On Loss Distributions from Installment-Repaid Loans
Abstract The banks have been accumulating huge data bases for many years and are increasingly turning to statistics to provide insight into customer behaviour, among other things. Credit risk is an important issue and certain stochastic models have been developed in recent years to describe and pred...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Crowder, Martin [verfasserIn] |
|---|
| Format: |
Artikel |
|---|---|
| Sprache: |
Englisch |
| Erschienen: |
2005 |
|---|
| Schlagwörter: |
|---|
| Anmerkung: |
© Springer Science+Business Media, Inc. 2005 |
|---|
| Übergeordnetes Werk: |
Enthalten in: Lifetime data analysis - Kluwer Academic Publishers, 1995, 11(2005), 4 vom: Dez., Seite 545-564 |
|---|---|
| Übergeordnetes Werk: |
volume:11 ; year:2005 ; number:4 ; month:12 ; pages:545-564 |
| Links: |
|---|
| DOI / URN: |
10.1007/s10985-005-5239-6 |
|---|
| Katalog-ID: |
OLC2067134280 |
|---|
| LEADER | 01000caa a22002652 4500 | ||
|---|---|---|---|
| 001 | OLC2067134280 | ||
| 003 | DE-627 | ||
| 005 | 20230503171424.0 | ||
| 007 | tu | ||
| 008 | 200820s2005 xx ||||| 00| ||eng c | ||
| 024 | 7 | |a 10.1007/s10985-005-5239-6 |2 doi | |
| 035 | |a (DE-627)OLC2067134280 | ||
| 035 | |a (DE-He213)s10985-005-5239-6-p | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 082 | 0 | 4 | |a 510 |a 004 |q VZ |
| 100 | 1 | |a Crowder, Martin |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a On Loss Distributions from Installment-Repaid Loans |
| 264 | 1 | |c 2005 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a ohne Hilfsmittel zu benutzen |b n |2 rdamedia | ||
| 338 | |a Band |b nc |2 rdacarrier | ||
| 500 | |a © Springer Science+Business Media, Inc. 2005 | ||
| 520 | |a Abstract The banks have been accumulating huge data bases for many years and are increasingly turning to statistics to provide insight into customer behaviour, among other things. Credit risk is an important issue and certain stochastic models have been developed in recent years to describe and predict loan default. Two of the major models currently used in the industry are considered here, and various ways of extending their application to the case where a loan is repaid in installments are explored. The aspect of interest is the probability distribution of the total loss due to repayment default at some time. Thus, the loss distribution is determined by the distribution of times to default, here regarded as a discrete-time survival distribution. In particular, the probabilities of large losses are to be assessed for insurance purposes. | ||
| 650 | 4 | |a credit risk | |
| 650 | 4 | |a default time | |
| 650 | 4 | |a discrete-time survival | |
| 650 | 4 | |a installment repayments | |
| 650 | 4 | |a loan lifetime | |
| 650 | 4 | |a loss distributions | |
| 650 | 4 | |a portfolio risk | |
| 650 | 4 | |a repayment failure time | |
| 700 | 1 | |a Hand, David J. |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t Lifetime data analysis |d Kluwer Academic Publishers, 1995 |g 11(2005), 4 vom: Dez., Seite 545-564 |w (DE-627)233193332 |w (DE-600)1393066-7 |w (DE-576)07005777X |x 1380-7870 |7 nnns |
| 773 | 1 | 8 | |g volume:11 |g year:2005 |g number:4 |g month:12 |g pages:545-564 |
| 856 | 4 | 1 | |u https://doi.org/10.1007/s10985-005-5239-6 |z lizenzpflichtig |3 Volltext |
| 912 | |a GBV_USEFLAG_A | ||
| 912 | |a SYSFLAG_A | ||
| 912 | |a GBV_OLC | ||
| 912 | |a SSG-OLC-MAT | ||
| 912 | |a SSG-OPC-MAT | ||
| 912 | |a GBV_ILN_70 | ||
| 912 | |a GBV_ILN_4305 | ||
| 951 | |a AR | ||
| 952 | |d 11 |j 2005 |e 4 |c 12 |h 545-564 | ||
| author_variant |
m c mc d j h dj djh |
|---|---|
| matchkey_str |
article:13807870:2005----::nositiuinfoisale |
| hierarchy_sort_str |
2005 |
| publishDate |
2005 |
| allfields |
10.1007/s10985-005-5239-6 doi (DE-627)OLC2067134280 (DE-He213)s10985-005-5239-6-p DE-627 ger DE-627 rakwb eng 510 004 VZ Crowder, Martin verfasserin aut On Loss Distributions from Installment-Repaid Loans 2005 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, Inc. 2005 Abstract The banks have been accumulating huge data bases for many years and are increasingly turning to statistics to provide insight into customer behaviour, among other things. Credit risk is an important issue and certain stochastic models have been developed in recent years to describe and predict loan default. Two of the major models currently used in the industry are considered here, and various ways of extending