| Title |
Utility indifference pricing of insurance catastrophe derivatives
|
|---|---|
| Published in |
European Actuarial Journal, May 2017
|
| DOI | 10.1007/s13385-017-0154-2 |
| Pubmed ID | |
| Authors |
Andreas Eichler, Gunther Leobacher, Michaela Szölgyenyi |
| Abstract |
We propose a model for an insurance loss index and the claims process of a single insurance company holding a fraction of the total number of contracts that captures both ordinary losses and losses due to catastrophes. In this model we price a catastrophe derivative by the method of utility indifference pricing. The associated stochastic optimization problem is treated by techniques for piecewise deterministic Markov processes. A numerical study illustrates our results. |
X Demographics
The data shown below were collected from the profiles of 9 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 3 | 33% |
| Puerto Rico | 1 | 11% |
| Unknown | 5 | 56% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 7 | 78% |
| Scientists | 1 | 11% |
| Unknown | 1 | 11% |
Mendeley readers
The data shown below were compiled from readership statistics for 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 12 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 4 | 33% |
| Lecturer | 2 | 17% |
| Student > Doctoral Student | 1 | 8% |
| Student > Ph. D. Student | 1 | 8% |
| Student > Bachelor | 1 | 8% |
| Other | 2 | 17% |
| Unknown | 1 | 8% |
| Readers by discipline | Count | As % |
|---|---|---|
| Economics, Econometrics and Finance | 6 | 50% |
| Mathematics | 2 | 17% |
| Business, Management and Accounting | 1 | 8% |
| Medicine and Dentistry | 1 | 8% |
| Engineering | 1 | 8% |
| Other | 0 | 0% |
| Unknown | 1 | 8% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 19 May 2017.
All research outputs
#7,780,614
of 25,382,440 outputs
Outputs from European Actuarial Journal
#10
of 43 outputs
Outputs of similar age
#114,007
of 327,782 outputs
Outputs of similar age from European Actuarial Journal
#2
of 2 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 43 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.1. This one scored the same or higher as 33 of them.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 327,782 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 64% of its contemporaries.
We're also able to compare this research output to 2 others from the same source and published within six weeks on either side of this one.