotrade](https:\u002F\u002Fgithub.com\u002Fcyanly\u002Fgotrade) - 用Go语言编写的电子交易与订单管理系统\n\n* [gofinance](https:\u002F\u002Fgithub.com\u002Faktau\u002Fgofinance) - Go语言中的金融信息获取与处理\n\n* [goib](https:\u002F\u002Fgithub.com\u002Fgofinance\u002Fib) - 纯Go语言的互动经纪商IB API接口\n\n* [Matlab交易工具箱](https:\u002F\u002Fwww.mathworks.com\u002Fproducts\u002Ftrading.html) - MathWorks官方工具箱；配套有[Matlab交易工具箱入门](https:\u002F\u002Fwww.mathworks.com\u002Fmatlabcentral\u002Ffileexchange\u002F52588-automated-trading-system-development-with-matlab?focused=5253184&tab=example)，以及[使用MATLAB开发自动化交易系统网络研讨会](https:\u002F\u002Fwww.mathworks.com\u002Fvideos\u002Fautomated-trading-system-development-with-matlab-106851.html)、[使用MATLAB进行自动化交易网络研讨会](https:\u002F\u002Fwww.mathworks.com\u002Fvideos\u002Fautomated-trading-with-matlab-81911.html)、[MATLAB实时交易系统网络研讨会](https:\u002F\u002Fwww.mathworks.com\u002Fvideos\u002Fa-real-time-trading-system-in-matlab-92900.html)、[使用MATLAB进行自动化交易](https:\u002F\u002Fwww.mathworks.com\u002Fvideos\u002Fautomated-trading-with-matlab-81911.html)、[使用MATLAB进行商品交易网络研讨会](https:\u002F\u002Fwww.mathworks.com\u002Fvideos\u002Fcommodities-trading-with-matlab-81986.html)、[使用计量经济学工具箱进行协整与配对交易网络研讨会](https:\u002F\u002Fwww.mathworks.com\u002Fvideos\u002Fcointegration-and-pairs-trading-with-econometrics-toolbox-81799.html)\n\n* [Matlab风险管理工具箱](https:\u002F\u002Fwww.mathworks.com\u002Fproducts\u002Frisk-management.html) - MathWorks官方风险管理工具箱\n\n* [Matlab向前推进分析工具箱](https:\u002F\u002Fwfatoolbox.com\u002F) - 用于向前推进分析的工具箱\n\n* [IB4m](https:\u002F\u002Fgithub.com\u002Fsoftwarespartan\u002FIB4m) - MATLAB与互动经纪商的接口\n\n* [IB-Matlab](https:\u002F\u002Fundocumentedmatlab.com\u002Fib-matlab\u002F) - 另一种MATLAB与互动经纪商接口的介绍及[演示视频](https:\u002F\u002Fundocumentedmatlab.com\u002Fib-matlab\u002Freal-time-trading-system-demo)\n\n* [openAlgo Matlab](https:\u002F\u002Fgithub.com\u002Fmtompkins\u002FopenAlgo\u002Ftree\u002Fmaster\u002FMatlab) - openAlgo的MATLAB库\n\n* [MatTest](https:\u002F\u002Fgithub.com\u002Fedisonhyc\u002FMatTest) - MATLAB回测系统\n\n## 量化库\n\n* [Quantlib](https:\u002F\u002Fwww.quantlib.org\u002F) - 著名的C++量化金融库；可通过Swig翻译成其他语言\n\n* [TA-Lib](https:\u002F\u002Fgithub.com\u002Fmrjbq7\u002Fta-lib) - TA-Lib的Python封装\n\n* [DX Analytics](https:\u002F\u002Fdx-analytics.com\u002F) - 基于Python的金融分析库\n\n* [FinMath](http:\u002F\u002Ffinmath.net\u002F) - Java分析库\n\n* [OpenGamma](https:\u002F\u002Fopengamma.com\u002F) - 名为STRATA的Java分析库\n\n* [Quantiacs](https:\u002F\u002Fgithub.com\u002FQuantiacs) - [Matlab](https:\u002F\u002Fgithub.com\u002FQuantiacs\u002Fquantiacs-matlab)工具箱\n\n* [pyflux](https:\u002F\u002Fgithub.com\u002FRJT1990\u002Fpyflux) - 开源的Python时间序列库\n\n* [arch](https:\u002F\u002Fgithub.com\u002Fbashtage\u002Farch) - Python中的ARCH模型\n\n* [flint](https:\u002F\u002Fgithub.com\u002Ftwosigma\u002Fflint) - 面向Apache Spark的时间序列库\n\n* [Statsmodels](https:\u002F\u002Fwww.statsmodels.org) - Statsmodels的文档\n\n## 定量模型\n\n* [awesome-deep-trading](https:\u002F\u002Fgithub.com\u002Fcbailes\u002Fawesome-deep-trading) - 用于交易的机器学习资源列表\n\n* [Awesome-Quant-Machine-Learning-Trading](https:\u002F\u002Fgithub.com\u002Fgrananqvist\u002FAwesome-Quant-Machine-Learning-Trading) - 另一个用于交易的机器学习资源列表\n\n* [awesome-ai-in-finance](https:\u002F\u002Fgithub.com\u002Fgeorgezouq\u002Fawesome-ai-in-finance) - 