their application to the case where a loan is repaid in installments are explored. The aspect of interest is the probability distribution of the total loss due to repayment default at some time. Thus, the loss distribution is determined by the distribution of times to default, here regarded as a discrete-time survival distribution. In particular, the probabilities of large losses are to be assessed for insurance purposes. credit risk default time discrete-time survival installment repayments loan lifetime loss distributions portfolio risk repayment failure time Hand, David J. aut Enthalten in Lifetime data analysis Kluwer Academic Publishers, 1995 11(2005), 4 vom: Dez., Seite 545-564 (DE-627)233193332 (DE-600)1393066-7 (DE-576)07005777X 1380-7870 nnns volume:11 year:2005 number:4 month:12 pages:545-564 https://doi.org/10.1007/s10985-005-5239-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OPC-MAT GBV_ILN_70 GBV_ILN_4305 AR 11 2005 4 12 545-564 |
| spelling |
10.1007/s10985-005-5239-6 doi (DE-627)OLC2067134280 (DE-He213)s10985-005-5239-6-p DE-627 ger DE-627 rakwb eng 510 004 VZ Crowder, Martin verfasserin aut On Loss Distributions from Installment-Repaid Loans 2005 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, Inc. 2005 Abstract The banks have been accumulating huge data bases for many years and are increasingly turning to statistics to provide insight into customer behaviour, among other things. Credit risk is an important issue and certain stochastic models have been developed in recent years to describe and predict loan default. Two of the major models currently used in the industry are considered here, and various ways of extending their application to the case where a loan is repaid in installments are explored. The aspect of interest is the probability distribution of the total loss due to repayment default at some time. Thus, the loss distribution is determined by the distribution of times to default, here regarded as a discrete-time survival distribution. In particular, the probabilities of large losses are to be assessed for insurance purposes. credit risk default time discrete-time survival installment repayments loan lifetime loss distributions portfolio risk repayment failure time Hand, David J. aut Enthalten in Lifetime data analysis Kluwer Academic Publishers, 1995 11(2005), 4 vom: Dez., Seite 545-564 (DE-627)233193332 (DE-600)1393066-7 (DE-576)07005777X 1380-7870 nnns volume:11 year:2005 number:4 month:12 pages:545-564 https://doi.org/10.1007/s10985-005-5239-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OPC-MAT GBV_ILN_70 GBV_ILN_4305 AR 11 2005 4 12 545-564 |
| allfields_unstemmed |
10.1007/s10985-005-5239-6 doi (DE-627)OLC2067134280 (DE-He213)s10985-005-5239-6-p DE-627 ger DE-627 rakwb eng 510 004 VZ Crowder, Martin verfasserin aut On Loss Distributions from Installment-Repaid Loans 2005 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, Inc. 2005 Abstract The banks have been accumulating huge data bases for many years and are increasingly turning to statistics to provide insight into customer behaviour, among other things. Credit risk is an important issue and certain stochastic models have been developed in recent years to describe and predict loan default. Two of the major models currently used in the industry are considered here, and various ways of extending their application to the case where a loan is repaid in installments are explored. The aspect of interest is the probability distribution of the total loss due to repayment default at some time. Thus, the loss distribution is determined by the distribution of times to default, here regarded as a discrete-time survival distribution. In particular, the probabilities of large losses are to be assessed for insurance purposes. credit risk default time discrete-time survival installment repayments loan lifetime loss distributions portfolio risk repayment failure time Hand, David J. aut Enthalten in Lifetime data analysis Kluwer Academic Publishers, 1995 11(2005), 4 vom: Dez., Seite 545-564 (DE-627)233193332 (DE-600)1393066-7 (DE-576)07005777X 1380-7870 nnns volume:11 year:2005 number:4 month:12 pages:545-564 https://doi.org/10.1007/s10985-005-5239-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OPC-MAT GBV_ILN_70 GBV_ILN_4305 AR 11 2005 4 12 545-564 |
| allfieldsGer |
