This project is a part of the course "Introduction to Risk Modeling and Management" at ETH Zurich, D-MTEC. The project is developed and maintained by Alex Makassiouk, Viktor Rasmussen, and Alexander Hansson.
The project focuses on risk modeling, with the first potential model residing in the cascading-processes folder and the systemic-risk.ipynb file. These files contain the core logic and models that drive the risk analysis aspects of the project.
The cascading-processes folder contains the necessary files and scripts to simulate and analyze cascading processes in risk modeling. It is a crucial part of the project as it forms the basis of our risk analysis.
The systemic-risk.ipynb file is a Jupyter notebook that contains the implementation of systemic risk models. It is used to visualize and understand the systemic risks involved in the scenarios we are studying. The backend models used in this notebook are in model.py and agent.py as explained below
model.py The model.py file contains the main risk model used in the project. It defines the structure of the model, including the parameters and variables, and the relationships between them. It also includes the logic for simulating the model over time.
agent.py The agent.py file defines the agents in the model. Each agent represents an entity that can be affected by risk and can affect the risk of other entities. The file includes the definition of the agent's properties and the logic for the agent's behavior.
To get started with the project, clone the repository and navigate to the cascading-processes folder. Open the systemic-risk.ipynb file in a Jupyter notebook to view the systemic risk models and visualizations, and to see the necessary steps to get started with the model.
We welcome contributions to the project. If you have any questions or suggestions, please feel free to reach out to us.
This project is licensed under the MIT License. See the LICENSE file for more details.