金融领域的人工智能资源集合\n\n* [deepstock](https:\u002F\u002Fgithub.com\u002Fkeon\u002Fdeepstock) - 利用深度学习击败股市的技术实验\n\n* [qtrader](https:\u002F\u002Fgithub.com\u002Ffilangel\u002Fqtrader) - 用于投资组合管理的强化学习\n\n* [stockPredictor](https:\u002F\u002Fgithub.com\u002FNazanin1369\u002FstockPredictor) - 使用机器学习和深度学习算法预测股票走势\n\n* [stock_market_reinforcement_learning](https:\u002F\u002Fgithub.com\u002Fkh-kim\u002Fstock_market_reinforcement_learning) - 基于OpenGym的股市环境，结合深度Q-learning和策略梯度方法\n\n* [deep-algotrading](https:\u002F\u002Fgithub.com\u002FLiamConnell\u002Fdeep-algotrading) - 从回归到LSTM的深度学习技术在金融数据中的应用\n\n* [deep_trader](https:\u002F\u002Fgithub.com\u002Fdeependersingla\u002Fdeep_trader) - 在股票市场上使用强化学习，让智能体尝试学习交易策略。\n\n* [Deep-Trading](https:\u002F\u002Fgithub.com\u002FRachnog\u002FDeep-Trading) - 结合深度学习的算法交易实验\n\n* [Deep-Trading](https:\u002F\u002Fgithub.com\u002Fha2emnomer\u002FDeep-Trading) - 使用RNN进行算法交易\n\n* [100 Day Machine Learning](https:\u002F\u002Fgithub.com\u002FAvik-Jain\u002F100-Days-Of-ML-Code) - 包含代码的机器学习教程\n\n* [Multidimensional-LSTM-BitCoin-Time-Series](https:\u002F\u002Fgithub.com\u002Fjaungiers\u002FMultidimensional-LSTM-BitCoin-Time-Series) - 使用多维LSTM神经网络对比特币价格进行预测\n\n* [QLearning_Trading](https:\u002F\u002Fgithub.com\u002Fucaiado\u002FQLearning_Trading) - 在强化学习框架下学习交易\n\n* [bulbea](https:\u002F\u002Fgithub.com\u002Fachillesrasquinha\u002Fbulbea) - 基于深度学习的Python库，用于股市预测与建模\n\n* [PGPortfolio](https:\u002F\u002Fgithub.com\u002FZhengyaoJiang\u002FPGPortfolio) - “一种用于金融投资组合管理问题的深度强化学习框架”的源代码\n\n* [gym-trading](https:\u002F\u002Fgithub.com\u002Fhackthemarket\u002Fgym-trading) - 用于强化学习算法交易模型的环境\n\n* [Thesis](https:\u002F\u002Fgithub.com\u002Fpnecchi\u002FThesis) - 用于自动化交易的强化学习\n\n* [DQN](https:\u002F\u002Fgithub.com\u002Fjjakimoto\u002FDQN) - 用于金融领域的强化学习\n\n* [Deep-Trading-Agent](https:\u002F\u002Fgithub.com\u002Fsamre12\u002Fdeep-trading-agent) - 基于深度强化学习的比特币交易智能体\n\n* [deep_portfolio](https:\u002F\u002Fgithub.com\u002Fdeependersingla\u002Fdeep_portfolio) - 使用强化学习和监督学习优化投资组合配置\n\n* [Deep-Reinforcement-Learning-in-Stock-Trading](https:\u002F\u002Fgithub.com\u002Fshenyichen105\u002FDeep-Reinforcement-Learning-in-Stock-Trading) - 利用深度演员-评论家模型学习配对交易的最佳策略\n\n* [Stock-Price-Prediction-LSTM](https:\u002F\u002Fgithub.com\u002FNourozR\u002FStock-Price-Prediction-LSTM) - 使用LSTM循环神经网络预测苹果公司的OHLC平均值\n\n* [DeepDow](https:\u002F\u002Fgithub.com\u002Fjankrepl\u002Fdeepdow) - 利用深度学习进行投资组合优化\n\n* [Personae](https:\u002F\u002Fgithub.com\u002FCeruleanacg\u002FPersonae) - 基于深度学习的量化交易\n\n* [tensortrade](https:\u002F\u002Fgithub.com\u002Ftensortrade-org\u002Ftensortrade) - 强化学习与交易结合\n\n* [stockpredictionai](https:\u002F\u002Fgithub.com\u002Fborisbanushev\u002Fstockpredictionai) - 将GAN、PPO等AI模型应用于股票市场\n\n* [machine-learning-for-trading](https:\u002F\u002Fgithub.com\u002Fstefan-jansen\u002Fmachine-learning-for-trading) - 关于算法交易的机器学习书籍\n\n* [algorithmic-trading-with-python](https:\u002F\u002Fgithub.com\u002Fchrisconlan\u002Falgorithmic-trading-with-python) - 一本关于使用Python进行算法交易的书籍（2020年）\n\n* [machine-learning-asset-management](https:\u002F\u002Fgithub.com\u002Ffirmai\u002Fmachine-learning-asset-management) - 由[firmai.org](https:\u002F\u002Fwww.firmai.org\u002F)发布的资产管理中的机器学习\n\n## 