Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
Ruin Probability in Heavy-Tailed Claims with Extreme Value Theory
Date
2021-09-05
Author
Yıldırım Külekci, Bükre
Karabey, Uğur
Kestel, Sevtap Ayşe
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
170
views
0
downloads
Cite This
URI
https://publish.illinois.edu/ime-conf-2021a/
https://hdl.handle.net/11511/100546
Conference Name
24th International Congress on Insurance: Mathematics and Economics
Collections
Graduate School of Applied Mathematics, Conference / Seminar
Suggestions
OpenMETU
Core
Ruin Analysis of Takaful Insurance Using Multiple Threshold Model
Achlak, Arham; Kestel, Sevtap Ayşe; Tank, Fatih (2016-09-08)
Uncertainty quantification of parameters in local volatility model via frequentist, bayesian and stochastic galerkin methods
Animoku, Abdulwahab; Uğur, Ömür; Department of Financial Mathematics (2018)
In this thesis, we investigate and implement advanced methods to quantify uncertain parameter(s) in Dupire local volatility equation. The advanced methods investigated are Bayesian and stochastic Galerkin methods. These advanced techniques implore different ideas in estimating the unknown parameters in PDEs. The Bayesian approach assumes the parameter is a random variable to be sampled from its posterior distribution. The posterior distribution of the parameter is constructed via “Bayes theorem of inverse p...
Uncertainty modelling and stability analysis for 2-way fuzzy adaptive systems
Gürkan, Evren; Erkmen, Aydan Müşerref; Banks, Stephen P.; Department of Electrical and Electronics Engineering (2003)
Uncertainty assessment in projection of the extreme river flows, the case of Ömerli catchment, İstanbul
Engin, Batuhan Eren; Yücel, İsmail; Yılmaz, Ayşen; Department of Earth System Science (2015)
The average temperature at the surface of the Earth has been increasing over the past century due to the increased greenhouse gases concentrations in atmosphere through anthropogenic activities. Rising temperature leads to an increase in evaporation and thus intensifies the components of water cycle which results in extreme flows in different parts of the world through changes in globally averaged precipitation. Projection of extreme flows is very important in this aspect, yet obscurity about many factors t...
Uncertainty models for vector based functional curves and assessing the reliability of G-Band
Kurtar, Ahmet Kürşat; Düzgün, H. Şebnem; Department of Geodetic and Geographical Information Technologies (2006)
This study is about uncertainty medelling for vector features in geographic information systems (GIS). It has mainly two objectives which are about the band models used for uncertainty modelling . The first one is the assessment of accuracy of GBand model, which is the latest and the most complex uncertainty handling model for vector features. Some simulations and tests are applied to test the reliability of accuracy of G-Band with comparing Chrisman’s epsilon band model, which is the most frequently used b...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
B. Yıldırım Külekci, U. Karabey, and S. A. Kestel, “Ruin Probability in Heavy-Tailed Claims with Extreme Value Theory,” Illinois, Amerika Birleşik Devletleri, 2021, vol. 1, Accessed: 00, 2022. [Online]. Available: https://publish.illinois.edu/ime-conf-2021a/.