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

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 credi...

Descrizione completa

Dettagli Bibliografici
Autore principale: Segoviano, Miguel
Natura: Periodico
Lingua:English
Pubblicazione: Washington, D.C. : International Monetary Fund, 2006.
Serie:IMF Working Papers; Working Paper ; No. 2006/283
Accesso online:Full text available on IMF
LEADER 02204cas a2200241 a 4500
001 AALejournalIMF004587
008 230101c9999 xx r poo 0 0eng d
020 |c 5.00 USD 
020 |z 9781451865431 
022 |a 1018-5941 
040 |a BD-DhAAL  |c BD-DhAAL 
100 1 |a Segoviano, Miguel. 
245 1 0 |a Portfolio Credit Risk and Macroeconomic Shocks :   |b Applications to Stress Testing Under Data-Restricted Environments /  |c Miguel Segoviano. 
264 1 |a Washington, D.C. :  |b International Monetary Fund,  |c 2006. 
300 |a 1 online resource (50 pages) 
490 1 |a IMF Working Papers 
500 |a <strong>Off-Campus Access:</strong> No User ID or Password Required 
500 |a <strong>On-Campus Access:</strong> No User ID or Password Required 
506 |a Electronic access restricted to authorized BRAC University faculty, staff and students 
520 3 |a 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. 
538 |a Mode of access: Internet 
830 0 |a IMF Working Papers; Working Paper ;  |v No. 2006/283 
856 4 0 |z Full text available on IMF  |u http://elibrary.imf.org/view/journals/001/2006/283/001.2006.issue-283-en.xml  |z IMF e-Library