交易API\n\n* [Interactive Brokers](https:\u002F\u002Fwww.interactivebrokers.com) - 受散户投资者欢迎\n\n* [Bloomberg API](https:\u002F\u002Fwww.bloomberg.com\u002Fprofessional\u002Fsupport\u002Fapi-library\u002F) - 来自彭博社\n\n## 数据源\n\n* [Quandl](https:\u002F\u002Fwww.quandl.com\u002F) - 提供免费及付费数据源\n\n* [iex](https:\u002F\u002Fiextrading.com\u002Ftrading\u002Fmarket-data\u002F) - 免费市场数据\n\n* [one tick](https:\u002F\u002Fwww.onetick.com\u002F) - 历史分笔数据\n\n* [iqfeed](https:\u002F\u002Fwww.iqfeed.net\u002F) - 实时数据流\n\n* [quantquote](https:\u002F\u002Fquantquote.com\u002F) - 分笔及实时数据\n\n* [algoseek](https:\u002F\u002Fwww.algoseek.com\u002F) - 历史日内数据\n\n* [EOD data](https:\u002F\u002Feoddata.com\u002F) - 历史数据\n\n* [EOD historical data](https:\u002F\u002Feodhistoricaldata.com\u002F) - 历史数据\n\n* [intrinio](https:\u002F\u002Fintrinio.com\u002F) - 金融数据\n\n* [arctic](https:\u002F\u002Fgithub.com\u002Fmanahl\u002Farctic) - 由[Man AHL](https:\u002F\u002Fwww.ahl.com\u002F)提供的高性能时序与分笔数据存储系统\n\n* [SEC EDGAR API](https:\u002F\u002Fsec-api.io\u002F) - 查询美国证券交易委员会EDGAR数据库中的公司文件\n\n## 加密货币\n\n* [Blockchain-stuff](https:\u002F\u002Fgithub.com\u002FXel\u002FBlockchain-stuff) - 区块链与加密货币资源\n\n* [cryptrader](https:\u002F\u002Fcryptotrader.org\u002F) - 用于MtGox\u002FBitstamp\u002FBTC-E\u002FCEX.IO的Node.js比特币机器人；[cryptrade](https:\u002F\u002Fgithub.com\u002Fdonfanning\u002Fcryptrade)\n\n* [BitcoinExchangeFH](https:\u002F\u002Fgithub.com\u002FBitcoinExchangeFH\u002FBitcoinExchangeFH) - 加密货币交易所市场数据馈送处理程序\n\n* [hummingbot](http:\u002F\u002Fhummingbot.io) - 免费的[开源](https:\u002F\u002Fgithub.com\u002FCoinAlpha\u002Fhummingbot\u002F)加密货币交易机器人，支持去中心化交易所和中心化交易所\n\n* [blackbird](https:\u002F\u002Fgithub.com\u002Fbutor\u002Fblackbird) - C++交易系统，可在比特币交易所之间进行自动多空套利\n\n* [Peatio](https:\u002F\u002Fwww.peatio.tech) - 基于[github](https:\u002F\u002Fgithub.com\u002Fpeatio\u002Fpeatio)的开源加密货币交易所\n\n* [Qt Bitcoin Trader](https:\u002F\u002Fgithub.com\u002FJulyIGHOR\u002FQtBitcoinTrader) - Qt C++比特币交易\n\n* [ccxt](https:\u002F\u002Fgithub.com\u002Fccxt\u002Fccxt) - 支持130多家比特币\u002F山寨币交易所的JavaScript\u002FPython\u002FPHP加密货币交易库\n\n* [r2](https:\u002F\u002Fgithub.com\u002Fbitrinjani\u002Fr2) - 基于Node.js + TypeScript的全自动套利交易系统\n\n* [bcoin](https:\u002F\u002Fgithub.com\u002Fbcoin-org\u002Fbcoin) - 适用于Node.js和[浏览器](https:\u002F\u002Fbcoin.io\u002F)的Javascript比特币库\n\n* [XChange](https:\u002F\u002Fgithub.com\u002Fknowm\u002FXChange) - 提供简洁API以对接60多家比特币和山寨币交易所的Java库\n\n* [Krypto-trading-bot](https:\u002F\u002Fgithub.com\u002Fctubio\u002FKrypto-trading-bot) - 自托管的加密货币交易机器人（自动化高频做市），使用Node.js、Angular、TypeScript和C++\n\n* [freqtrade](https:\u002F\u002Fgithub.com\u002Ffreqtrade\u002Ffreqtrade) - 简单的高频加密货币交易机器人\n\n* [Gekko](https:\u002F\u002Fgithub.com\u002Faskmike\u002Fgekko) - 使用Node编写的比特币交易机器人\n\n* [viabtc_exchange_server](https:\u002F\u002Fgithub.com\u002Fviabtc\u002Fviabtc_exchange_server) - 高速性能且具备实时通知功能的交易引擎\n\n* [catalyst](https:\u002F\u002Fgithub.com\u002Fenigmampc\u002Fcatalyst) - 用于加密资产的Python算法交易库，由[Enigma](https:\u002F\u002Fenigma.co\u002F)开发\n\n* [buttercoin](https:\u002F\u002Fgithub.com\u002Fbuttercoin\u002Fbuttercoin) - 开源比特币交易所软件\n\n* [zenbot](https:\u002F\u002Fgithub.com\u002FDeviaVir\u002Fzenbot) - 