Tag Archives: cat bonds

Clearing the path for catastrophe bond issuance

Cat bond efficiency has come a long way in the last decade. The premature grey hair and portly reflection that peers back at me in the mirror serves as a reminder of a time when even the simplest deals seemed to take months of work.  A whole thriving food delivery industry grew up in the City of London just to keep us fed and watered back when success was measured on capacity to work a 120-hour week, as much as on quantitative ability.

Much has changed since then. Of course, complex ground-breaking deals still take a monumental amount of effort to place successfully—just ask anyone who’s been involved with Metrocat, PennUnion or Bosphorus, and they’ll tell you it’s a very intensive process.

But there’s little doubt that deal issuance has streamlined remarkably. It is now feasible to get a simple deal done in a matter of a few short weeks, and the market knows what to expect in the way of portfolio disclosure and risk analysis information. Indeed, collateralized reinsurance trades have pushed things further, removing some of the more complex structural obstacles to get risk into insurance linked securities (ILS) portfolios efficiently.

This week, I was on a panel at the Securities Industry and Financial Markets Association (SIFMA) Insurance and Risk Linked Securities Conference, discussing the ways in which the efficiency of the cat bond risk analysis could be further streamlined. This topic comes up a lot—a risk analysis can be one of the largest costs associated with a transaction (behind the structuring fees!), and certainly a major component of the time and effort involved.

If there’s one aspect we can all agree on, I suspect it’s the importance of understanding the risk in a deal, and how that deal might behave in different catastrophic scenarios. Commoditizing the risk analysis into a cookie-cutter view of a few well-known metrics is not the way to go—every portfolio is unique, and requires detailed, bespoke understanding if you’re to include it in a well performing ILS portfolio.

Going further, it is often suggested that the risk analysis could be removed from cat bonds—indeed, there’s no other asset class out there where the deal documents themselves contain an expertized risk analysis. Investors are increasingly sophisticated—many can now consume reinsurance submissions and have the infrastructure to analyze these in-house. The argument goes, why not let the investors do the risk analysis, and take it out of the deal—that way the deal can be issued more efficiently. One deal—Compass re II—has tested this hypothesis via the Rewire platform, and successfully placed with a tight spread.

Compass was parametric—this meant that disclosure was complete. The index was fully described, so investors (or their chosen modeling consultancy) could easily generate a view of risk for the deal.  This would not have been so straightforward for an indemnity deal—here, as an investor, you’d probably want to know the detailed contents of the portfolio in order to run catastrophe models appropriately. Aggregates won’t cut it if you don’t have a risk analysis.  So, for this to work with indemnity deals, disclosure would have to increase significantly.

An indemnity deal with no risk analysis would also open up the question of interpretation—even if all the detailed data were to be shared, how should the inuring reinsurance structures be interpreted?

This can be one of the most time consuming elements of even the simplest indemnity deals.  Passing this task on to the market rather than providing the risk analysis in the deal would inevitably lead to a change in the dynamic of deal marketing—suddenly investors would be competing more and more on the speed of their internal quoting process, and be required to develop large modeling infrastructure, far larger than most ILS funds currently have access to today.  Inevitably this would take longer and lead to a more uncertain marketing process.  Inevitably it must load cost into the system, which might well be passed back to issuers by way of spread or to end investors by way of management fees. Or both. Suddenly the cost saving in the bond structure doesn’t look as attractive.

I believe there’s a better alternative—and it’s already starting to happen. Increasingly, we are being engaged by potential deal sponsors much earlier in their planning process, often before they’ve even contemplated potential cat bond structures in detail. In this paradigm, the risk analysis can be largely done and dusted before the bond issuance process begins—of course, it’s fine-tuned throughout the discussions relating to bond structures, layers and triggers etc. But the bulk of the work is done, and the deal can happen efficiently, knowing precisely how the underlying risk will look as the deal comes together. This leads to much more effective bond execution, but doesn’t open up the many challenges associated with risk analysis removal.

