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Abstract In this paper we build a methodology for pricing of insurance-linked securities which are tied to multiple natural catastrophe perils. As a representative example, we construct a multi-peril catastrophe (CAT) bond which can be linked to the industry loss indices or actual losses incurred by an insurer. We provide pricing formulas for such CAT bonds. We illustrate the introduced methodology on the US natural catastrophe data obtained from Property Claim Services (PCS). Within this dataset, we specifically examine two types of risks: losses associated with wind and thunderstorm events, and those linked to winter storm events. Then, we fit and validate the underlying compound non-homogeneous Poisson processes taking into account the fact that the data are left-truncated. The best fitted loss distributions appear to be Burr and Generalised Extreme Value and for the first peril and log-normal for the second. Finally, we visualise the zero-coupon CAT bond prices for the selected best-fitted models.

In this paper we build a methodology for pricing of insurance-linked securities which are tied to multiple natural catastrophe perils. As a representative example, we construct a multi-peril catastrophe (CAT) bond which can be linked to the industry loss indices or actual losses incurred by an insurer. We provide pricing formulas for such CAT bonds. We illustrate the introduced methodology on the US natural catastrophe data obtained from Property Claim Services (PCS). Within this dataset, we specifically examine two types of risks: losses associated with wind and thunderstorm events, and those linked to winter storm events. Then, we fit and validate the underlying compound non-homogeneous Poisson processes taking into account the fact that the data are left-truncated. The best fitted loss distributions appear to be Burr and Generalised Extreme Value and for the first peril and log-normal for the second. Finally, we visualise the zero-coupon CAT bond prices for the selected best-fitted models. [ABSTRACT FROM AUTHOR]

The variety of catastrophe bond issuances can be used for portfolio diversification. However, the structure of catastrophe bonds differs from traditional bonds in that the face value and coupons depend on triggering events. This study aims to build a diversification strategy model framework using probabilistic–possibilistic bijective transformation (PPBT) and credibility measures in fuzzy environments based on the payoff function. The stages of modeling include identifying the trigger distribution; determining the membership degrees for the face value and coupons using PPBT; calculating the average face value and coupons using the fuzzy quantification theory; formulating the fuzzy variables for the yield; defining the function of triangular fuzzy membership for the yield; defining the credibility distribution for the triangular fuzzy variables for the yield; determining the expectation and total variance for the yield; developing a model of the catastrophe bond diversification strategy; the numerical simulation of the catastrophe bond strategy model; and formulating a solution to the simulation model of the diversification strategy using the sequential method, quadratic programming, transformation, and linearization techniques. The simulation results show that the proposed model can overcome the self-duality characteristic not possessed by the possibilistic measures in the fuzzy variables. The results obtained are expected to contribute to describing the yield uncertainty of investing in catastrophe bond assets so that investors can make wise decisions. [ABSTRACT FROM AUTHOR]

Earthquake contingency costs in traditional insurance cannot provide sufficient earthquake funding for a country because they often differ significantly from actual losses. Over the last three decades, this approach has been replaced by linking earthquake insurance to bonds in the capital market; this is now known as the earthquake catastrophe bond (ECB). Through the ECB, contingency costs become larger and more sustainable earthquake funds. Unfortunately, there are challenges in ECB issuance, as the pricing framework does not yet have standard rules and still needs to be studied. Therefore, the objective of this study is to systematically review how the ECB pricing framework is designed. The method used in this review is PRISMA. First, articles aiming to design an ECB pricing framework were collected from the Scopus, Science Direct, and Dimensions databases on 22 March 2023. Then, the results were selected, resulting in eleven relevant articles. Then, the articles' pricing frameworks were reviewed based on variables, methods, trigger events, coupon and redemption value payment schemes, and the model solution forms. Finally, several research opportunities for academics are also outlined. This research constitutes a reference for ECB issuers during the pricing process and can motivate academics to design more useful ECB pricing models. [ABSTRACT FROM AUTHOR]

