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A data-driven econo-financial stress-testing framework to estimate the effect of supply chain networks on financial systemic risk
András Borsos / Christian Diem / Jan Fialkowski / Stefan Thurner
contagion / credit riskResource overview

A data-driven econo-financial stress-testing framework to estimate the effect of supply chain networks on financial systemic risk

Paper2025

by András Borsos, Christian Diem, Jan Fialkowski, Stefan Thurner

Tags
contagioncredit riskfinancial networksfinancial stabilitystress testingsystemic risk

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Suggested foundations for risk measurement and stress and credit and counterparty risk. Specialist prerequisites vary by paper.

Before you read

  1. Random Variables and Distributions

    Represent losses as a distribution rather than one forecast.

  2. Expected Shortfall and Other Tail Risk Measures

    Distinguish a loss quantile from the average loss in the tail.

  3. Credit Instruments, PD/LGD/EAD, and Rating Migration

    Separate default probability, loss severity and exposure.

  4. Conditional Expectation

    Read conditional default and exposure quantities.

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  1. VaR Estimation in Practice: Variance-Covariance, Historical Simulation, Monte Carlo

    Compare risk estimators and their assumptions.

  2. Backtesting VaR and ES: Coverage Tests and Model Validation

    Check forecasts against realised losses.

  3. Threshold Models and the Gaussian Copula for Portfolio Default

    Study dependence between defaults.

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