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Qbot

AI-assisted quantitative investment research platform for backtesting and trading strategies.

GitHub Download qbot-pro_v1.2.1
Stars
18.8k
Forks
2.6k
Licence
MIT
Language
Jupyter Notebook
Last update
8 months ago
Type
App

What it is

Qbot is an open-source platform for building and testing automated stock, fund, futures, or crypto trading strategies. It covers data, strategy development, backtesting, simulated trading, and, according to the README, live trading. It emphasizes machine learning and reinforcement learning strategies combined with multi-factor models.

  • Backtest a trading strategy against historical data
  • Develop machine learning or reinforcement learning trading strategies
  • Run simulated trades to check a strategy before using real money
  • Analyze and mine multi-factor signals for stock or fund selection

Great for

  • Python users who want to research quantitative trading strategies
  • People experimenting with machine learning models for market prediction
  • Students learning backtesting on historical market data
  • Individual investors comfortable with some programming and trading basics

Not ideal for

  • Anyone wanting a turnkey, no-code trading product, since the README says some Python knowledge is needed
  • Users who need a guaranteed profitable strategy; the README makes no performance claims and live trading carries financial risk
  • Users on Python versions other than 3.8 or 3.9, since the README says only those were tested
Step-by-step guide: how to use QbotInstall, first run, examples, tips and FAQs
Qbot alternativesdaily_stock_analysis vs QbotQbot vs QlibQbot vs VeighNa

How to get it

  1. 1

    Clone and build from source

    You'll need: Python 3.8 or 3.9

    Clone the repository

    git clone https://github.com/UFund-Me/Qbot --depth 1

    Install dependencies

    pip install -r dev/requirements.txt

    Set PYTHONPATH and run (Linux/Windows shell)

    export PYTHONPATH=${PYTHONPATH}:$(pwd):$(pwd)/backend/multi-fact/mfm_learner && python main.py
  2. 2

    Run it

    • Clone the repository and change into the Qbot folder
    • Install the Python dependencies from dev/requirements.txt
    • Set PYTHONPATH as shown in the README
    • Run main.py; on Mac the README suggests pythonw main.py
    • Read docs/Install_guide.md for further setup details
  3. 3

    Get the most out of it

    • Read the online docs at https://ufund-me.github.io/Qbot for setup and usage
    • Review the backtesting and factor-mining examples shown in the README highlights
    • Explore the supported trading targets: stocks, funds, futures, and cryptocurrencies
    • Check the project's DeepWiki page for an interactive overview of the codebase

Downloads

Source code (.zip)main branch · straight from GitHubRelease qbot-pro_v1.2.15 files incl. qinvestool_darwin_amd64_v1.3.6Official website & docsgithub.com/Charmve

Strengths

  • Covers the full workflow from data to backtesting to simulated and live trading in one project
  • Supports several machine learning paradigms, including supervised learning and reinforcement learning
  • Released under the MIT license, so it is free to use and modify

Trade-offs

  • The README states it was only tested on Python 3.8 and 3.9 and documentation is partly in Chinese
  • Live trading and financial decisions carry risk, and the README does not document results or accuracy
  • Setup depends on several third-party libraries, so installation may be complicated for beginners

How it compares

ProjectStarsTypeLevelUpdatedBest for
Qbot (this)18.8kAppadvanced8 months agoPython users who want to research quantitative trading strategies
qlib49.9kLibraryadvanced7 days agoQuant researchers who want a structured ML workflow for stock data
vnpy46.2kFrameworkadvanced10 days agoPython developers who want to build custom quant trading systems
daily_stock_analysis67.4kAppintermediate5 days agoIndividual investors who follow a personal watchlist of A-shares, HK, US, or other listed stocks and want a daily summary
Vane38kAppintermediate2 months agoPeople who want AI-written answers with links to sources
Vibe-Trading37.4kAI model / agentintermediate5 days agoDevelopers who want an AI agent for quantitative trading research

Stats synced from GitHub. The assessment above was drafted with AI from the project's README on 2026-10-29 and may miss recent changes — check the README before relying on a command. MIT licence: free to use, modify and distribute, including commercially, as long as you keep the copyright notice.