Objective: Global catastrophic risks are classified into 62 categories, 34 of which have been recorded in Iran. Such risks are major threats to the Iranian economy. Using the capacity of the alternative risk transfer instruments, as one of the recommended ex-ante risk management strategies, creates financial protection in the macro frameworks of the domestic catastrophe risk management via incorporating the financial instruments of the Iranian capital market as well as the Islamic financial market. Transferring such catastrophic risks requires appropriate financial instruments. The purpose of this study is to provide, explain and design the domestic catastrophic risk management framework by alternative risk transfer instruments.Methods: The present study has been conducted based on a systematic literature review method. For this purpose, the related literature was systematically reviewed over a period of eight months. Firstly, after specifying the subject of study, the research question was developed. Then, the research protocol was designed and an appropriate mental model was designed accordingly. Subsequently, inclusion and exclusion criteria were determined. The researchers next began the comprehensive and systematic research through which 112 papers were examined. After classifying, screening, and measuring their quality, 73 studies were selected for the final in-depth analysis. In the next step, through the purposive and snowball sampling method, 18 experts were interviewed. The Delphi method was used to obtain the opinion of experts until data saturation was achieved. Their viewpoint was embedded in the final proposed framework. In the last step, the obtained data were classified, codified (using the open coding method through MAXQDA 2020 software) synthesized, and finally summarized. The trustworthiness and authenticity of the current research was measured according to the four-stage model of Lincoln and Guba.Results: In general, all the factors that affect the catastrophic risk management framework can be classified into four main categories of “necessity, implementation of infrastructure, risk measurement, and designing appropriate financial instruments”. Each category includes several subcategories and codes. The proposed framework in the present study is made up of 4 categories, 10 sub-categories, and 415. Also, 37 risks were collected and classified out of 62 catastrophic risks to obtain the “Iran Disaster Risks Diversity Table”. Finally, the appropriate financial instruments for risk transferring based on the capacity of the domestic capital market, i.e. “Insurance Sukuk Vekala” and “Cat Takaful (CT) Sukuk” (for the international Islamic Capital Market), were designed and proposed by this research.Conclusion: Finally, a schematic model was proposed to establish Iran’s catastrophic risk management framework through alternative risk transfer instruments, according to the diversity of detected factors. As a multi-dimensional concept, the framework should be considered in the implementation process.

The pandemic bond issued by the World Bank (WB) in 2017 is a financial innovation enabling the transfer of the pandemic risk from the underdeveloped/developing countries to the financial market. It covers perils of various diseases that could overwhelm the global health systems and adversely impact the world economy. If all the triggers are activated, the bond’s principal and coupons are used to finance coordinated, swift and resilient medical response to safeguard the well-being of the populace. This product, however, is criticised for its onerous trigger requirements. We examine the WB’s pandemic-bond pricing framework, which requires inputs that are only partially available. From a rather unstructured COVID-19 data set, an information database is created and customised for pandemic-bond valuation. A vector auto-regressive moving average model is utilised to jointly describe the triggers dynamics. Our modelling simulations of risk triggers reveal that the bond payout could be made in less than half of the WB’s earliest opportunity of 85 days.

The investor interest in multi-regional earthquake bonds may drop because high-risk locations are less appealing to investors than low-risk ones. Furthermore, a single parameter (earthquake magnitude) cannot accurately express the severity due to an earthquake. Therefore, the aim of this research is to propose valuing a framework for single earthquake bonds (SEB) using a double parameter trigger type, namely magnitude and depth of earthquakes, based on zone division according to seismic information. The zone division stage is divided into two stages. The first stage is to divide the covered area based on regional administrative boundaries and clustering based on the earthquake disaster risk index (EDRI), and the second stage involves clustering based on magnitude and depth of earthquakes and distance between earthquake events using the K-Means and K-Medoids algorithms. The distribution of double parameter triggers is modeled using the Archimedean copula. The result obtained is that the price of SEB based on the clustering result of EDRI categories and K-Means is higher than the price obtained by clustering EDRI categories and K-Medoids with maturities of less than 5 years. The result of this research is expected to assist the Special Purpose Vehicle in determining the price of SEB. [ABSTRACT FROM AUTHOR]

The variety of catastrophe bond issuances can be used for portfolio diversification. However, the structure of catastrophe bonds differs from traditional bonds in that the face value and coupons depend on triggering events. This study aims to build a diversification strategy model framework using probabilistic–possibilistic bijective transformation (PPBT) and credibility measures in fuzzy environments based on the payoff function. The stages of modeling include identifying the trigger distribution; determining the membership degrees for the face value and coupons using PPBT; calculating the average face value and coupons using the fuzzy quantification theory; formulating the fuzzy variables for the yield; defining the function of triangular fuzzy membership for the yield; defining the credibility distribution for the triangular fuzzy variables for the yield; determining the expectation and total variance for the yield; developing a model of the catastrophe bond diversification strategy; the numerical simulation of the catastrophe bond strategy model; and formulating a solution to the simulation model of the diversification strategy using the sequential method, quadratic programming, transformation, and linearization techniques. The simulation results show that the proposed model can overcome the self-duality characteristic not possessed by the possibilistic measures in the fuzzy variables. The results obtained are expected to contribute to describing the yield uncertainty of investing in catastrophe bond assets so that investors can make wise decisions.

The compound Poisson process (CPP) is often used in catastrophe risk modeling, for example, aggregate loss risk modeling. Hence, CPP can be involved in pricing catastrophe bonds (CAT bonds) because it requires a catastrophe risk modeling method. However, studies of how the application of CPP in pricing CAT bonds is still scarce. Therefore, this study aims to conduct a systematic literature review (SLR) on how CPP is used in pricing CAT bonds. The SLR consists of three stages: the literature selection, bibliometric analysis, and gap analysis. At the literature selection stage, the 30 articles regarding the application of CPP in pricing CAT bonds are obtained. Then, the conceptual and nonconceptual structures of the articles are mapped at the bibliometric analysis stage. Finally, in the gap analysis stage, the application of CPP in pricing CAT bonds from the previous studies is analyzed, and new research opportunities are studied. This research can be a reference for researchers regarding the application of CPP in pricing CAT bonds and can motivate them to design more beneficial ways of pricing CAT bonds with CPP in the future. [ABSTRACT FROM AUTHOR]

