# UFund-Me/Qbot

[🔥updating ...] AI 自动量化交易机器人(完全本地部署) AI-powered Quantitative Investment Research Platform. 📃 online docs: https://ufund-me.github.io/Qbot   ✨ :news: qbot-mini: https://github.com/Charmve/iQuant

Repository: https://github.com/UFund-Me/Qbot
Canonical: https://ross.abutalabs.com/products/qbot
Homepage: https://github.com/Charmve
Language: Jupyter Notebook
License: MIT
License Family: permissive
Topics: funds, machine-learning, pytrade, quantitative-finance, quantitative-trading, quantization, strategies, trademarks, quant-trade, quant-trader, bitcoin, blockchain, deep-learning, fintech, qlib, trade-bot, backtest
Last push: 2026-03-11T12:16:42+00:00

## Health v2 (maintenance only)
Score: 54/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 71, release rhythm 8, longevity 98
- inputs: {"age_days": 1380, "days_push": 175, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 18394, forks 2590 (observed 2026-08-28T04:11:26.629277+00:00)

## What it is
Qbot is an AI-powered automated quantitative investment and trading research platform that runs fully locally. It combines machine learning strategies, backtesting, and live trading support for funds, stocks, and crypto assets.

## Use cases
- backtest quantitative trading strategies on historical market data
- build AI/ML-driven trading strategies for funds and crypto
- run a fully local automated trading bot
- research quantitative investment ideas with Jupyter notebooks
- visualize portfolio performance and market analytics
- automate live trading with strategy scheduling

## When to choose
- you want an open-source, locally deployed quant research and trading platform in Python
- you need ML-based strategy development with backtesting built in
- you trade funds, stocks, or crypto and want automation

## When to avoid
- you need a battle-tested institutional-grade trading system with guaranteed reliability
- you want a no-code SaaS trading product
- you need guaranteed financial returns or regulatory compliance support

## Facets
- artifact type: application
- maturity: active
- function: machine-learning, trading, data-science, data-visualization, developer-tools
- domain: fintech, machine-learning, data-science
- platform: python, cross-platform
- tags: quantitative-trading, backtesting, trading-bot, fintech, qlib, strategy-research, local-deployment, cryptocurrency, automation, docker

## Member repositories
- UFund-Me/Qbot (main) score 54

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:11:26.629277+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 2026-08-29T17:02:03.411343+00:00, confidence not recorded.
  - readme: https://github.com/UFund-Me/Qbot (fetched 2026-08-28T04:11:26.629277+00:00, sha 54d603250218)
  - homepage: https://github.com/Charmve (fetched 2026-08-29T07:59:42.194608+00:00, sha 7d2f1962afd0)
- Data as of 2026-08-30T08:39:29.467469+00:00.