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heavy tails
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Insurance / Mathematics & economics
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Advanced modelling in mathematical finance : in honour of Ernst Eberlein
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On marine liability portfolio modeling
Guevara Alarcon, William
;
Albrecher, Hansjörg
; …
- In:
ASTIN bulletin : the journal of the International …
50
(
2020
)
1
,
pp. 61-93
Persistent link: https://www.econbiz.de/10012194112
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2
Properties of a risk measure derived from ruin theory
Trufin, Julien
;
Albrecher, Hansjörg
;
Denuit, Michel
- In:
The Geneva risk and insurance review
36
(
2011
)
2
,
pp. 174-188
Persistent link: https://www.econbiz.de/10009389178
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3
Optimal reinsurance from an optimal transport perspective
Acciaio, Beatrice
;
Albrecher, Hansjörg
;
García …
- In:
Insurance : mathematics and economics
122
(
2025
),
pp. 194-213
Persistent link: https://www.econbiz.de/10015432078
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4
The magnitude of a market crash can be predicted
Novak, S. Y.
;
Beirlant, Jan
- In:
Journal of banking & finance
30
(
2006
)
2
,
pp. 453-462
Persistent link: https://www.econbiz.de/10003291287
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5
Modelling censored losses using splicing : a global fit strategy with mixed Erlang and extreme value distributions
Reynkens, Tom
;
Verbelen, Roel
;
Beirlant, Jan
;
Antonio, …
- In:
Insurance / Mathematics & economics
77
(
2017
),
pp. 65-77
Persistent link: https://www.econbiz.de/10011783900
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6
Hunting for black swans in the European banking sector using extreme value analysis
Beirlant, Jan
;
Schoutens, Wim
;
De Spiegeleer, Jan
; …
- In:
Advanced modelling in mathematical finance : in honour …
,
(pp. 147-166)
.
2016
Persistent link: https://www.econbiz.de/10011800355
Saved in:
7
Center-outward quantiles and the measurement of multivariate risk
Beirlant, Jan
;
Buitendag, Sven
;
Barrio, Eustasio del
; …
- In:
Insurance / Mathematics & economics
95
(
2020
),
pp. 79-100
Persistent link: https://www.econbiz.de/10012419249
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8
A new class of copula regression models for modelling multivariate heavy-tailed data
Li, Zhengxiao
;
Beirlant, Jan
;
Yang, Liang
- In:
Insurance / Mathematics & economics
104
(
2022
),
pp. 243-261
Persistent link: https://www.econbiz.de/10013264956
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