Vibe-Trading is a natural-language finance research AI agent designed to assist with trading and investment analysis.
Source: README View on GitHub →Vibe-Trading is gaining attention due to its comprehensive trading capabilities, natural language processing for finance, and active development with regular feature updates. It addresses the pain points of traditional trading by providing a more accessible and efficient way to conduct research and backtesting. The project stands out for its integration of various financial data sources and its focus on community contributions and collaboration.
Source: Synthesis of README and project traitsThe Alpha Zoo provides a collection of pre-built quantitative alphas across different financial markets, allowing users to benchmark and test strategies easily. It includes various alphas from different sources and supports one-line CLI commands for benching any zoo on a specific universe.
Source: READMEThe Research Spine includes a Hypothesis Registry for managing research hypotheses, and supports external-content readers with security warnings. It also features deterministic OHLCV feature evaluation for Shadow Account scanning.
Source: READMEVibe-Trading offers robust backtesting capabilities, emitting `run_card.json` and `run_card.md` alongside artifacts for reproducible research runs. It supports various financial markets and time periods for backtesting.
Source: READMEThe architecture of Vibe-Trading is modular, with a clear separation of concerns. It features a backend using FastAPI and a frontend with React. The codebase is organized into modules such as `agent`, `backtest`, and `mcp_server`. Key technical decisions include the use of Docker for containerization and the integration of various financial data sources.
Source: Code tree + dependency filesCenter: project; inner ring: core feature modules; outer ring: key dependencies. Auto-generated from core_features and tech_stack.key_deps.
richpyyamllangchainpandasfastapiuvicornpydanticVibe-Trading is suitable for financial analysts, traders, and researchers who need to conduct natural language processing on financial data, perform backtesting of trading strategies, and manage research hypotheses. It is useful for scenarios such as financial market analysis, investment strategy development, and quantitative trading.
Source: READMEv0.1.8 (2026-05-17): Alpha Zoo v1 (452 alphas across 4 zoos)
Source: GitHub ReleasesVibe-Trading is a promising open-source project for those interested in combining natural language processing with financial trading. Its comprehensive features and active development make it worth watching, especially for individuals and teams involved in financial research and quantitative trading.
Vibe-Trading is a natural-language finance research AI agent designed to assist with trading and investment analysis.
Vibe-Trading's core features include: Alpha Zoo, Research Spine, Backtesting.
Vibe-Trading is gaining attention due to its comprehensive trading capabilities, natural language processing for finance, and active development with regular feature updates.
Vibe-Trading is suitable for financial analysts, traders, and researchers who need to conduct natural language processing on financial data, perform backtesting of trading strategies, and manage research hypotheses.