1.

Record Nr.

UNINA9910788699403321

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

1-4623-3062-2

1-4527-6224-4

1-283-51662-4

9786613829078

1-4519-0996-9

Descrizione fisica

1 online resource (52 p.)

Collana

IMF Working Papers

Soggetti

Risk

Bank investments

Bank loans

Bank capital

Banks and Banking

Finance: General

Financial Risk Management

Industries: Financial Services

Money and Monetary Policy

Mathematical Methods

Econometric and Statistical Methods: Other

Model Evaluation and Selection

Optimization Techniques

Programming Models

Dynamic Analysis

Business Fluctuations

Cycles

Banks

Depository Institutions

Micro Finance Institutions

Mortgages

Financing Policy

Financial Risk and Risk Management

Capital and Ownership Structure

Value of Firms



Goodwill

International Financial Markets

Financial Institutions and Services: Government Policy and Regulation

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

Finance

Financial services law & regulation

Banking

Monetary economics

Credit risk

Loans

Asset valuation

Stress testing

Financial regulation and supervision

Financial institutions

Financial sector policy and analysis

Asset and liability management

Credit

Money

Financial risk management

Asset-liability management

Banks and banking

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.