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Vibe-Trading

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"Vibe-Trading: Your Personal Trading Agent"

Subagents12k estrellas2.3k forksPythonMITActualizado today
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Vibe-Trading is a multi-agent Python framework that gives Claude and other LLMs a full suite of quantitative trading tools through a single pip install (`vibe-trading-ai`). It connects to Claude via MCP, meaning Claude Code and Claude Desktop can invoke its tools directly, and it also exposes a FastAPI backend with a React 19 frontend for chat-based interaction. The agent system includes named swarm presets such as an investment committee, quant desk, and risk committee, each with real-time per-worker status cards streamed into the chat timeline. An Alpha Zoo module houses over 191 backtestable alphas that can be benchmarked head-to-head using IC mean, information ratio, and IC-positive ratio metrics. A Shadow Account feature lets users simulate trades without real capital. The project targets retail traders, quant researchers, and developers who want to wire LLM reasoning into algorithmic trading workflows without building execution, backtesting, or data infrastructure from scratch.

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  • Open-source license (MIT)
  • Actively maintained (<30d)
  • Healthy fork ratio
  • Clear description
  • Topics declared
  • Documented (README)
Last scanned: 6/11/2026
Install as a Claude Code subagent
Method: Clone
Terminal
git clone https://github.com/HKUDS/Vibe-Trading && cp Vibe-Trading/*.md ~/.claude/agents/
1. Clone the repository and copy the agent .md definitions into ~/.claude/agents (or .claude/agents inside a project).
2. Start a new Claude Code session to load the agents.
3. Delegate work to them with the Task/Agent tool or by name.

24 items en este repositorio

Professional finance research toolkit — backtesting (7 engines + benchmark comparison panel), factor analysis, Alpha Zoo (452 pre-built alphas across qlib158/alpha101/gtja191/academic), options pricing, 77 finance skills, 29 multi-agent swarm teams, Trade Journal analyzer, and Shadow Account (extract → backtest → render) across 7 data sources (tushare, yfinance, okx, akshare, mootdx, ccxt, futu).

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ADR/H-share/A-share cross-listing premium analysis — track pricing gaps between US-listed ADRs, HK-listed H-shares, and A-shares for arbitrage signals, dual-listing valuation, and delisting risk assessment.

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akshareSkill

AKShare financial data aggregator (18k+ stars). Free, no API key. Covers A-shares, US, HK, futures, macro, forex. Primary fallback for tushare and yfinance.

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Browse and bench the bundled alpha zoos — prebuilt cross-sectional factor libraries (Kakushadze 101, GTJA 191, Qlib 158, Fama-French / Carhart). Use when the user asks "which alphas exist", wants metadata on a named alpha, or wants to run IC/IR on a whole zoo over a universe.

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A 股 ST/*ST 风险预测框架 — 基于最新中报/三季报或业绩预告/快报,预测下一财年是否会因营收、利润、净资产、分红不达标而被风险警示,并将新浪监管处罚记录作为独立证据面纳入风险等级。仅适用于 A 股,不预测财务造假。

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Asset allocation theory and optimizer usage — MPT / Black-Litterman / risk budgeting / all-weather strategy, including guides for 4 optimizers and rebalancing rules.

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Diagnose failed or underperforming backtests, locate the root cause, and fix the issue

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Behavioral finance applications: theories of overreaction and underreaction, behavioral explanations for momentum and reversal, investor sentiment cycles, cognitive-bias checklists, and debiasing quantitative strategies.

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Candlestick pattern recognition engine, pure pandas vectorized implementation of 15 classic candlestick patterns (5 single-candle + 5 double-candle + 4 triple-candle + 1 trend confirmation), generating a composite signal from bullish/bearish pattern scores.

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ccxtSkill

CCXT unified crypto exchange library (100+ exchanges). Free public market data. Fallback when OKX is unavailable.

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chanlunSkill

基于缠论(缠中说禅)的形态识别引擎,使用czsc库自动检测K线分型、笔、中枢,并生成一买/一卖/二买/二卖/三买/三卖等买卖点信号。支持多周期分析和形态分类(3/5/7/9/11笔形态)。

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Commodity analysis (oil supply-demand balance / gold pricing / copper as an economic predictor / inventory cycles / futures premium-discount structure / seasonality), generating directional commodity signals.

