{
  "title": "Portfolio Credit Risk and Macroeconomic Shocks: Applications to Stress Testing Under Data-Restricted Environments",
  "publication": "IMF Working Papers, December 1, 2006",
  "sourceUrl": "https://www.imf.org/en/publications/wp/issues/2016/12/31/portfolio-credit-risk-and-macroeconomic-shocks-applications-to-stress-testing-under-data-20064",
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  "summary": "Portfolio credit risk measurement is greatly affected by data constraints, especially when focusing on loans given to unlisted firms.",
  "sections": [
    {
      "heading": "Summary and purpose",
      "content": "- Portfolio credit risk measurement is greatly affected by data constraints, especially for loans to unlisted firms.\n- Standard methodologies often adopt convenient, but not necessarily properly specified parametric distributions or ignore the effects of macroeconomic shocks on credit risk.\n- The paper proposes the joint implementation of two methodologies designed to improve portfolio credit risk measurement under data restrictions: the conditional probability of default (CoPoD) methodology and the consistent information multivariate density optimizing (CIMDO) methodology.\n- Implementation is presented as straightforward and particularly useful in stress testing exercises (STEs), illustrated by an STE carried out within the Danish Financial Sector Assessment Program."
    },
    {
      "heading": "Methodologies proposed",
      "content": "- Conditional Probability of Default (CoPoD)\n  - Incorporates the effects of macroeconomic shocks into credit risk.\n  - Recovers robust estimators when only short time series of loans exist.\n- Consistent Information Multivariate Density Optimizing (CIMDO)\n  - Recovers portfolio multivariate distributions on which portfolio credit risk measurement relies.\n  - Provides improved specifications when only partial information about borrowers is available."
    },
    {
      "heading": "Key findings and analytical contributions",
      "content": "- Data constraints materially affect measurement of portfolio credit risk; commonly used parametric assumptions may be misspecified.\n- Incorporating macroeconomic shocks via CoPoD leads to more robust default probability estimation in short time-series environments.\n- Recovering multivariate portfolio distributions with CIMDO improves the specification of loss distributions when borrower-level information is incomplete.\n- The joint use of CoPoD and CIMDO enhances the reliability of stress testing under data-restricted environments."
    },
    {
      "heading": "Applications and examples",
      "content": "- The methodologies are illustrated through their application in a stress testing exercise within the Danish Financial Sector Assessment Program (Denmark and the IMF context noted).\n- Implementation is described as straightforward for STE practitioners facing partial borrower information and short loan time series."
    },
    {
      "heading": "Subject coverage and keywords",
      "content": "- Subjects: Asset and liability management; Asset valuation; Banking; Credit; Credit risk; Financial institutions; Financial regulation and supervision; Financial sector policy and analysis; Loans; Money; Stress testing.\n- Keywords: Asset valuation; bank portfolio UL; capital adequacy ratio; concentration effect; Credit; credit portfolio; Credit risk; credit risk modeling; credit risk quality; economic theory; entropy distribution; Europe; importance of portfolio credit risk; loan default; loan portfolio; Loans; loss distribution; macroeconomic shock measurement; multivariate density estimation; multivariate distribution; portfolio credit risk; Portfolio credit risk measurement; stress testing; time series; WP.\n\n---\n\n Content in this bundle\n\n- wp06283\n  - wp06283 (Markdown version){rel=\"alternate\" type=\"text/markdown\"}\n  - wp06283 (PDF){rel=\"external\" type=\"application/pdf\"}\n\n---\n\nSource: https://www.imf.org/en/publications/wp/issues/2016/12/31/portfolio-credit-risk-and-macroeconomic-shocks-applications-to-stress-testing-under-data-20064"
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    "Authors: Miguel A. Segoviano",
    "Published: December 1, 2006",
    "Series: IMF Working Papers",
    "DOI: https://doi.org/10.5089/9781451865431.001",
    "Portfolio credit risk measurement is greatly affected by data constraints, especially for loans to unlisted firms.",
    "Standard methodologies often adopt convenient, but not necessarily properly specified parametric distributions or ignore the effects of macroeconomic shocks on credit risk.",
    "The paper proposes the joint implementation of two methodologies designed to improve portfolio credit risk measurement under data restrictions: the conditional probability of default (CoPoD) methodology and the consistent information multivariate density optimizing (CIMDO) methodology.",
    "Implementation is presented as straightforward and particularly useful in stress testing exercises (STEs), illustrated by an STE carried out within the Danish Financial Sector Assessment Program.",
    "Conditional Probability of Default (CoPoD)",
    "Consistent Information Multivariate Density Optimizing (CIMDO)",
    "Data constraints materially affect measurement of portfolio credit risk; commonly used parametric assumptions may be misspecified.",
    "Incorporating macroeconomic shocks via CoPoD leads to more robust default probability estimation in short time-series environments.",
    "Recovering multivariate portfolio distributions with CIMDO improves the specification of loss distributions when borrower-level information is incomplete.",
    "The joint use of CoPoD and CIMDO enhances the reliability of stress testing under data-restricted environments.",
    "The methodologies are illustrated through their application in a stress testing exercise within the Danish Financial Sector Assessment Program (Denmark and the IMF context noted).",
    "Implementation is described as straightforward for STE practitioners facing partial borrower information and short loan time series.",
    "Subjects: Asset and liability management; Asset valuation; Banking; Credit; Credit risk; Financial institutions; Financial regulation and supervision; Financial sector policy and analysis; Loans; Money; Stress testing.",
    "Keywords: Asset valuation; bank portfolio UL; capital adequacy ratio; concentration effect; Credit; credit portfolio; Credit risk; credit risk modeling; credit risk quality; economic theory; entropy distribution; Europe; importance of portfolio credit risk; loan default; loan portfolio; Loans; loss distribution; macroeconomic shock measurement; multivariate density estimation; multivariate distribution; portfolio credit risk; Portfolio credit risk measurement; stress testing; time series; WP.",
    "**_wp06283**"
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