trisk.analysis

The goal of trisk.analysis is to provide a tool that can be used to conduct what-if climate stress test analyses for financial institutions, supervisors, regulators and other stakeholders. The tool aims at highlighting potential financial risk in especially climate relevant sectors, split by production technology where required. The core Trisk model source code is available in another package, already included in the installation of this one. Specific documentation and source code related links is available on trisk.model .

• trisk.analysis
  • Use the package
    • Installation
    • Input and output dataframes columns
    • Scenarios data
  • Analyses
    • Portfolio analysis
    • Sensitivity analysis
  • Funding

Use the package

Installation

You can install this package directly from GitHub using the pak package in R.

1. Install the pak package if you don’t have it:

   install.packages("pak")

2. Install the package from GitHub:

   pak::pak("Theia-Finance-Labs/trisk.analysis")

Input and output dataframes columns

There are 4 input datasets (assets, scenarios, financial_features, ngfs_carbon_prices), and 3 output datasets (npv_results, pd_results, company_trajectories). The Inputs and Outputs describes their columns structure with a simple Trisk run, and the definitions of Trisk input parameters.

Scenarios data

We provide consolidated scenarios data from publicly available sources. The Download Scenarios vignette showcases how to access this data and explore available scenarios.

Note Application of the code requires availability of custom data for assets and financial data. Those inputs need to be pre-processed independantly, following the structure of the mock datasets presented in the vignettes.

Analyses

An online version of those analyses is available on our apps portal https://apps.1in1000.com

Portfolio analysis

A wrapper function called run_trisk_on_portfolio() can be used to run Trisk on a subset of the input assets dataframe, based on companies that can be matched between the two. Along with PDs and NPVs computed in the model the function also returns the expected loss, computed using the loss given default provided in the input portfolio. Plots to visualize the results are included in the package. Example showcased in the Portfolio Analysis vignette.

Sensitivity analysis

A wrapper function called run_trisk_sa() is provided if you’d like to generate a set of Trisk runs with different parameters configurations. The results obtained can be plotted using functions included in the package, or integrated in your analysis pipeline. Example showcased in the Sensitivity Analysis vignette.

Funding

EU LIFE Project Grant

Co-funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or CINEA. Neither the European Union nor the granting authority can be held responsible for them.

Scientific Transition Risk Exercises for Stress tests & Scenario Analysis has received funding from the European Union’s Life programme under Grant No. LIFE21-GIC-DE-Stress under the LIFE-2021-SAP-CLIMA funding call.