Detailed understanding of risk, delivered in the bond documentation, but with analysis performed ahead of the deal timeline. Perhaps the catastrophe bond analysts of the future won’t have to suffer the ignominy of receiving Grecian 2000 for their 30th birthdays.

Ben and the RMS capital markets team will be talking more about innovation in the ILS market at Exceedance 2016– sign up today to join us in Miami

Cat Bond Pricing: Calculating the True Rewards

Commentary in the specialist insurance press has generally deemed pricing of catastrophe bonds in 2015 to have bottomed out. While true in average terms, baseline pricing figures mask risk-return values. True risk pricing can be calculated only by considering all dimensions of loss, including seasonal variations and the time value of money. New analysis by RMS does just that, and shows that cat bond pricing has actually been higher in 2015 than it was last year.

Pricing of individual cat bonds is based largely on the expected loss—the average amount of principal an investor can expect to lose in the year ahead. Risk modelers calculate the expected loss for each deal as part of the transaction structuring, but to obtain a market-wide view based on consistent assumptions, we first applied the same model across all transactions to calculate the average expected loss.

Care must be taken as all loss is not equal, a fact reflected in the secondary-market pricing of catastrophe bonds. Because of the time value of money, a loss six months from now is preferable to a loss today: you can invest the money you are yet to lose, and collect coupons in the meantime. We have calculated the time-valued expected loss across more than 130 issuances in the secondary markets, which we have called Cat Cost. It is dramatically different than unadjusted values, as shown in Figure 1.

The next step to reveal the true level of cat bond pricing involves accounting for secondary market pricing quotes. Figure 2 plots the same Cat Cost data as Figure 1, but now includes pricing quotes of the bonds, which we gleaned from Swiss Re’s weekly pricing sheets. Also plotted is the “Z-spread”—this is the spread earned if all future cash flows are paid in full and the metric is calculated using a proprietary cash flow model which determines future cash flows (floating and fixed), and discounts back to the current market price. The difference between the two—the space between the top and bottom lines—is the Cat-Adjusted Spread, which measures the expected catastrophe risk-adjusted return.

We can see clearly that on 30 September, 2014 the Cat Cost was 1.53%, identical to the Cat Cost on the same day in 2015. However, this year’s cat-adjusted spread for that day is 2.52%, compared to 2.22% for 2014. In other words, the pricing of cat bonds at the end of the third quarter of 2015 was thirty basis points higher than it was on the same date in in 2014, relative to the risk and adjusted for the time value of money.

The astute will have noticed that the bond spread rises each year as the hurricane season approaches, and falls as it wanes. To account for this seasonal pricing effect, and to reveal the underlying changes in market pricing, we have split the analysis between bonds covering U.S. hurricanes and those covering U.S. earthquakes.

The findings are plotted in Figure 3, and the picture is again dramatic. It is clear that the price of non-seasonal earthquake bonds is relatively static, while hurricane bond prices rise and fall based on the time of year.


This analysis further shows—for both hurricane and earthquake bonds—that spreads were higher this year than last, relative to adjusted risk. Steep drops in excess returns masked roughly static end-of-year returns in the cat bond market, rather than reflecting a risk-based price decline. Despite the prevailing commentary, the catastrophe bond market is returning markedly more to investors today than it did a year ago, when it bottomed out. But only accurate risk and return modeling reveals the true rewards.

This post is co-authored by Oliver Withers and Jinal Shah, CFA.

Jinal Shah

Director, Capital Markets, RMS
With more than 10 years of experience in the Insurance Linked Securities (ILS) market, Jin is responsible for managing investor relationships and new ILS product development at RMS. During his time at RMS, Jin has led analytical projects for catastrophe bond placements , and has designed new parametric indices to facilitate trading of index-based deals in peak zones, as well as introduced new pricing initiatives to the ILS market.

Jin currently focuses on pricing deals and managing portfolios with RMS ILS investor clients, and leads the development of Miu, the RMS ILS portfolio management platform. Jin holds a bachelor’s in Mathematics from The University of Manchester Institute of Science and Technology, and a master’s in Operational Research from Aston Business School and is a CFA charter holder.