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subject:"Prognoseverfahren"
~accessRights:"restricted"
~person:"Hwang, Ruey-Ching"
~subject:"Nichtparametrisches Verfahren"
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Prognoseverfahren
Nichtparametrisches Verfahren
Credit risk
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Statistische Verteilung
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Conditional distribution
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Loss given default
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Central limit theorem
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Defaulted-debt portfolio
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Loss given default distribution
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Portfolio selection
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Right-tailed censored beta-mixture regression
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Hwang, Ruey-Ching
Ravazzolo, Francesco
7
Blazsek, Szabolcs
6
Taylor, James W.
6
Paolella, Marc S.
5
Wu, Ximing
5
Almeida, Caio
4
Ardison, Kym
4
Garcia, René
4
Gupta, Rangan
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Kang, Kyu Ho
4
Pierdzioch, Christian
4
Polak, Pawel
4
Wen, Kuangyu
4
Casarin, Roberto
3
Catania, Leopoldo
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Chu, Chih-Kang
3
Clements, Adam
3
Dijk, Herman K. van
3
González-Rivera, Gloria
3
Huber, Florian
3
Jacobs, Kris
3
Jiang, Cuixia
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Linton, Oliver
3
Mitchell, James
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Patton, Andrew J.
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Perote, Javier
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Ruiz, Esther
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Vicente, Jose
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Wei, Yu
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Wied, Dominik
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Xu, Qifa
3
Ziel, Florian
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Aastveit, Knut Are
2
Adrian, Tobias
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International journal of forecasting
1
Journal of financial services research
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Journal of financial services research : JFSR
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ECONIS (ZBW)
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Predicting the loss given default distribution with the zero-inflated censored beta-mixture regression that allows probability masses and bimodality
Hwang, Ruey-Ching
;
Chu, Chih-Kang
;
Yu, Kaizhi
- In:
Journal of financial services research
59
(
2021
)
3
,
pp. 143-172
Persistent link: https://www.econbiz.de/10012547106
Saved in:
2
Predicting LGD distributions with mixed continuous and discrete ordinal outcomes
Hwang, Ruey-Ching
;
Chu, Chih-Kang
;
Yu, Kaizhi
- In:
International journal of forecasting
36
(
2020
)
3
,
pp. 1003-1022
Persistent link: https://www.econbiz.de/10012497162
Saved in:
3
Predicting loss distributions for small-size defaulted-debt portfolios using a convolution technique that allows probability masses to occur at boundary points
Chu, Chih-Kang
;
Hwang, Ruey-Ching
- In:
Journal of financial services research : JFSR
56
(
2019
)
1
,
pp. 95-117
Persistent link: https://www.econbiz.de/10012301329
Saved in:
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