Pricing Catastrophe Swaps: A Contingent Claims Approach
Journal
Insurance: Mathematics and Economics
ISSN
0167-6687
ISSN-Digital
1873-5959
Type
journal article
Date Issued
2011-11
Author(s)
Abstract
In this paper, we comprehensively analyze the (cat) catastrophe swap, a financial instrument which has attracted little scholarly attention to date. We begin with a discussion of the typical contract design, the current state of the market, as well as major areas of application. Subsequently, a two stage contingent claims pricing approach is proposed, which distinguishes between the main risk drivers ex-ante as well as during the loss reestimation phase and additionally incorporates counterparty default risk. Catastrophe occurrence is modeled as a doubly stochastic Poisson process (Cox process) with mean-reverting Ornstein-Uhlenbeck intensity. In addition, we fit various parametric distributions to normalized historical loss data for hurricanes and earthquakes in the U.S. and find the heavy-tailed Burr distribution to be the most adequate representation for loss severities. Applying our pricing model to market quotes for hurricane and earthquake contracts, we derive implied Poisson intensities which are subsequently condensed into a common factor for each peril by means of exploratory factor analysis. Further examining the resulting factor scores, we show that a first order autoregressive process provides a good fit. Hence, its continuous-time limit, the Ornstein-Uhlenbeck process should be well suited to represent the dynamics of the Poisson intensity in a cat swap pricing model.
Language
English
Keywords
Catastrophe Swaps
Contingent Claims Pricing Approach
Doubly Stochastic Poisson Process
Mean-Reverting Ornstein-Uhlenbeck Intensity
Counterparty Default Risk
Implied Intensities
Exploratory Factor Analysis
First Order Autoregressive Process
HSG Classification
contribution to scientific community
Refereed
Yes
Publisher
Elsevier
Publisher place
Amsterdam
Volume
49
Number
3
Start page
520
End page
536
Pages
17
Subject(s)
Division(s)
Eprints ID
69303