Assessing Climate Risks of a Large Credit Portfolio

This repository contains the code to reproduce the results of the paper An Efficient SSP-based Methodology for Assessing Climate Risks of a Large Credit Portfolio.

Installation

To set up the environment and install dependencies, follow these steps:

• Clone the repository and navigate to the project directory:

  git clone https://github.com/bloomberg/climate-credit-risk.git
  cd climate-credit-risk
  

• Create a virtual environment:

  python3 -m venv .venv
  

• Activate the virtual environment:

  source .venv/bin/activate
  

• Install the required dependencies:

  pip install .
  

After setting up the environment, you can run the scripts and notebooks in this repository to reproduce the results presented in the paper.

Repository Structure

The repository is organized as follows:

• firm.py: Contains the Firm class, which models a single firm's optimal carbon emission strategy.
• utils.py: Utility functions and constants used across the project.
• firm.ipynb: Notebook for single firm analysis.
• opt_emission_decomp.ipynb: Notebook for optimal emission decomposition for a specific firm, scenario, and sector.
• pca.ipynb: Notebook to investigate the PCA approximation.
• portfolio.ipynb: Notebook to analyze and visualize the climate risks of a credit portfolio.
• rhs_l1_error.ipynb: Notebook to study the L1 error between the PCA loss and the exact loss.

License

Distributed under the Apache-2.0 license. See LICENSE for more information.