Now showing 1 - 2 of 2
No Thumbnail Available
Publication

What Drives Insurers' Demand for Cat Bond Investments? Evidence from a Pan-European Survey

2013-07-10 , Braun, Alexander , Müller, Katja , Schmeiser, Hato

Although catastrophe bonds are continuing to gain importance in today's risk transfer and capital markets, little is known about the decision-making processes that drive the demand for this aspiring asset class. In the paper at hand, we focus on one segment of the investing community. Our main research goal is to identify major determinants of the cat bond investment decision of insurance and reinsurance companies. For this purpose, we have conducted a comprehensive survey among senior executives in the European insurance industry. Evaluating the resulting data set by means of exploratory factor analysis and logistic regression methodology, we are able to show that the expertise and experience with regard to cat bonds, the perceived fit of the instrument with the prevailing asset and liability management strategy, as well as the applicable regulatory regime are significant drivers of an insurer's propensity to invest. These statistical findings are supported by further qualitative survey results and additional information from structured interviews with the investment managers of four large dedicated cat bond funds.

No Thumbnail Available
Publication

Pricing Catastrophe Swaps: A Contingent Claims Approach

2011-11 , Braun, Alexander

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.