1.

Record Nr.

UNINA9910972470803321

Autore

Segoviano Miguel

Titolo

Portfolio Credit Risk and Macroeconomic Shocks : : Applications to Stress Testing Under Data-Restricted Environments / / Miguel Segoviano

Pubbl/distr/stampa

Washington, D.C. : , : International Monetary Fund, , 2006

ISBN

9786613829078

9781462330621

1462330622

9781452762241

1452762244

9781283516624

1283516624

9781451909968

1451909969

Edizione

[1st ed.]

Descrizione fisica

1 online resource (52 p.)

Collana

IMF Working Papers

Soggetti

Risk

Bank investments

Bank loans

Bank capital

Asset and liability management

Asset valuation

Asset-liability management

Banking

Banks and Banking

Banks and banking

Banks

Business Fluctuations

Capital and Ownership Structure

Credit risk

Credit

Cycles

Depository Institutions

Dynamic Analysis

Econometric and Statistical Methods: Other

Finance

Finance: General



Financial Institutions and Services: Government Policy and Regulation

Financial institutions

Financial regulation and supervision

Financial Risk and Risk Management

Financial Risk Management

Financial risk management

Financial sector policy and analysis

Financial services law & regulation

Financing Policy

Goodwill

Industries: Financial Services

International Financial Markets

Loans

Mathematical Methods

Micro Finance Institutions

Model Evaluation and Selection

Monetary economics

Monetary Policy, Central Banking, and the Supply of Money and Credit: General

Money and Monetary Policy

Money

Mortgages

Optimization Techniques

Programming Models

Stress testing

Value of Firms

Denmark

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

"December 2006."

Nota di bibliografia

Includes bibliographical references (p. 45-50).

Nota di contenuto

""Contents""; ""I. INTRODUCTION""; ""II. PORTFOLIO CREDIT RISK""; ""III. PROPOSAL TO IMPROVE PORTFOLIO CREDIT RISK MEASUREMENT""; ""IV. PROPOSED PROCEDURE FOR STRESS TESTING""; ""V. STRESS TESTING: EMPIRICAL IMPLEMENTATION IN DENMARK""; ""VI. ANALYSIS OF STRESS TESTING RESULTS""; ""VII. CONCLUSIONS""; ""Appendix 1: Entropy in a Nutshell""; ""References""

Sommario/riassunto

Portfolio credit risk measurement is greatly affected by data constraints, especially when focusing on loans given to unlisted firms. Standard methodologies adopt convenient, but not necessarily properly specified parametric distributions or simply ignore the effects of macroeconomic shocks on credit risk. Aiming to improve the measurement of portfolio credit risk, we propose the joint implementation of two new methodologies, namely the conditional probability of default (CoPoD) methodology and the consistent information multivariate density optimizing (CIMDO) methodology. CoPoD incorporates the effects of macroeconomic shocks into credit risk, recovering robust estimators when only short time series of loans



exist. CIMDO recovers portfolio multivariate distributions (on which portfolio credit risk measurement relies) with improved specifications, when only partial information about borrowers is available. Implementation is straightforward and can be very useful in stress testing exercises (STEs), as illustrated by the STE carried out within the Danish Financial Sector Assessment Program.