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A股可转债分析——转股/纯债/期权三维估值、下修/强赎/回售博弈、双低策略与转债轮动选债框架

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公司事件驱动分析:并购套利价差计算、大股东增减持信号、股权激励解读、定增配股影响评估、A股ST/退市预警

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Correlation and cointegration analysis — co-movement discovery, deep return-correlation analysis, sector clustering, realized correlation, Engle-Granger / Johansen cointegration, half-life, Kalman dynamic hedge ratio, cross-market linkage analysis, and pair-trading signal generation

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固收与信用分析:信用债评级、利差分析、违约风险评估、城投债研究、可转债定价与策略。

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Write signal_engine.py for portfolios spanning multiple markets (A-shares + crypto, equity + forex, etc.)

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Crypto-derivatives strategies — perpetual funding-rate arbitrage, futures term-structure contango/backwardation trading, and option volatility-smile / Greeks analysis.

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Data source selection decision tree. Load this skill BEFORE any backtest or data-fetching task to choose the best available data source.

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DeFi yield analysis and optimization — lending rates, LP yields, staking returns, yield farming strategies, risk-adjusted yield comparison, and protocol-level sustainability assessment.

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Dividend stock analysis for income, dividend-growth, and shareholder-return strategies, including yield quality, payout sustainability, ex-dividend mechanics, and yield-trap checks.

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Read any common document/data file — PDF, Word (.docx), Excel (.xlsx/.xls), PowerPoint (.pptx), images (OCR), CSV/TSV, plain text, JSON/YAML/TOML, HTML/XML, and most source-code files. Use the `read_document` tool.

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盈利预测与一致预期分析(自上而下/自下而上预测法/SUE/PEAD/分析师预期修正),捕捉业绩超预期交易机会。

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Earnings estimate revisions, guidance analysis, and post-earnings drift (PEAD) — track analyst consensus changes, earnings surprise patterns, and management guidance shifts for US/HK equities.

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Casos de uso

Resumen de Subagents

<p align="center">
  <b>English</b> | <a href="README_zh.md">中文</a> | <a href="README_ja.md">日本語</a> | <a href="README_ko.md">한국어</a> | <a href="README_ar.md">العربية</a>
</p>

<p align="center">
  <img src="assets/icon.png" width="120" alt="Vibe-Trading Logo"/>
</p>

<h1 align="center">Vibe-Trading: Your Personal Trading Agent</h1>

<p align="center">
  <b>One Command to Empower Your Agent with Comprehensive Trading Capabilities</b>
</p>

<p align="center">
  <a href="https://trendshift.io/repositories/25527" target="_blank"><img src="https://trendshift.io/api/badge/repositories/25527" alt="HKUDS%2FVibe-Trading | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
</p>

<p align="center">
  <img src="https://img.shields.io/badge/Python-3.11%2B-3776AB?style=flat&logo=python&logoColor=white" alt="Python">
  <img src="https://img.shields.io/badge/Backend-FastAPI-009688?style=flat" alt="FastAPI">
  <img src="https://img.shields.io/badge/Frontend-React%2019-61DAFB?style=flat&logo=react&logoColor=white" alt="React">
  <a href="https://pypi.org/project/vibe-trading-ai/"><img src="https://img.shields.io/pypi/v/vibe-trading-ai?style=flat&logo=pypi&logoColor=white" alt="PyPI"></a>
  <a href="LICENSE"><img src="https://img.shields.io/badge/License-MIT-yellow?style=flat" alt="License"></a>
  <br>
  <a href="https://github.com/HKUDS/.github/blob/main/profile/README.md"><img src="https://img.shields.io/badge/Feishu-Group-E9DBFC?style=flat-square&logo=feishu&logoColor=white" alt="Feishu"></a>
  <a href="https://github.com/HKUDS/.github/blob/main/profile/README.md"><img src="https://img.shields.io/badge/WeChat-Group-C5EAB4?style=flat-square&logo=wechat&logoColor=white" alt="WeChat"></a>
  <a href="https://discord.gg/2vDYc2w5"><img src="https://img.shields.io/badge/Discord-Join-7289DA?style=flat-square&logo=discord&logoColor=white" alt="Discord"></a>
</p>

<p align="center">
  <a href="https://vibetrading.wiki/">Website</a> &nbsp;&middot;&nbsp;
  <a href="https://vibetrading.wiki/docs/">Docs</a> &nbsp;&middot;&nbsp;
  <a href="#-news">News</a> &nbsp;&middot;&nbsp;
  <a href="#-key-features">Features</a> &nbsp;&middot;&nbsp;
  <a href="#-shadow-account">Shadow Account</a> &nbsp;&middot;&nbsp;
  <a href="#-demo">Demo</a> &nbsp;&middot;&nbsp;
  <a href="#-quick-start">Quick Start</a> &nbsp;&middot;&nbsp;
  <a href="#-examples">Examples</a> &nbsp;&middot;&nbsp;
  <a href="#-api-server">API / MCP</a> &nbsp;&middot;&nbsp;
  <a href="#-roadmap">Roadmap</a> &nbsp;&middot;&nbsp;
  <a href="#-contributing">Contributing</a>
</p>