10.1007/s10985-005-5239-6 doi (DE-627)OLC2067134280 (DE-He213)s10985-005-5239-6-p DE-627 ger DE-627 rakwb eng 510 004 VZ Crowder, Martin verfasserin aut On Loss Distributions from Installment-Repaid Loans 2005 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, Inc. 2005 Abstract The banks have been accumulating huge data bases for many years and are increasingly turning to statistics to provide insight into customer behaviour, among other things. Credit risk is an important issue and certain stochastic models have been developed in recent years to describe and predict loan default. Two of the major models currently used in the industry are considered here, and various ways of extending their application to the case where a loan is repaid in installments are explored. The aspect of interest is the probability distribution of the total loss due to repayment default at some time. Thus, the loss distribution is determined by the distribution of times to default, here regarded as a discrete-time survival distribution. In particular, the probabilities of large losses are to be assessed for insurance purposes. credit risk default time discrete-time survival installment repayments loan lifetime loss distributions portfolio risk repayment failure time Hand, David J. aut Enthalten in Lifetime data analysis Kluwer Academic Publishers, 1995 11(2005), 4 vom: Dez., Seite 545-564 (DE-627)233193332 (DE-600)1393066-7 (DE-576)07005777X 1380-7870 nnns volume:11 year:2005 number:4 month:12 pages:545-564 https://doi.org/10.1007/s10985-005-5239-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OPC-MAT GBV_ILN_70 GBV_ILN_4305 AR 11 2005 4 12 545-564 |
| allfieldsSound |
10.1007/s10985-005-5239-6 doi (DE-627)OLC2067134280 (DE-He213)s10985-005-5239-6-p DE-627 ger DE-627 rakwb eng 510 004 VZ Crowder, Martin verfasserin aut On Loss Distributions from Installment-Repaid Loans 2005 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, Inc. 2005 Abstract The banks have been accumulating huge data bases for many years and are increasingly turning to statistics to provide insight into customer behaviour, among other things. Credit risk is an important issue and certain stochastic models have been developed in recent years to describe and predict loan default. Two of the major models currently used in the industry are considered here, and various ways of extending their application to the case where a loan is repaid in installments are explored. The aspect of interest is the probability distribution of the total loss due to repayment default at some time. Thus, the loss distribution is determined by the distribution of times to default, here regarded as a discrete-time survival distribution. In particular, the probabilities of large losses are to be assessed for insurance purposes. credit risk default time discrete-time survival installment repayments loan lifetime loss distributions portfolio risk repayment failure time Hand, David J. aut Enthalten in Lifetime data analysis Kluwer Academic Publishers, 1995 11(2005), 4 vom: Dez., Seite 545-564 (DE-627)233193332 (DE-600)1393066-7 (DE-576)07005777X 1380-7870 nnns volume:11 year:2005 number:4 month:12 pages:545-564 https://doi.org/10.1007/s10985-005-5239-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OPC-MAT GBV_ILN_70 GBV_ILN_4305 AR 11 2005 4 12 545-564 |
| language |
English |
| source |
Enthalten in Lifetime data analysis 11(2005), 4 vom: Dez., Seite 545-564 volume:11 year:2005 number:4 month:12 pages:545-564 |
| sourceStr |
Enthalten in Lifetime data analysis 11(2005), 4 vom: Dez., Seite 545-564 volume:11 year:2005 number:4 month:12 pages:545-564 |
| format_phy_str_mv |
Article |
| institution |
findex.gbv.de |
| topic_facet |
credit risk default time discrete-time survival installment repayments loan lifetime loss distributions portfolio risk repayment failure time |
| dewey-raw |
510 |
| isfreeaccess_bool |
false |
| container_title |
Lifetime data analysis |
| authorswithroles_txt_mv |
Crowder, Martin @@aut@@ Hand, David J. @@aut@@ |
| publishDateDaySort_date |
2005-12-01T00:00:00Z |
| hierarchy_top_id |
233193332 |
| dewey-sort |
3510 |
| id |
OLC2067134280 |
| language_de |
englisch |
