bibtype J - Journal Article
ARLID 0385822
utime 20240103201808.2
mtime 20130111235959.9
WOS 000287979900026
title (primary) (eng) Modeling a Distribution of Mortgage Credit Losses
specification
page_count 19 s.
serial
ARLID cav_un_epca*0250419
ISSN 0013-3035
title Ekonomický časopis
volume_id 60
volume 10 (2012)
page_num 1005-1023
publisher
name Ekonomický ústav SAV
keyword credit risk
keyword mortgage
keyword delinquency rate
keyword generalized hyperbolic distribution
keyword normal distribution
author (primary)
ARLID cav_un_auth*0264433
name1 Gapko
name2 Petr
full_dept (cz) Ekonometrie
full_dept (eng) Department of Econometrics
department (cz) E
department (eng) E
institution UTIA-B
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
author
ARLID cav_un_auth*0101206
name1 Šmíd
name2 Martin
full_dept (cz) Ekonometrie
full_dept Department of Econometrics
department (cz) E
department E
institution UTIA-B
full_dept Department of Econometrics
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
source
url http://library.utia.cas.cz/separaty/2013/E/smid-modeling a distribution of mortgage credit losses.pdf
cas_special
project
project_id 46108
agency Univerzita Karlova
country CZ
project
project_id GD402/09/H045
agency GA ČR
ARLID cav_un_auth*0253998
project
project_id GBP402/12/G097
agency GA ČR
country CZ
ARLID cav_un_auth*0281000
research CEZ:AV0Z10750506
abstract (eng) In our paper, we focus on the credit risk quantification methodology. We demonstrate that the current regulatory standards for credit risk management are at least not perfect. Generalizing the well-known KMV model, standing behind Basel II, we build a model of a loan portfolio involving a dynamics of the com- mon factor, influencing the borrowers’ assets, which we allow to be non-normal. We show how the parameters of our model may be estimated by means of past mortgage delinquency rates. We give statistical evidence that the non-normal model is much more suitable than the one which assumes the normal distribution of risk factors. We point out in what way the assumption that risk factors follow a normal distribution can be dangerous. Especially during volatile periods compa- rable to the current crisis, the normal-distribution-based methodology can under- estimate the impact of changes in tail losses caused by underlying risk factors.
reportyear 2013
RIV AH
num_of_auth 2
inst_support RVO:67985556
permalink http://hdl.handle.net/11104/0216180
mrcbT16-e ECONOMICS
mrcbT16-j 0.04
mrcbT16-q 7
mrcbT16-s 0.231
mrcbT16-y 26.6
mrcbT16-x 0.15
mrcbT16-4 Q3
mrcbT16-B 2.405
mrcbT16-C 8.559
mrcbT16-D Q4
mrcbT16-E Q3
arlyear 2012
mrcbU34 000287979900026 WOS
mrcbU63 cav_un_epca*0250419 Ekonomický časopis 0013-3035 0013-3035 Roč. 60 č. 10 2012 1005 1023 Ekonomický ústav SAV