📈 QuantClaw Data

The open financial intelligence platform. 42 modules built, 93 planned, 100+ CLI commands, REST API, MCP-ready.

Built autonomously by AI agents. 5 modules built in parallel every ~7 minutes. Self-evolving roadmap.

🌐 Live: data.quantclaw.org 📖 CLI Reference: data.quantclaw.org/#install

📦 Install via ClawHub (for OpenClaw agents)

clawhub install quantclaw-data

Or manually:

⚡ Quick Start

# Clone
git clone https://github.com/yoniassia/quantclaw-data.git
cd quantclaw-data

# Install dependencies
pip install yfinance numpy scipy pandas statsmodels pandas-datareader requests beautifulsoup4

# Try it
python cli.py price AAPL
python cli.py technicals TSLA
python cli.py fama-french NVDA
python cli.py monte-carlo SPY --simulations 10000 --days 252

🧠 What Is This?

QuantClaw Data is a comprehensive financial data platform that gives you Bloomberg Terminal-level capabilities through a simple CLI and REST API — powered entirely by free data sources.

It covers:

• Real-time prices for stocks, crypto, commodities, forex
• Quantitative models — Fama-French, Black-Litterman, Monte Carlo, Kalman Filter
• Options analytics — Greeks, GEX, pin risk, flow analysis
• Alternative data — Congressional trades, social sentiment, patent filings, satellite proxies
• Fixed income — Yield curves, credit spreads, CDS estimates
• Smart alerts — Custom DSL for complex multi-condition rules
• SEC filings — NLP analysis, earnings transcripts, 13F replication

All free. No API keys required for core functionality.

📊 Module Status

✅ Built Modules (42/93)

Foundation (Phases 1-4)

Intelligence (Phases 5-10)

Advanced Analytics (Phases 11-27)

Quantitative Models (Phases 28-42)

🖥️ CLI Commands

Market Data

python cli.py price AAPL                          # Real-time price
python cli.py price AAPL --history 30d             # Historical
python cli.py crypto bitcoin                       # Crypto
python cli.py commodity gold                       # Commodities
python cli.py forex EUR/USD                        # Forex

Technical Analysis

python cli.py technicals AAPL                      # Full TA (RSI, MACD, SMA)
python cli.py mtf AAPL                             # Multi-timeframe
python cli.py kalman SPY                           # Kalman filter trend
python cli.py regime-detect TSLA                   # Market regime
python cli.py support-resistance AAPL              # Volume-based S/R

Options

python cli.py options AAPL                         # Options chain + Greeks
python cli.py gex SPY                              # Gamma exposure
python cli.py pin-risk AAPL                        # Pin risk analysis
python cli.py options-flow --unusual               # Unusual activity

Quantitative Models

python cli.py fama-french AAPL                     # Factor regression
python cli.py monte-carlo AAPL --simulations 10000 # Monte Carlo
python cli.py var TSLA --confidence 0.95 0.99      # Value at Risk
python cli.py black-litterman --tickers AAPL,MSFT,GOOGL  # Portfolio optimization
python cli.py cointegration KO PEP                 # Pairs trading
python cli.py sector-rotation 60                   # Sector rotation signals
python cli.py walk-forward SPY --strategy sma-crossover  # Walk-forward test

Alternative Data

python cli.py congress AAPL                        # Congressional trades
python cli.py social GME --source reddit           # Social sentiment
python cli.py 13f 0001067983                       # Hedge fund holdings (Berkshire)
python cli.py smart-money AAPL                     # Institutional flow
python cli.py top-funds                            # Top hedge funds
python cli.py activists AAPL                       # Activist investors
python cli.py short-interest --squeeze             # Short squeeze candidates
python cli.py patents AAPL                         # Patent velocity

Smart Alerts

python cli.py alert-create AAPL --condition "price>200"  # Create alert
python cli.py alert-list                           # List active
python cli.py alert-check                          # Check against live data
python cli.py alert-backtest AAPL --condition "rsi<30" --period 1y  # Backtest
python cli.py dsl-eval AAPL "price > 200 AND rsi < 30"  # DSL expression
python cli.py dsl-scan "rsi < 25" --universe SP500      # Scan universe

Fixed Income & Macro

python cli.py bonds yield-curve                    # Treasury yield curve
python cli.py credit-spreads                       # HY/IG spreads
python cli.py sovereign-risk Italy                 # Sovereign CDS
python cli.py macro gdp                            # GDP data
python cli.py macro cpi --history 5y               # Inflation

🌐 REST API

Base URL: https://data.quantclaw.org/api/v1

# Gamma exposure
curl "https://data.quantclaw.org/api/v1/gex?symbol=SPY"

# Fama-French regression
curl "https://data.quantclaw.org/api/v1/fama-french?ticker=AAPL"

# Monte Carlo simulation
curl "https://data.quantclaw.org/api/v1/monte-carlo?action=simulate&symbol=AAPL&simulations=1000&days=30"

# Pairs trading
curl "https://data.quantclaw.org/api/v1/pairs?action=cointegration&symbol1=KO&symbol2=PEP"

# Alert DSL
curl "https://data.quantclaw.org/api/v1/alert-dsl?action=eval&ticker=AAPL&expression=price>200%20AND%20rsi<30"

# Credit spreads
curl "https://data.quantclaw.org/api/v1/cds?action=credit-spreads"

# Hedge fund 13F
curl "https://data.quantclaw.org/api/v1/13f?cik=0001067983"

All endpoints return JSON.

🤖 MCP Server (for AI Agents)

Add to your Claude Desktop or MCP client config:

{
  "mcpServers": {
    "quantclaw-data": {
      "command": "node",
      "args": ["mcp-server.js"],
      "cwd": "/path/to/quantclaw-data"
    }
  }
}

📡 Data Sources (All Free)

🗺️ Full Roadmap

✅ Done (42 phases)

Phases 1-42 — see module table above.

🔧 In Progress

📋 Planned (46 phases)

🏗️ How It's Built

This platform is built autonomously by AI agents:

1. 5 sub-agents run in parallel, each building one module (~5-7 min each)
2. Each agent reads existing patterns, creates Python module + CLI + API route
3. When a batch of 5 completes → deploy → launch next 5
4. At phase 80 → a research agent discovers new data sources
5. At phase 93 → pipeline self-terminates

Cost per module: ~$0.04 (Claude Sonnet) Total platform cost: ~$4 for all 93 modules Build time: ~2 hours for the full platform

📁 Project Structure

quantclaw-data/
├── cli.py                    # Main CLI dispatcher
├── modules/                  # Python modules (one per phase)
│   ├── alert_backtest.py
│   ├── alert_dsl.py
│   ├── black_litterman.py
│   ├── cds_spreads.py
│   ├── kalman_filter.py
│   ├── monte_carlo.py
│   ├── multi_timeframe.py
│   ├── order_book.py
│   ├── pairs_trading.py
│   ├── sector_rotation.py
│   ├── smart_alerts.py
│   └── walk_forward.py
├── src/app/
│   ├── page.tsx              # Dashboard UI
│   ├── services.ts           # Module registry
│   ├── roadmap.ts            # Full roadmap with status
│   ├── install.ts            # Install instructions & CLI reference
│   └── api/v1/               # REST API routes
├── package.json
└── README.md

🤝 Part of the MoneyClaw Ecosystem

• MoneyClaw — AI Trading Agents
• TerminalX — Bloomberg-style Terminal
• ClawX — AI Trading Assistant
• GoodWallet — DeFi + Predictions

📜 License

MIT — use it, fork it, build on it.

Built with 🦞 by QuantClaw — Autonomous Financial Intelligence