使用Node.js和MongoDB的命令行加密货币交易机器人\n\n* [tribeca](https:\u002F\u002Fgithub.com\u002Fmichaelgrosner\u002Ftribeca) - 基于Node.js的高频做市加密货币交易平台\n\n* [rbtc_arbitrage](https:\u002F\u002Fgithub.com\u002Fhstove\u002Frbtc_arbitrage) - 用于自动化比特币交易所间套利的Ruby gem\n\n* [automated-trading](https:\u002F\u002Fgithub.com\u002Fbevry-trading\u002Fautomated-trading) - 自动化交易：Trading View策略 => Bitfinex, itBit, DriveWealth\n\n* [gocryptotrader](https:\u002F\u002Fgithub.com\u002Fthrasher-\u002Fgocryptotrader) - 使用Golang编写的多交易所支持的加密货币交易机器人及框架\n\n* [btcrobot](https:\u002F\u002Fgithub.com\u002Fphilsong\u002Fbtcrobot) - Golang比特币交易机器人\n\n* [bitex](https:\u002F\u002Fgithub.com\u002Fblinktrade\u002Fbitex) - 开源比特币交易所；及其[前端](https:\u002F\u002Fgithub.com\u002Fblinktrade\u002Ffrontend)\n\n* [cryptoworks](https:\u002F\u002Fcryptoworks.co\u002F) - 加密货币套利机会计算器。覆盖800多种币种和50个市场；[cryptocurrency-arbitrage](https:\u002F\u002Fgithub.com\u002Fmanu354\u002Fcryptocurrency-arbitrage)\n\n* [crypto-exchange](https:\u002F\u002Fgithub.com\u002Fpassabilities\u002Fcrypto-exchange) - 列出可统一通过API交互的加密货币交易所\n\n* [bitcoin-abe](https:\u002F\u002Fgithub.com\u002Fbitcoin-abe\u002Fbitcoin-abe) - 比特币及类似币种的区块浏览器\n\n* [MultiPoolMiner](https:\u002F\u002Fgithub.com\u002FMultiPoolMiner\u002FMultiPoolMiner) - 实时监控加密货币挖矿池，以找到对您的机器最有利的矿池。可控制任何可通过命令行访问的矿机\n\n* [tai](https:\u002F\u002Fgithub.com\u002Ffremantle-capital\u002Ftai) - 开源、可组合、实时的市场数据与交易执行工具包，使用Elixir编写\n\n* [crypto-signal](https:\u002F\u002Fgithub.com\u002FCryptoSignal\u002Fcrypto-signal) - 多交易所技术信号\n\n## 公司\n\n不求详尽\n\n* [卖方](https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FList_of_investment_banks)\n\n* [FIA PTG](http:\u002F\u002Fwww.marketswiki.com\u002Fwiki\u002FPrincipal_Traders_Group) 和 [FIA Europe](https:\u002F\u002Fwww.fia.org\u002Fepta-membership)\n\n* [Allston Trading](http:\u002F\u002Fwww.marketswiki.com\u002Fwiki\u002FAllston_Trading,_LLC)\n\n* [CTC](http:\u002F\u002Fwww.marketswiki.com\u002Fwiki\u002FChicago_Trading_Company)\n\n* [Citadel](https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FCitadel_LLC)\n\n* [D.E. Shaw](https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FD._E._Shaw_%26_Co.)\n\n* [DRW](http:\u002F\u002Fwww.marketswiki.com\u002Fwiki\u002FDRW)\n\n* [Flow Traders](https:\u002F\u002Fwww.flowtraders.com\u002F)\n\n* [GTS](http:\u002F\u002Fwww.gtsx.com\u002F)\n\n* [HRT](https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FHudson_River_Trading)\n\n* [IMC](https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FIMC_Financial_Markets)\n\n* [Infinium](http:\u002F\u002Fwww.marketswiki.com\u002Fwiki\u002FInfinium_Capital_Management,_LLC)\n\n* [Jane Street](https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FJane_Street_Capital)\n\n* [Jump Trading](http:\u002F\u002Fwww.marketswiki.com\u002Fwiki\u002FJump_Trading_LLC)\n\n* [Millennium](https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FMillennium_Management,_LLC)\n\n* [Optiver](https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FOptiver)\n\n* [Quantlab Financial](https:\u002F\u002Fwww.quantlab.com\u002F)\n\n* [Renaissance](https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FRenaissance_Technologies)\n\n* [Bridgewater Associates](https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FBridgewater_Associates)\n\n* [Man