| fullrecord |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">OLC2067134280</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230503171424.0</controlfield><controlfield tag="007">tu</controlfield><controlfield tag="008">200820s2005 xx ||||| 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s10985-005-5239-6</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)OLC2067134280</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-He213)s10985-005-5239-6-p</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">510</subfield><subfield code="a">004</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Crowder, Martin</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">On Loss Distributions from Installment-Repaid Loans</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2005</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">ohne Hilfsmittel zu benutzen</subfield><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Band</subfield><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© Springer Science+Business Media, Inc. 2005</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract The banks have been accumulating huge data bases for many years and are increasingly turning to statistics to provide insight into customer behaviour, among other things. Credit risk is an important issue and certain stochastic models have been developed in recent years to describe and predict loan default. Two of the major models currently used in the industry are considered here, and various ways of extending their application to the case where a loan is repaid in installments are explored. The aspect of interest is the probability distribution of the total loss due to repayment default at some time. Thus, the loss distribution is determined by the distribution of times to default, here regarded as a discrete-time survival distribution. In particular, the probabilities of large losses are to be assessed for insurance purposes.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">credit risk</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">default time</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">discrete-time survival</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">installment repayments</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">loan lifetime</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">loss distributions</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">portfolio risk</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">repayment failure time</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Hand, David J.</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Lifetime data analysis</subfield><subfield code="d">Kluwer Academic Publishers, 1995</subfield><subfield code="g">11(2005), 4 vom: Dez., Seite 545-564</subfield><subfield code="w">(DE-627)233193332</subfield><subfield code="w">(DE-600)1393066-7</subfield><subfield code="w">(DE-576)07005777X</subfield><subfield code="x">1380-7870</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:11</subfield><subfield code="g">year:2005</subfield><subfield code="g">number:4</subfield><subfield code="g">month:12</subfield><subfield code="g">pages:545-564</subfield></datafield><datafield tag="856" ind1="4" ind2="1"><subfield code="u">https://doi.org/10.1007/s10985-005-5239-6</subfield><subfield code="z">lizenzpflichtig</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_OLC</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-MAT</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OPC-MAT</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4305</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">11</subfield><subfield code="j">2005</subfield><subfield code="e">4</subfield><subfield code="c">12</subfield><subfield code="h">545-564</subfield></datafield></record></collection>
|
| author |
Crowder, Martin |
| spellingShingle |
Crowder, Martin ddc 510 misc credit risk misc default time misc discrete-time survival misc installment repayments misc loan lifetime misc loss distributions misc portfolio risk misc repayment failure time On Loss Distributions from Installment-Repaid Loans |
| authorStr |
Crowder, Martin |
| ppnlink_with_tag_str_mv |
@@773@@(DE-627)233193332 |
| format |
Article |
| dewey-ones |
510 - Mathematics 004 - Data processing & computer science |
| delete_txt_mv |
keep |
| author_role |
aut aut |
| collection |
OLC |
| remote_str |
false |
| illustrated |
Not Illustrated |
| issn |
1380-7870 |
| topic_title |
510 004 VZ On Loss Distributions from Installment-Repaid Loans credit risk default time discrete-time survival installment repayments loan lifetime loss distributions portfolio risk repayment failure time |
| topic |
ddc 510 misc credit risk misc default time misc discrete-time survival misc installment repayments misc loan lifetime misc loss distributions misc portfolio risk misc repayment failure time |
