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GenParkQuantTriangularArbitrageBellmanFordDetector

GenParkQuantTriangularArbitrageBellmanFordDetector

Official
by alphaparkinc
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

genpark-quant-triangular-arbitrage-bellman-ford-detector-skill

Organization Model Context Protocol Zero-Dependency Python Version Domain License

Production-grade Quantitative Finance & DeFi Microstructure skill engineered strictly with Python standard library. Provides real-time concentrated liquidity optimization, L2 orderbook imbalance metrics, negative-cycle triangular arbitrage detection, and Bayesian Black-Litterman portfolio rebalancing via the Model Context Protocol (MCP).

Architecture & Data Flow

flowchart TD
    MarketFeed[L2 Tick / Orderbook / Exchange Rate Matrix / Covariance] --> Normalizer[Data Normalizer]
    Normalizer --> Core["GenParkQuantTriangularArbitrageBellmanFordDetector"]
    Core --> Analytics[Microstructure & Optimization Engine]
    Analytics --> RiskGuard[Slippage & Drawdown Constraints]
    RiskGuard --> MCPOutput[Standard MCP Tool Result / Execution Vector]

Related MCP server: quant-mcp

Quickstart & Usage

1. Direct Python Client Execution

python example_usage.py

2. Standalone MCP Server Launch

Run the native STDIO MCP server:

python mcp_server.py

License

This project is licensed under the MIT License - see the LICENSE file for details.

This server cannot be deployed

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Resources

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