<p align="center">
  <a href="#-quick-start"><img src="assets/pip-install.svg" height="45" alt="pip install vibe-trading-ai"></a>
</p>

---

## 📰 News

- **2026-06-12** 🩺 **Provider reliability overhaul — DeepSeek hangs, Kimi access, streaming liveness**: A cluster of provider reports — DeepSeek runs stuck on "Agent is working…" ([#208](https://github.com/HKUDS/Vibe-Trading/issues/208), thanks @XYWOX), `reached max iterations` masking empty model responses ([#203](https://github.com/HKUDS/Vibe-Trading/issues/203), thanks @mojianliang), the UI never recovering after a stall ([#195](https://github.com/HKUDS/Vibe-Trading/issues/195), thanks @mafia23), and Kimi rejecting the client ([#204](https://github.com/HKUDS/Vibe-Trading/issues/204), thanks @liao497) — shared one root: every OpenAI-compatible provider ran through a single shim that applied DeepSeek/Kimi/Gemini quirks globally and silently swallowed stream failures. Provider-specific behavior now lives in an explicit **capability layer** — reasoning capture/replay, Gemini thought signatures, the Kimi `User-Agent`, OpenRouter's reasoning body are each gated to their own provider instead of cross-contaminating. Reasoning-only streams show a live **"Reasoning…"** indicator instead of dead air; a stream failure raises a contextual `provider_stream_error` with one automatic retry for transient resets (deterministic 4xx fail fast) instead of silently falling back to a slow non-streaming call; an empty model response is reported as `empty_model_response` instead of "max iterations"; SSE heartbeats no longer break reconnect replay; and a stuck read-only tool times out instead of hiding behind heartbeats forever. A new **`vibe-trading provider doctor`** prints a redacted provider/model/package/proxy snapshot for one-command triage of environment-side hangs. DeepSeek users can opt into the official native adapter with `pip install "vibe-trading-ai[deepseek]"`, and kimi-k2.x's `temperature=1` requirement is applied automatically — the Kimi path is verified end-to-end against the live API (tool calls + strict multi-turn reasoning replay on `kimi-k2.6`).
- **2026-06-11** 🐝 **Swarm workers now pull market data through the loader layer**: An investment-committee run on NVDA exposed a chain of gaps — workers wrote ad-hoc yfinance scripts, trusted a malformed latest bar (volume present, OHLC empty), leaked `NaN` into non-strict JSON, and a context-free continuation prompt re-routed to the wrong preset ([#198](https://github.com/HKUDS/Vibe-Trading/issues/198), thanks @BillDin for an exceptional diagnosis plus both fixes). Swarm workers now get a local `get_market_data` tool backed by the same normalized loader registry as MCP — strict JSON, non-finite floats serialize as `null` — wired into **every market-data preset** (21 workers across 13 presets) with a prompt policy that steers OHLCV work tool-first ([#199](https://github.com/HKUDS/Vibe-Trading/pull/199)); `run_swarm` takes an explicit `preset_name` and refuses ambiguous continuation fragments instead of silently falling back to `equity_research_team` ([#200](https://github.com/HKUDS/Vibe-Trading/pull/200)). Grounding got smarter too: a bare US ticker like `NVDA` in a swarm prompt is promoted to `NVDA.US` (stopword-guarded), so workers start from authoritative pre-fetched prices. The tool joins the main agent registry as well — **48 tools** now. Also: **your Docker data now survives updates** — persistent memory, the session search index, user-created skills, shadow accounts and broker config live in named volumes, so `docker compose up --build` no longer wipes them ([#197](https://github.com/HKUDS/Vibe-Trading/issues/197), thanks @FlyerJ).
- **2026-06-10** 🐳 **Docker reaches a host-side Ollama out of the box**: Inside the container `localhost` is the container itself, so the shipped `OLLAMA_BASE_URL=http://localhost:11434` failed the LLM preflight for every Dockerized Ollama setup. `docker-compose.yml` now defaults to `http://host.docker.internal:11434` (export `OLLAMA_BASE_URL` to point elsewhere) and adds the `host-gateway` `extra_hosts` mapping so the same file works on Linux as well as Docker Desktop ([#196](https://github.com/HKUDS/Vibe-Trading/pull/196), thanks @ShahNewazKhan).
<details>
<summary>Earlier news</summary>

