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The US insurance industry has long faced the spectrum of large unexpected losses from natural catastrophes such as hurricanes and earthquakes. However, the September 11, 2001 terrorist attack clearly demonstrated a new form of catastrophic risk of man‐made origin. The damages in property and life are now well known as estimates of insured losses deriving from this event range from $40 to $54 billion. The 9/11 terrorist attacks renewed the capacity problem faced the insurance industry in the underwriting of large catastrophic risk. In that regard, this paper explores the feasibility of capital market alternatives to the conventional insurance mechanism, and analyses whether the capital market could provide extra capacity to absorb terrorism risk.

In this article, the authors develop an arbitrage approach to valuing insurance‐linked securities (ILS) for non‐catastrophic events within a framework of stochastic interest rates. The prices of these transactions are driven by both an interest rate process and a non‐trivial actuarial risk process. The authors find that the duration of ILS is, in most cases, higher than the Macaulay duration of risk‐free bonds, which implies that the alleged relative out‐performance of ILS is illusory.

Insurance‐linked securities can benefit both issuers and investors; they supply insurance and reinsurance companies with additional risk capital at reasonable prices (with little or no credit risk), and supply excess returns to investors that are uncorrelated with the returns of other financial assets. This article explains the terminology of insurance and reinsurance, the structure of insurance‐linked securities, and provides an overview of major transactions. First, there is a discussion of how stochastic catastrophe modeling has been applied to assess the risk of natural catastrophes, including the reliability and validation of the risk models. Second, the authors compare the risk‐adjusted returns of recent securitizations on the basis of relative value. Compared with high‐yield bonds, catastrophe (“CAT”) bonds have wide spreads and very attractive Sharpe ratios. In fact, the risk‐adjusted returns on CAT bonds dominate high‐yield bonds. Furthermore, since natural catastrophe risk is essentially uncorrelated with market risk, high expected excess returns make CAT bonds high‐alpha assets. The authors illustrate this point and show that a relatively small allocation of insurance‐linked securities within a fixed income portfolio can enhance the expected return and simultaneously decrease risk, without significantly changing the skewness and kurtosis of the return distribution.

The recent trend of integrated risk management has resulted in corporations reassessing their risk management practices. Insurance derivatives and insurance‐linked securities are emerging as alternatives or complements to traditional resisurance capacity. Despite its theoretical benefits, the market for insurance‐linked transactions has not matured, due to problems of information asymmetry and lack of transparency. This article proposes a solution to resolve the conflicting interests preventing insurers/reinsurers and investors from more widely trading insurance risk.

Risk is difficult to measure — so difficult that no single measure seems robust enough for all circumstances. This is especially true of measuring the risk contained in insurance‐linked securities. Insurance risk is usually asymmetrically skewed. As a conse‐quence, traditional capital market risk measures — expected loss, probability of default, and the standard deviation of return out‐comes — are less than perfect to the insurance task. Without a good risk measure, it is impossible to compare the risk‐adjusted pricing of insurance‐linked notes on a consistent basis. It is impossible to tell which securities are cheap and which are expensive. It is impossible to decide on their value relative to more traditional investments.

Two strands of the literature are combined, namely the modeling of disability insurance and the design, valuation and discussion of insurance-linked securities.

This paper provides a discussion regarding the advantages and detriments of disability-linked securities in comparison with mortality-linked bonds and swaps as well as regarding potential disability-linked indices and the potential use. The discussion is followed by an introduction of a potential design and a corresponding valuation of disability bonds and swaps.

This securitization will provide useful tools for the risk management of disability risk in a risk-based regulatory framework.

No disability-linked securities have been defined and discussed so far.

Property and casualty (“P&C”) insurance companies rely on “risk capital” to absorb large losses that unexpectedly deplete claims‐paying resources and reduce underwriting capacity. The purpose of this paper is to review the similarities and differences between two different types of risk capital raised by insurers to cover losses arising from natural catastrophes: internal risk capital provided by investors in insurance company debt and equity; and external risk capital provided by third parties. The paper also explores the distinctions between four types of external catastrophe risk capital: reinsurance, industry loss warranties, catastrophe derivatives, and insurance‐linked securities. Finally, how the credit crisis has impacted alternative sources of catastrophe risk capital in different ways is considered.

The discussion is based on the conceptual framework for analyzing risk capital developed by Merton and Perold.

In 2008, the P&C insurance industry was adversely affected by significant natural catastrophe‐related losses, floundering investments, and limited access to capital markets, all of which put upward pressure on catastrophe reinsurance premiums. But the influx of new risk capital that generally accompanies hardening markets has been slower than usual to occur in the wake of the credit crisis. Meanwhile, disparities between the relative costs and benefits of alternative sources of catastrophe risk capital are even more pronounced than usual.

Although many insurance companies focus on how much reinsurance to buy, this paper emphasizes that a more important question is how much risk capital to acquire from external parties (and in what form) vis‐à‐vis investors in the insurance company's own securities.

The insurance industry, in general, accepts large risks due to the combined severity and frequency of catastrophic events; further, these risks are poorly defined given the small amount of data available for extreme events. It is important for the equitable transfer of risk to understand and quantify this risk as accurately as possible. As this risk is propagated to the capital markets, more and more parties will be exposed. An important part of pricing insurance‐linked securities (ILS) is quantifying the uncertainties existing in the physical parameters of the catastrophe models, including both the hazard and damage models. Given the amount of reliable data (1945 till present) on important storm parameters such as central pressure drop, radius to maximum winds, and non‐stationarity of the occurrence rate, moments estimated for these parameters are not highly reliable and knowledge uncertainty must be considered. Also, the engineering damage model for a given class of building in a large portfolio is subject to uncertainty associated with the quality of the buildings. A sample portfolio is used to demonstrate the impact of these knowledge uncertainties. Uncertainties associated with variability of statistics on central pressure drop, occurrence rate, and building quality were estimated and later propagated through a tropical cyclone catastrophe model to quantify the uncertainty of PML results. Finally their effect on the pricing of a typical insurance‐linked security (ILS) was estimated. Statistics of spread over LIBOR given different bond ratings/probability of attachment are presented using a pricing model (Lane [2000]). For a typical ILS, a relatively large coefficient of variation for both probability of attachment and spread over LIBOR was observed. This in turn leads to a rather large price uncertainty for a typical layer and may explain why rational investors expect a higher return for assuming catastrophe risk. The results hold independent of pricing model used. The objective of this study is to quantify this uncertainty for a simple call option and demonstrate its effect on pricing.