Pulling the Parametric Trigger

Last year was another record-breaker for catastrophe bond issuance, with more than US$7 billion in 27 publicly disclosed deals. Despite a soft reinsurance market and a sluggish start, 2008 looks thus far like it might continue the trend of increased use of capital markets for catastrophe risk cover. But measured against other areas of fixed income, cat bond issuance remains small. The volume of collateralized debt obligations (CDOs) issued in 2007 exceeded US$250 billion, while for mortgage-backed securities it was more than US$2 trillion. And yet, a recent Guy Carpenter report revealed total cat bond issuance corresponds to only 8% of the current reinsurance cover. So why has a tool that at first looked so attractive not taken off sooner?

We believe two factors hinder the growth of the cat bond market — pricing, and transparency v. basis risk.

PRICING

Cat bonds effectively compete with traditional reinsurance. Following two years of relatively low insured losses from natural disasters, reinsurance rates are depressed, whereas credit spreads are high due to the ongoing credit crisis. In this environment, cat bonds no longer look as attractive to fixed income investors, while reinsurance looks more appealing to potential cedants. This is almost certainly a temporary issue that will change as both markets revert to more normal pricing.

TRANSPARENCY VERSUS BASIS RISK

There is a fundamental tension in the cat bond market. Most investors want greater transparency in the bond structure; as a result, they often prefer parametric structures in which bonds are triggered by a physical or numerical index like wind speed. Issuers, on the other hand, tend to be more concerned with basis risk, the risk associated with imperfect hedging. For this reason, issuers generally prefer structures linked to their own insured loss experience (as opposed, say, to measuring risk based on industry averages or event parameters).Typically, the choice comes down to risk versus return, but the market has probably not yet hit on the structure that provides an optimal balance between the interests of issuers and investors.

Recent developments in the provision of parametric indices have sought to address the inherent tension between transparency and basis risk. If an index can effectively mirror the actual exposures in a cedant’s portfolio, then the tension between transparency and basis risk can be resolved. This can be achieved by creating an index comprised of many sub-indices, each with a narrow geographical focus. Each sub-index can be weighted in an appropriate way to match the cedant’s exposure profile. How this can be done is described in detail below, using U. S. hurricanes as an example.

PEAK ZONE EXPOSURES

The catastrophe risk insurance market is highly concentrated, posing a significant challenge for (re)insurers. By way of example, one need only look at Florida, which accounts for 80% of extreme hurricane risk in the United States. (Re)insurers must attempt either to diversify this risk away or keep significant concentrations and strive to get paid appropriately. Although many insurers have significant exposure in Florida, very few have a profile that closely matches the average industry exposure to the state. So a parametric solution based on state-level losses or triggers would leave many potential cat bond issuers exposed to significant levels of basis risk. Yet a parametric approach would be easier for most potential investors to comprehend: it is much easier to understand the chance of 100 mp-h winds blowing than the probability of a particular insurer incurring more than US$1 billion of losses.

Paradex, a new index introduced by RMS, is designed to address these issues and benefit both issuers and investors. RMS has partnered with WeatherFlow to develop a network of hurricane-hardened weather stations along the U. S. coast to record wind speeds. The network currently covers Houston and surrounding areas and Florida but will be extended to the entire Gulf region and Eastern Seaboard by the start of the 2009 hurricane season. The Florida stations are indicated in the map below (See Figure 1 on page 44).

The data supplied from this network will allow peak wind speeds to be accurately estimated down to zip code level across the entire area affected by a hurricane. These measurements are then referenced against RMS insurance industry exposure and vulnerability curves to calculate final index values. Although the area covered by the weather stations is detailed enough to provide loss information at the zip code level, in most cases the nine zones on the map above will provide adequate resolution for potential cat bond issuers to reduce basis risk to acceptable levels.

The approach, as illustrated, is used in a U. S. hurricane situation. But there is reason to believe it would work for all natural catastrophe perils, so long as the hazard can be measured in sufficient detail that sub-indices can be developed to minimize basis risk. Potential investors don’t need to understand the intricacies of insurance, just the odds of specified physical events occurring. As for cedants, they can tailor the index by adjusting the weights of each sub-index to manage basis risk to acceptably low levels.

Over time, these approaches could allow the capital markets to offer the most competitive pricing for peak zone hazard risk.