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Paper / 2024SMQ / 83465000826822
Quantitative technologies and reflexivity: The role of tools and their layouts in the case of credit risk management
Céline Baud / Nathalie Lallemand-Stempak
credit risk / risk managementResource overview

Quantitative technologies and reflexivity: The role of tools and their layouts in the case of credit risk management

Paper2024

by Céline Baud, Nathalie Lallemand-Stempak

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credit riskrisk management

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Understand this paper

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

Before you read

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

    Separate default probability, loss severity and exposure.

  2. Conditional Expectation

    Read conditional default and exposure quantities.

  3. Random Variables and Distributions

    Represent losses as a distribution rather than one forecast.

  4. Expected Shortfall and Other Tail Risk Measures

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

Go further

  1. Threshold Models and the Gaussian Copula for Portfolio Default

    Study dependence between defaults.

  2. CVA and DVA

    Connect exposure and counterparty losses to valuation adjustments.

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

    Compare risk estimators and their assumptions.

Explore a related reading path

Lesson links open public previews. Access to full lessons depends on the topic and your membership.

Explore Counterparty Credit Risk and CVA Explore Quantitative Risk Management

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