Group](https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FMan_Group)，[AHL](https:\u002F\u002Fwww.ahl.com\u002F)\n\n* [SIG](https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FSusquehanna_International_Group)\n\n* [Tower Research](https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FTower_Research)\n\n* [Tradebot Systems](https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FTradebot)\n\n* [Two Sigma](https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FTwo_Sigma)\n\n* [Virtu Financial](https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FVirtu_Financial)\n\n* [XR Trading](http:\u002F\u002Fwww.xrtrading.com\u002F)\n\n* [XTX Markets](https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FXTX_Markets)\n\n专注于大宗商品的公司\n\n* [Cargill](https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FCargill)\n\n* [Glencore](https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FGlencore)\n\n* [Mercuria](https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FMercuria_Energy_Group)\n\n* [Trafigura](https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FTrafigura)\n\n* [Vigor](https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FVitol)\n\n## 金融科技\n\n* [Alpaca](https:\u002F\u002Fwww.alpaca.ai\u002F)\n\n* [Knesho](https:\u002F\u002Fwww.kensho.com\u002F)\n\n* [Neotic](https:\u002F\u002Fneotic.ai\u002F)\n\n* [Numerai](https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FNumerai)\n\n* [Symphony](https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FSymphony_Communication)\n\n## 网站 论坛 博客\n\n* [顶尖极客量化博客](https:\u002F\u002Falphaarchitect.com\u002F2014\u002F10\u002F13\u002Ftop-geeky-quant-blogs\u002F#.VECOwfldV8E) - 一份量化博客推荐清单\n\n* [Quantocracy](https:\u002F\u002Fquantocracy.com\u002F) - 量化相关新闻聚合平台\n\n* [Seeking Alpha](https:\u002F\u002Fseekingalpha.com\u002F) - Seeking Alpha 社区\n\n* [Quantivity](https:\u002F\u002Fquantivity.wordpress.com\u002F) - 定量与算法交易\n\n* [Wilmott](https:\u002F\u002Fwww.wilmott.com\u002F) - 定量金融社区论坛\n\n* [Elitetrader](https:\u002F\u002Fwww.elitetrader.com\u002F) - 交易论坛\n\n* [Nuclearphynance](https:\u002F\u002Fwww.nuclearphynance.com\u002F) - 定量金融论坛\n\n* [Investopedia](https:\u002F\u002Fwww.investopedia.com\u002F) - 投资百科全书\n\n* [Quantpedia](https:\u002F\u002Fwww.quantpedia.com\u002F) - 定量交易策略百科全书\n\n* [EpChan](https:\u002F\u002Fepchan.blogspot.com\u002F) - 埃尔尼·陈博士的博客\n\n* [Quantinsti](https:\u002F\u002Fquantra.quantinsti.com\u002F) - 量化研究院\n\n* [QuantStart](https:\u002F\u002Fwww.quantstart.com\u002F) - 迈克尔·霍尔斯-摩尔的 QuantStart，量化交易入门；其 Python 回测平台 [qstrader](https:\u002F\u002Fgithub.com\u002Fmhallsmoore\u002Fqstrader) 和 [qsforex](https:\u002F\u002Fgithub.com\u002Fmhallsmoore\u002Fqsforex)\n\n* [Algotrading 101](https:\u002F\u002Falgotrading101.com\u002F) - 算法交易入门\n\n* [Systematic Investor](https:\u002F\u002Fsystematicinvestor.github.io\u002F)\u002F[旧版](https:\u002F\u002Fsystematicinvestor.wordpress.com\u002F) - [迈克尔·卡普勒](https:\u002F\u002Fwww.linkedin.com\u002Fin\u002Fmichael-kapler-mmf-cfa-92a1a02\u002F?ppe=1) 的博客，最佳 R 语言量化博客之一；[Systematic Investor Toolkit](https:\u002F\u002Fgithub.com\u002Fsystematicinvestor\u002FSIT)\n\n* [R-Finance](https:\u002F\u002Fgithub.com\u002FR-Finance) - R-Finance 代码库。