# DemonDamon/FinnewsHunter

FinnewsHunter: Multi-agent financial intelligence platform powered by AgenticX. Real-time news analysis, sentiment fusion, and alpha factor mining.

Repository: https://github.com/DemonDamon/FinnewsHunter
Canonical: https://ross.abutalabs.com/products/finnewshunter
Language: Python
License: Apache-2.0
License Family: permissive
Topics: agentic-ai, fintech, multi-agent, quant-finance, sentiment-analysis, alpha-signals
Last push: 2026-07-05T07:03:44+00:00

## Health v2 (maintenance only)
Score: 73/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 91, release rhythm 35, longevity 100
- inputs: {"age_days": 3111, "days_push": 59, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1487, forks 341 (observed 2026-08-28T04:04:52.027113+00:00)

## What it is
FinnewsHunter is a multi-agent financial intelligence platform built on the AgenticX framework that monitors Chinese financial news sources in real time, performs LLM-driven sentiment analysis and market impact assessment, and mines alpha signals for quantitative trading. It ships as a full-stack system with a React frontend, FastAPI gateway, PostgreSQL/Milvus/Redis storage, and Docker Compose deployment.

## Use cases
- analyze financial news sentiment for stock trading
- mine alpha factors from real-time news streams
- monitor Chinese financial news sources automatically
- assess market impact of breaking news with LLMs
- run multi-agent debate workflows for investment research
- combine news analysis with stock K-line data
- build a quant research news pipeline

## When to choose
- you need LLM-driven sentiment and impact analysis of Chinese financial news
- you want a production-ready, self-hosted multi-agent news analysis stack with Docker deployment
- you're building quant strategies that consume news-derived alpha signals
- you want multi-provider LLM support and vector search over news

## When to avoid
- you need coverage of non-Chinese financial news sources
- you want a lightweight library to embed in an existing pipeline rather than a full platform
- you have no LLM API access or budget for inference costs
- you need guaranteed-accurate trading signals - outputs are decision support, not advice

## Facets
- artifact type: application
- maturity: active
- function: agent-framework, nlp, machine-learning, rag, web-scraping, data-visualization, search-engine, vector-database, api-framework, chatbot
- domain: fintech, artificial-intelligence, data-science, analytics, large-language-models
- platform: python, self-hosted, cross-platform
- tags: fintech, quant-finance, sentiment-analysis, alpha-signals, multi-agent, news-analysis, agenticx, fastapi, milvus, react, ai-agents, natural-language-processing, docker, web-server

## Member repositories
- DemonDamon/FinnewsHunter (main) score 73

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:52.027113+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T04:33:47.101937+00:00, confidence not recorded.
  - readme: https://github.com/DemonDamon/FinnewsHunter (fetched 2026-08-28T04:04:52.027113+00:00, sha 1d6de1fdc7be)
- Data as of 2026-08-30T08:39:29.467469+00:00.