| topic_unstemmed |
ddc 510 misc credit risk misc default time misc discrete-time survival misc installment repayments misc loan lifetime misc loss distributions misc portfolio risk misc repayment failure time |
| topic_browse |
ddc 510 misc credit risk misc default time misc discrete-time survival misc installment repayments misc loan lifetime misc loss distributions misc portfolio risk misc repayment failure time |
| format_facet |
Aufsätze Gedruckte Aufsätze |
| format_main_str_mv |
Text Zeitschrift/Artikel |
| carriertype_str_mv |
nc |
| hierarchy_parent_title |
Lifetime data analysis |
| hierarchy_parent_id |
233193332 |
| dewey-tens |
510 - Mathematics 000 - Computer science, knowledge & systems |
| hierarchy_top_title |
Lifetime data analysis |
| isfreeaccess_txt |
false |
| familylinks_str_mv |
(DE-627)233193332 (DE-600)1393066-7 (DE-576)07005777X |
| title |
On Loss Distributions from Installment-Repaid Loans |
| ctrlnum |
(DE-627)OLC2067134280 (DE-He213)s10985-005-5239-6-p |
| title_full |
On Loss Distributions from Installment-Repaid Loans |
| author_sort |
Crowder, Martin |
| journal |
Lifetime data analysis |
| journalStr |
Lifetime data analysis |
| lang_code |
eng |
| isOA_bool |
false |
| dewey-hundreds |
500 - Science 000 - Computer science, information & general works |
| recordtype |
marc |
| publishDateSort |
2005 |
| contenttype_str_mv |
txt |
| container_start_page |
545 |
| author_browse |
Crowder, Martin Hand, David J. |
| container_volume |
11 |
| class |
510 004 VZ |
| format_se |
Aufsätze |
| author-letter |
Crowder, Martin |
| doi_str_mv |
10.1007/s10985-005-5239-6 |
| dewey-full |
510 004 |
| title_sort |
on loss distributions from installment-repaid loans |
| title_auth |
On Loss Distributions from Installment-Repaid Loans |
| abstract |
Abstract The banks have been accumulating huge data bases for many years and are increasingly turning to statistics to provide insight into customer behaviour, among other things. Credit risk is an important issue and certain stochastic models have been developed in recent years to describe and predict loan default. Two of the major models currently used in the industry are considered here, and various ways of extending their application to the case where a loan is repaid in installments are explored. The aspect of interest is the probability distribution of the total loss due to repayment default at some time. Thus, the loss distribution is determined by the distribution of times to default, here regarded as a discrete-time survival distribution. In particular, the probabilities of large losses are to be assessed for insurance purposes. © Springer Science+Business Media, Inc. 2005 |
| abstractGer |
Abstract The banks have been accumulating huge data bases for many years and are increasingly turning to statistics to provide insight into customer behaviour, among other things. Credit risk is an important issue and certain stochastic models have been developed in recent years to describe and predict loan default. Two of the major models currently used in the industry are considered here, and various ways of extending their application to the case where a loan is repaid in installments are explored. The aspect of interest is the probability distribution of the total loss due to repayment default at some time. Thus, the loss distribution is determined by the distribution of times to default, here regarded as a discrete-time survival distribution. In particular, the probabilities of large losses are to be assessed for insurance purposes. © Springer Science+Business Media, Inc. 2005 |
| abstract_unstemmed |
Abstract The banks have been accumulating huge data bases for many years and are increasingly turning to statistics to provide insight into customer behaviour, among other things. Credit risk is an important issue and certain stochastic models have been developed in recent years to describe and predict loan default. Two of the major models currently used in the industry are considered here, and various ways of extending their application to the case where a loan is repaid in installments are explored. The aspect of interest is the probability distribution of the total loss due to repayment default at some time. Thus, the loss distribution is determined by the distribution of times to default, here regarded as a discrete-time survival distribution. In particular, the probabilities of large losses are to be assessed for insurance purposes. © Springer Science+Business Media, Inc. 2005 |