包含回测工具 [quantstrat](https:\u002F\u002Fgithub.com\u002FR-Finance\u002Fquantstrat)、[trade blotter](https:\u002F\u002Fgithub.com\u002FR-Finance\u002Fblotter)，以及著名的 [performance analytics](https:\u002F\u002Fgithub.com\u002FR-Finance\u002FPerformanceAnalytics) 包和 [portfolio analytics](https:\u002F\u002Fgithub.com\u002FR-Finance\u002FPortfolioAnalytics)、[portfolio attribution](https:\u002F\u002Fgithub.com\u002FR-Finance\u002FPortfolioAttribution) 包。\n\n* [quantmod](https:\u002F\u002Fwww.quantmod.com\u002F) - R 语言建模与交易框架\n\n* [R 编程](http:\u002F\u002Fwww.r-programming.org\u002Fpapers) - 盖伊·约林的 R 回测\n\n* [Seer Trading](http:\u002F\u002Fwww.seertrading.com\u002F) - R 回测与实盘交易\n\n* [Trading with Python](https:\u002F\u002Ftradingwithpython.blogspot.com\u002F)\n\n* [Python 编程金融](https:\u002F\u002Fpythonprogramming.net\u002Ffinance-tutorials\u002F) - Python 金融教程及 Quantopian 教程\n\n* [Python for Finance](https:\u002F\u002Fwww.pythonforfinance.net\u002F) - Python 金融\n\n* [Quant Econ](https:\u002F\u002Fquantecon.org\u002F) - 经济建模的开源 Python 和 Julia 代码；以及相关课程\n\n* [JuliaQuant](https:\u002F\u002Fgithub.com\u002FJuliaQuant) - Julia 语言下的量化金融\n\n* [Portfolio Effect](https:\u002F\u002Fwww.portfolioeffect.com\u002F) - 实时投资组合与风险管理\n\n* [quant365](http:\u002F\u002Fwww.quant365.com\u002F) - 亨利·穆的博客与交易系统；包括 Sentosa、[pysentosa 绑定](https:\u002F\u002Fgithub.com\u002Fhenrywoo\u002Fpysentosa)、rsentosa 绑定以及 [qblog](https:\u002F\u002Fgithub.com\u002Fhenrywoo\u002Fqblog)。\n\n* [hpc quantlib](https:\u002F\u002Fhpcquantlib.wordpress.com\u002F) - 高性能计算 + QuantLib\n\n* [Quant Corner](https:\u002F\u002Fquantcorner.wordpress.com\u002F)\n\n* [quantstrat trader](https:\u002F\u002Fquantstrattrader.wordpress.com\u002F) - 使用 R 语言 [QuantStrat](https:\u002F\u002Fgithub.com\u002FR-Finance\u002Fquantstrat) 包回测交易策略\n\n* [Backtesting Strategies](https:\u002F\u002Ftimtrice.github.io\u002Fbacktesting-strategies\u002F) - R 语言中的回测；代码托管于 [Github](https:\u002F\u002Fgithub.com\u002Ftimtrice\u002Fbacktesting-strategies)\n\n* [The Quant MBA](https:\u002F\u002Fthequantmba.wordpress.com\u002F) - 优秀的量化博客\n\n* [Foss Trading](http:\u002F\u002Fblog.fosstrading.com\u002F) - 使用免费开源软件进行算法交易\n\n* [Gekko Quant](http:\u002F\u002Fgekkoquant.com\u002F) - 定量交易\n\n* [Investment Idiocy](https:\u002F\u002Fqoppac.blogspot.com\u002F) - 罗伯特·卡弗关于系统性交易、定量金融、投资、金融行动主义及经济决策的讨论；[他的著作](https:\u002F\u002Fwww.amazon.com\u002FSystematic-Trading-designing-trading-investing\u002Fdp\u002F0857194453) 和 [他的 Python 库](https:\u002F\u002Fgithub.com\u002Frobcarver17\u002Fpysystemtrade)\n\n* [Quantifiable Edges](https:\u002F\u002Fquantifiableedges.com\u002Fblog\u002F)\u002F[旧版](https:\u002F\u002Fquantifiableedges.blogspot.com\u002F) - 利用指标与历史数据评估市场走势\n\n* [My Simple Quant](http:\u002F\u002Fmysimplequant.blogspot.com\u002F) - 基于历史回测数据的市场分析\n\n* [Vix and more](https:\u002F\u002Fvixandmore.blogspot.com\u002F) - 关于 VIX 的讨论\n\n* [Timely Portfolio](https:\u002F\u002Ftimelyportfolio.blogspot.com\u002F) - R 语言中的策略与测试\n\n* [Quantitative Research and Trading](https:\u002F\u002Fjonathankinlay.com\u002F)\n\n* [Qusma](https:\u002F\u002Fqusma.com\u002F) - 定量系统性市场分析\n\n* [return and risk](http:\u002F\u002Fwww.returnandrisk.com\u002F) - 定量金融、分析及其应用\n\n* [Physics of Finance](https:\u002F\u002Fphysicsoffinance.blogspot.com\u002F) - 