Abstract
The Esscher premium principle provides an important framework for allocating a certain loaded premium for some claim (risk) in order to manage the risks of insurance companies. In this paper, we show how to model the celebrated Esscher premium principle for a system of elliptically distributed dependent risks, where each risk is greater or equal than its value-at-risk. Furthermore, we present calculations of the proposed multivariate risk measure, investigate its properties and formulas, and show how special elliptical models can be implemented in the theory.
Original language | English |
---|---|
Title of host publication | ICORES 2019 - Proceedings of the 8th International Conference on Operations Research and Enterprise Systems |
Editors | Greg H. Parlier, Federico Liberatore, Marc Demange, Greg H. Parlier |
Publisher | SciTePress |
Pages | 102-110 |
Number of pages | 9 |
ISBN (Electronic) | 9789897583520 |
ISBN (Print) | 9789897583520 |
DOIs | |
State | Published - 2019 |
Externally published | Yes |
Event | 8th International Conference on Operations Research and Enterprise Systems, ICORES 2019 - Prague, Czech Republic Duration: 19 Feb 2019 → 21 Feb 2019 |
Publication series
Name | ICORES 2019 - Proceedings of the 8th International Conference on Operations Research and Enterprise Systems |
---|
Conference
Conference | 8th International Conference on Operations Research and Enterprise Systems, ICORES 2019 |
---|---|
Country/Territory | Czech Republic |
City | Prague |
Period | 19/02/19 → 21/02/19 |
Bibliographical note
Publisher Copyright:Copyright © 2019 by SCITEPRESS - Science and Technology Publications, Lda. All rights reserved.
Keywords
- Esscher premium
- Extreme risks
- Multivariate risk measures
- Premium principles
- Tail value at risk
- Value-at-risk
ASJC Scopus subject areas
- Management Science and Operations Research
- Computational Theory and Mathematics
- Computer Science Applications
- Control and Systems Engineering
- Computer Science (miscellaneous)
- Control and Optimization
- Theoretical Computer Science