| collection_details |
GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OPC-MAT GBV_ILN_70 GBV_ILN_4305 |
| container_issue |
4 |
| title_short |
On Loss Distributions from Installment-Repaid Loans |
| url |
https://doi.org/10.1007/s10985-005-5239-6 |
| remote_bool |
false |
| author2 |
Hand, David J. |
| author2Str |
Hand, David J. |
| ppnlink |
233193332 |
| mediatype_str_mv |
n |
| isOA_txt |
false |
| hochschulschrift_bool |
false |
| doi_str |
10.1007/s10985-005-5239-6 |
| up_date |
2024-07-03T13:53:16.507Z |
| _version_ |
1803566235263172608 |
| fullrecord_marcxml |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">OLC2067134280</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230503171424.0</controlfield><controlfield tag="007">tu</controlfield><controlfield tag="008">200820s2005 xx ||||| 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s10985-005-5239-6</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)OLC2067134280</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-He213)s10985-005-5239-6-p</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">510</subfield><subfield code="a">004</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Crowder, Martin</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">On Loss Distributions from Installment-Repaid Loans</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2005</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">ohne Hilfsmittel zu benutzen</subfield><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Band</subfield><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© Springer Science+Business Media, Inc. 2005</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract The banks have been accumulating huge data bases for many years and are increasingly turning to statistics to provide insight into customer behaviour, among other things. Credit risk is an important issue and certain stochastic models have been developed in recent years to describe and predict loan default. Two of the major models currently used in the industry are considered here, and various ways of extending their application to the case where a loan is repaid in installments are explored. The aspect of interest is the probability distribution of the total loss due to repayment default at some time. Thus, the loss distribution is determined by the distribution of times to default, here regarded as a discrete-time survival distribution. In particular, the probabilities of large losses are to be assessed for insurance purposes.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">credit risk</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">default time</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">discrete-time survival</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">installment repayments</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">loan lifetime</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">loss distributions</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">portfolio risk</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">repayment failure time</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Hand, David J.</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Lifetime data analysis</subfield><subfield code="d">Kluwer Academic Publishers, 1995</subfield><subfield code="g">11(2005), 4 vom: Dez., Seite 545-564</subfield><subfield code="w">(DE-627)233193332</subfield><subfield code="w">(DE-600)1393066-7</subfield><subfield code="w">(DE-576)07005777X</subfield><subfield code="x">1380-7870</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:11</subfield><subfield code="g">year:2005</subfield><subfield code="g">number:4</subfield><subfield code="g">month:12</subfield><subfield code="g">pages:545-564</subfield></datafield><datafield tag="856" ind1="4" ind2="1"><subfield code="u">https://doi.org/10.1007/s10985-005-5239-6</subfield><subfield code="z">lizenzpflichtig</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_OLC</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-MAT</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OPC-MAT</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4305</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">11</subfield><subfield code="j">2005</subfield><subfield code="e">4</subfield><subfield code="c">12</subfield><subfield code="h">545-564</subfield></datafield></record></collection>
|
| score |
7.4014397 |