以物理学为灵感思考经济、金融和社会系统\n\n* [Quantum Financier](https:\u002F\u002Fquantumfinancier.wordpress.com\u002F) - 算法交易\n\n* [Trading the Odds](http:\u002F\u002Fwww.tradingtheodds.com\u002F) -- 市场择时与定量分析\n\n* [CSSA](https:\u002F\u002Fcssanalytics.wordpress.com\u002F) - 定量研究的新概念\n\n* [The Practical Quant](https:\u002F\u002Fpracticalquant.blogspot.com\u002F)\n\n* [Tr8dr](https:\u002F\u002Ftr8dr.github.io\u002F) - 战略、统计学、计算机科学、数值方法\n\n* [Deniz's Note](https:\u002F\u002Fdenizstij.blogspot.com\u002F) - 量化分析师德尼兹·图兰的博客\n\n* [Quant at risk](http:\u002F\u002Fwww.quantatrisk.com\u002F) - 定量分析与风险管理\n\n* [Quant Blog](https:\u002F\u002Fletianzj.github.io\u002F) - 定量交易、投资组合管理与机器学习，附带 [Github 上的源代码](https:\u002F\u002Fgithub.com\u002Fletianzj\u002FQuantResearch)\n\n* [The R Trader](https:\u002F\u002Fwww.thertrader.com\u002F) - 在量化金融中使用 R 语言\n\n* [rbresearch](https:\u002F\u002Frbresearch.wordpress.com\u002F) - 利用 R 语言探索外汇和股票市场的交易策略\n\n* [NaN Quantivity](https:\u002F\u002Fquantlife.wordpress.com\u002F) - 量化交易、统计学习、编程与头脑风暴\n\n* [Factor Investing](https:\u002F\u002Ffactorinvestingtutorial.wordpress.com\u002F) - WordPress 上的博客\n\n* [Meb Faber Research](https:\u002F\u002Fmebfaber.com\u002F)\n\n* [Big Mike Trading](https:\u002F\u002Fwww.youtube.com\u002Fuser\u002FBigMikeTrading\u002Fvideos) - 量化交易领域的 YouTube 频道\n\n* [Mechanical Markets](https:\u002F\u002Fmechanicalmarkets.wordpress.com\u002F)\n\n* [Humble Student of the Markets](https:\u002F\u002Fhumblestudentofthemarkets.blogspot.com\u002F)\n\n* [使用 RNN 预测股票价格](https:\u002F\u002Flilianweng.github.io\u002Flil-log\u002F2017\u002F07\u002F08\u002Fpredict-stock-prices-using-RNN-part-1.html)\n\n* [BlackArbs](http:\u002F\u002Fwww.blackarbs.com\u002Fblog) - 博客及 [Github 上的机器学习笔记本](https:\u002F\u002Fgithub.com\u002FBlackArbsCEO\u002FAdv_Fin_ML_Exercises)","# EliteQuant 快速上手指南\n\n**注意**：EliteQuant 并非一个单一的独立软件包，而是一个**量化金融开源资源精选列表**。它汇集了交易平台、交易系统、量化库、模型及数据源等优质项目。因此，本指南将指导你如何利用该列表找到适合的工具，并以列表中极具代表性的 Python 量化框架 `vnpy` 和通用依赖安装为例，演示如何开始量化开发。\n\n## 环境准备\n\n在开始之前，请确保你的开发环境满足以下基本要求。大多数推荐的量化工具（如 `vnpy`, `zipline`, `backtrader`）主要基于 Python 生态。\n\n*   **操作系统**：推荐 Linux (Ubuntu\u002FCentOS) 或 macOS。Windows 用户建议使用 WSL2 (Windows Subsystem for Linux) 以获得更好的兼容性，或直接使用 Windows 10\u002F11（部分 C++ 底层库可能需要额外配置）。\n*   **Python 版本**：建议安装 **Python 3.8 - 3.10**（许多量化库对最新 Python 版本支持可能有延迟）。\n*   **前置依赖**：\n    *   `git`：用于克隆代码仓库。\n    *   `pip` 或 `conda`：包管理工具。\n    *   `C++ 编译器`：部分高性能库（如 `TA-Lib`, `QuantLib`）需要编译环境。\n        *   Linux: `build-essential`\n        *   macOS: `Xcode Command Line Tools`\n        *   Windows: `Microsoft C++ Build Tools`\n\n## 安装步骤\n\n由于 EliteQuant 包含多个项目，此处以国内开发者广泛使用的 **vnpy**（社区版量化交易框架）为例进行安装演示，同时介绍如何安装通用的量化基础库。\n\n### 1. 配置国内镜像源（加速下载）\n为避免网络问题，建议将 pip 源切换至清华大学或阿里云镜像。\n\n```bash\nmkdir -p ~\u002F.pip\ncat \u003C\u003CEOF > ~\u002F.pip\u002Fpip.conf\n[global]\nindex-url = https:\u002F\u002Fpypi.tuna.tsinghua.edu.cn\u002Fsimple\ntrusted-host = pypi.tuna.tsinghua.edu.cn\nEOF\n```\n\n### 2. 安装基础量化依赖\n许多量化项目依赖 `TA-Lib` 进行技术指标计算。建议先通过系统包管理器安装底层库，再安装 Python 包装器。\n\n**Linux (Ubuntu\u002FDebian):**\n```bash\nsudo apt-get update\nsudo apt-get install -y build-essential libta-lib-dev\npip install ta-lib\n```\n\n**macOS (使用 Homebrew):**\n```bash\nbrew install ta-lib\npip install ta-lib\n```\n\n**Windows:**\n建议直接下载预编译的 `.whl` 文件安装，或使用 `conda`：\n```bash\nconda install -c conda-forge ta-lib\n```\n\n### 3. 