Global Systemic Risk Visualizer and Simulator (GSRVS) - v2.0

Overview

GSRVS is an enterprise-grade, open-source platform for simulating and visualizing financial contagion. Built with a modern tech stack, it provides a powerful, interactive environment for researchers, regulators, and financial professionals to conduct sophisticated systemic risk analysis.

Key Enhancements in v2.0

• Sophisticated Simulation Engine: Models multi-stage contagion, including credit losses, funding shocks, and asset fire sales.
• Interactive React Frontend: A dynamic and user-friendly interface for building scenarios, controlling simulations, and analyzing results.
• RESTful API Backend: A robust FastAPI backend serving data and handling complex calculations.
• Containerized with Docker: Get the entire application running with a single command.
• Advanced Visualization: Interactive network graphs and time-series dashboards to track key risk metrics.

Key Features

• Dynamic Network Visualization: Interactive graphs powered by React Flow.
• Shock Simulation Engine: Simulate defaults, liquidity shocks, and asset price crashes.
• Scenario Builder: Interactively design and save complex scenarios.
• Capital & Liquidity Modeling: Tracks regulatory capital (CET1) and liquidity buffers. -. Contagion Pathways Analyzer: Trace the exact pathways of shock propagation.
• Risk Dashboards: Real-time charts for capital shortfalls, defaulted assets, and more.

Getting Started

Prerequisites

• Docker and Docker Compose

Running the Project

This project is fully containerized. To get started, simply clone the repository and run Docker Compose.

1. Clone the repository:

   git clone [https://github.com/your-username/GSRVS.git](https://github.com/your-username/GSRVS.git)
   cd GSRVS

2. Build and run the containers:

   docker-compose up --build

3. Access the application:

   • Frontend UI: Open your browser to http://localhost:3000
   • Backend API Docs: Access the interactive API documentation at http://localhost:8000/docs

Project Architecture

• /api: The Python backend powered by FastAPI. It handles all data processing, simulation logic, and serves the REST API.
• /client: The React.js frontend. It provides the user interface for interacting with the simulation.
• /data: Contains sample data files for a quick start.

Usage

1. Load Data: The application loads the sample data by default.
2. Configure Scenario: Use the "Control Panel" on the left to define the initial shock (e.g., select an institution to default, or define a market-wide asset price drop).
3. Run Simulation: Click the "Run Simulation" button.
4. Analyze Results:
   • Observe the Network Graph as nodes change color to reflect their status (Healthy, Stressed, Defaulted).
   • Watch the Results Dashboard to see charts of key metrics evolving over the simulation rounds.

Contributing

We welcome contributions! Please see CONTRIBUTING.md for guidelines.

License

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