- **2026-06-09** 🔑 **Clearer error when the Web UI is opened from another machine**: Reaching the chat from a non-loopback client (another machine, a VM host, a phone on your LAN) without `API_AUTH_KEY` set returned `403` on every sensitive endpoint — sending a message, listing sessions, live status — but the chat only showed a generic "Failed to send message, please retry." The send path now surfaces the real reason — *"Remote API access requires an API key. Add it in Settings, or run the backend on localhost for local-only use."* — and the README's web-UI setup spells out the localhost-vs-LAN rule plus the three fixes (browse via `localhost` on the same machine; set `API_AUTH_KEY` and enter it once in Settings; or `VIBE_TRADING_TRUST_DOCKER_LOOPBACK=1` for Docker Desktop's host gateway) ([#191](https://github.com/HKUDS/Vibe-Trading/issues/191), thanks @mafia23).
- **2026-06-08** 🔧 **Gemini 3.x multi-turn tool-calling fix**: This completes the Gemini 3.x thinking-model fix. The 6/05 round-trip ([#176](https://github.com/HKUDS/Vibe-Trading/pull/176)) only covered in-memory history, but the real agent loop replays history as OpenAI-format dicts where LangChain dropped the per-tool-call `thought_signature` before the request was built — so multi-turn tool calling still 400'd with `missing thought_signature`. It is now re-attached at the single `_convert_input` chokepoint both `invoke` and `stream` pass through (parallel calls, where only the first of N is signed, included) ([#184](https://github.com/HKUDS/Vibe-Trading/pull/184), thanks @ngoanpv).
- **2026-06-07** 🐝 **Live swarm status in the chat timeline**: When the agent launches a multi-agent swarm (investment committee, quant desk, risk committee, …), the chat now renders an inline **status card** that streams each worker's state — waiting / running / done / failed / blocked / retrying — in real time, the same per-agent visibility the standalone swarm dashboard already had. Runtime events are bridged into the session SSE stream without changing the existing `/swarm/runs` API, and a finished card rehydrates from the final `run_swarm` result on reconnect or history replay ([#188](https://github.com/HKUDS/Vibe-Trading/pull/188), thanks @BillDin). Preset routing also got sharper: an explicitly named preset (e.g. `investment_committee`, with or without underscores) now wins over keyword scoring, and the bare `IV` derivatives keyword no longer false-matches inside ordinary words like "g**iv**en" ([#189](https://github.com/HKUDS/Vibe-Trading/pull/189), thanks @BillDin).
- **2026-06-06** ⚖️ **Alpha compare — head-to-head across CLI, Web UI, REST & agent**: A new `alpha compare` benches a hand-picked shortlist of Alpha Zoo alphas against each other on a universe and period, then ranks them by IC mean/std, IR, IC-positive ratio or sample count — each with its gap to the leader. Unlike a full-zoo bench it evaluates **only the alphas you name** (a new `run_bench(only=…)` subset filter), so comparing three alphas no longer scores all 191 in their zoo. One shared core powers every surface: `vibe-trading alpha compare <id1> <id2> 
ai-agentalgorithmic-tradingbacktestingfintechllmmcpmulti-agentpythonquantitative-financetrading

Lo que la gente pregunta sobre Vibe-Trading

¿Qué es HKUDS/Vibe-Trading?

+

HKUDS/Vibe-Trading es subagents para el ecosistema de Claude AI. "Vibe-Trading: Your Personal Trading Agent" Tiene 12k estrellas en GitHub y se actualizó por última vez today.

¿Cómo se instala Vibe-Trading?

+

Puedes instalar Vibe-Trading clonando el repositorio (https://github.com/HKUDS/Vibe-Trading) o siguiendo las instrucciones del README en GitHub. ClaudeWave también te ofrece bloques de instalación rápida en esta misma página.

¿Es seguro usar HKUDS/Vibe-Trading?

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Nuestro agente de seguridad ha analizado HKUDS/Vibe-Trading y le ha asignado un Trust Score de 100/100 (tier: Verified). Revisa el desglose completo de comprobaciones superadas y flags en esta página.

¿Quién mantiene HKUDS/Vibe-Trading?

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HKUDS/Vibe-Trading es mantenido por HKUDS. La última actividad registrada en GitHub es de today, con 9 issues abiertos.

¿Hay alternativas a Vibe-Trading?

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Sí. En ClaudeWave puedes explorar subagents similares en /categories/agents, ordenados por popularidad o actividad reciente.

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