安装示例框架 (vnpy)\n`vnpy` 是 EliteQuant 列表中推荐的强大开源交易平台，支持多种接口。\n\n```bash\n# 克隆 vnpy 仓库\ngit clone https:\u002F\u002Fgithub.com\u002Fvnpy\u002Fvnpy.git\ncd vnpy\n\n# 安装依赖\npip install -r requirements.txt\n\n# 安装 vnpy 核心包\npip install .\n```\n\n*注：若需使用其他列表中的工具（如 `backtrader` 或 `zipline`），可直接运行 `pip install backtrader` 等命令。*\n\n## 基本使用\n\n以下示例展示如何使用 Python 调用量化库进行简单的策略回测逻辑（基于 `vnpy` 风格伪代码及通用 `pandas` 数据处理），这是量化开发的最简起点。\n\n### 1. 导入必要的库\n```python\nimport pandas as pd\nimport numpy as np\n# 假设已安装 vnpy 或类似的回测引擎\n# from vnpy.trader.engine import MainEngine \n```\n\n### 2. 加载数据与计算指标\n利用 `TA-Lib` 或 `pandas` 计算移动平均线（MA），这是最基础的量化模型。\n\n```python\n# 模拟生成一些收盘价数据\ndates = pd.date_range(start='2023-01-01', periods=100)\nclose_prices = np.random.rand(100) * 100 + 200\n\ndf = pd.DataFrame({'close': close_prices}, index=dates)\n\n# 计算简单移动平均线 (SMA)\nwindow = 20\ndf['sma_20'] = df['close'].rolling(window=window).mean()\n\n# 生成简单的交易信号：当收盘价上穿均线时买入 (1)，下穿时卖出 (-1)\ndf['signal'] = 0\ndf.loc[df['close'] > df['sma_20'], 'signal'] = 1\ndf.loc[df['close'] \u003C df['sma_20'], 'signal'] = -1\n\nprint(df[['close', 'sma_20', 'signal']].tail())\n```\n\n### 3. 探索更多资源\n访问 EliteQuant 原始列表，根据需求选择特定领域的工具：\n*   **深度学习交易**：查看 `awesome-deep-trading` 列表，尝试 `deepstock` 项目。\n*   **高频交易 (HFT)**：参考 `OpenHFT` (Java) 或 `thOth` (C++)。\n*   **数据源**：查找 `Data Source` 章节获取免费或付费的市场数据接口。\n\n你可以随时回到 EliteQuant 仓库，搜索关键词（如 \"Reinforcement Learning\" 或 \"Crypto\"）来发现新的开源工具并重复上述安装流程。","某初创量化团队正在从零搭建自动化交易系统，急需整合回测框架、实时数据源及交易接口以验证策略。\n\n### 没有 EliteQuant 时\n- 团队成员需在 GitHub、论坛和技术博客中盲目搜索，耗费数周筛选出如 `vnpy` 或 `Backtrader` 等可靠库，效率极低。\n- 因缺乏权威指引，容易选中已停止维护的冷门项目（如某些无星数的旧库），导致后期代码重构成本高昂。\n- 难以系统性对比不同平台特性，例如不清楚 `QuantConnect` (C#) 与 `Quantopian` (Python) 的核心差异，选型决策全靠试错。\n- 数据源与交易 API 分散各处，新手常因找不到合规且低延迟的数据接口而卡在策略开发的第一步。\n\n### 使用 EliteQuant 后\n- 直接访问分类清晰的资源列表，几分钟内即可锁定高星开源项目（如 `zipline`、`pyalgotrade`），立即启动开发。\n- 依托\"GitHub 超 100 星”的推荐原则，自动过滤掉不稳定资源，确保技术栈基于成熟社区支持的方案构建。\n- 通过横向对比 `Trading System` 与 `Quantitative Trading Platform` 板块，迅速根据团队语言偏好（Python\u002FC#）选定最佳架构。\n- 在 `Data Source` 和 `Trading API` 专区一键获取经过验证的接口文档，大幅缩短从策略构思到实盘部署的周期。\n\nEliteQuant 将原本需要数周的调研工作压缩至数小时，为量化团队提供了一条通往成熟技术生态的捷径。","https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002FEliteQuant_EliteQuant_f50a1984.png","https:\u002F\u002Foss.gittoolsai.com\u002Favatars\u002FEliteQuant_f2b9061b.jpg","Online resources for quantitative trading and portfolio management\r\n",null,"https:\u002F\u002Fgithub.com\u002FEliteQuant",3788,659,"2026-04-11T12:00:57","Apache-2.0",1,"","未说明",{"notes":84,"python":82,"dependencies":85},"EliteQuant 本身不是一个单一的可执行软件或代码库，而是一个量化建模、交易和投资组合管理的在线资源列表（Awesome List）。README 中列出了数十个不同的开源项目（如 vnpy, Backtrader, QuantLib 等），这些项目各自拥有独立的运行环境需求（涵盖 Python, C++, C#, Java, Matlab, R, Golang 等多种语言）。因此，无法为整个列表提供统一的操作系统、GPU、内存或依赖库要求。用户需根据列表中具体感兴趣的项目，前往其对应的 GitHub 仓库查阅详细的环境配置说明。",[],[14],[88,89,90,91,92,93,94,95,96,97],"quantitative-trading","quantitative-finance","trading-platform","trading-systems","portfolio-management","asset-management","asset-pricing","mathematical-finance","machine-learning","algorithmic-trading","2026-03-27T02:49:30.150509","2026-04-12T05:14:53.118102",[],[]]