0xemmkty/QuantMuse

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

2900 stars · 602 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A Python-based quantitative trading system combining factor analysis, ML models, and LLM-powered market analysis with real-time market data streaming and risk management. It includes an extensible strategy framework, backtesting, portfolio optimization, and interactive dashboards.

Use cases

• build algorithmic trading strategies in python
• backtest quantitative trading strategies
• analyze market sentiment with llm
• stream real-time crypto market data
• optimize a portfolio with risk parity
• screen stocks using multi-factor models

When to choose

• you want an end-to-end quant pipeline from data ingestion to strategy execution
• you need AI/LLM-driven market analysis integrated with trading workflows
• you want built-in risk management and portfolio optimization
• you prefer a Python stack with dashboard visualization

When to avoid

• you need guaranteed low-latency HFT execution
• you require broker certification or regulatory compliance out of the box
• you want a fully managed cloud trading service rather than self-hosted software

Facets

application · maturity active

machine-learning nlp data-visualization streaming caching trading llm-inference rag fintech machine-learning data-science analytics python windows self-hosted quantitative-trading algorithmic-trading factor-models backtesting risk-management portfolio-optimization sentiment-analysis market-data binance streamlit-dashboard real-time linux macos docker

Member repositories

For agents

markdown · JSON · MCP: product_card(name="0xemmkty/QuantMuse")