Out of 64 possible catastrophic events in the whole world, about 34 of them have been experienced in Iran; more than 80% of the regions are exposed to natural disasters risks such as earthquakes exposure. Domestic insurance capacity does not cover this volume of risk and the need for external reinsurance capacity is always felt. Catastrophe bonds structure as a financial & insurance innovative solution (Alternative Risk Transfer Instruments) allows an issuing institution to transfer catastrophic exposures and risk to capital market's investors by creating capital relief and additional risk capacity for our insurance industry. We adjusted the formal cat bonds structure with the Islamic jurisprudence. According to the systematic review research method 8 steps, the Sukuk model was implemented based on the extracted concepts from 23 Farsi articles and 50 English articles. After that interviews by 18 experts who were selected by purposive & Snowball sampling, The Delphi method was used to obtain the opinion of experts and their opinion was modified and implemented in the final model. In the open coding stage, 415 concepts were extracted which were classified into 10 categories and finally presented in 4 Propositions/themes. The trustworthiness and authenticity did base on the four-stage model of Lincoln and Guba and also its complementary step. We finally suggested that the catastrophe bond instrument could be issued in the form of a cat takaful (CT) sukuk contract template, as a solution for transferring catastrophic risks to the Islamic financial market.

Objective: Global catastrophic risks are classified into 62 categories, 34 of which have been recorded in Iran. Such risks are major threats to the Iranian economy. Using the capacity of the alternative risk transfer instruments, as one of the recommended ex-ante risk management strategies, creates financial protection in the macro frameworks of the domestic catastrophe risk management via incorporating the financial instruments of the Iranian capital market as well as the Islamic financial market. Transferring such catastrophic risks requires appropriate financial instruments. The purpose of this study is to provide, explain and design the domestic catastrophic risk management framework by alternative risk transfer instruments. Methods: The present study has been conducted based on a systematic literature review method. For this purpose, the related literature was systematically reviewed over a period of eight months. Firstly, after specifying the subject of study, the research question was developed. Then, the research protocol was designed and an appropriate mental model was designed accordingly. Subsequently, inclusion and exclusion criteria were determined. The researchers next began the comprehensive and systematic research through which 112 papers were examined. After classifying, screening, and measuring their quality, 73 studies were selected for the final in-depth analysis. In the next step, through the purposive and snowball sampling method, 18 experts were interviewed. The Delphi method was used to obtain the opinion of experts until data saturation was achieved. Their viewpoint was embedded in the final proposed framework. In the last step, the obtained data were classified, codified (using the open coding method through MAXQDA 2020 software) synthesized, and finally summarized. The trustworthiness and authenticity of the current research was measured according to the four-stage model of Lincoln and Guba. Results: In general, all the factors that affect the catastrophic risk management framework can be classified into four main categories of “necessity, implementation of infrastructure, risk measurement, and designing appropriate financial instruments”. Each category includes several subcategories and codes. The proposed framework in the present study is made up of 4 categories, 10 sub-categories, and 415. Also, 37 risks were collected and classified out of 62 catastrophic risks to obtain the “Iran Disaster Risks Diversity Table”. Finally, the appropriate financial instruments for risk transferring based on the capacity of the domestic capital market, i.e. “Insurance Sukuk Vekala” and “Cat Takaful (CT) Sukuk” (for the international Islamic Capital Market), were designed and proposed by this research. Conclusion: Finally, a schematic model was proposed to establish Iran’s catastrophic risk management framework through alternative risk transfer instruments, according to the diversity of detected factors. As a multi-dimensional concept, the framework should be considered in the implementation process. [ABSTRACT FROM AUTHOR]

The investor interest in multi-regional earthquake bonds may drop because high-risk locations are less appealing to investors than low-risk ones. Furthermore, a single parameter (earthquake magnitude) cannot accurately express the severity due to an earthquake. Therefore, the aim of this research is to propose valuing a framework for single earthquake bonds (SEB) using a double parameter trigger type, namely magnitude and depth of earthquakes, based on zone division according to seismic information. The zone division stage is divided into two stages. The first stage is to divide the covered area based on regional administrative boundaries and clustering based on the earthquake disaster risk index (EDRI), and the second stage involves clustering based on magnitude and depth of earthquakes and distance between earthquake events using the K-Means and K-Medoids algorithms. The distribution of double parameter triggers is modeled using the Archimedean copula. The result obtained is that the price of SEB based on the clustering result of EDRI categories and K-Means is higher than the price obtained by clustering EDRI categories and K-Medoids with maturities of less than 5 years. The result of this research is expected to assist the Special Purpose Vehicle in determining the price of SEB.

Climate change is worsening the severity and increasing the frequency of certain hazard events, thus requiring more financing for disaster mitigation or climate change adaptation. A wide range of financial tools is emerging to finance projects reducing hazard impacts on communities. Several of these tools have resilience bonds in their titles, and one is specifically known as Resilience Bonds. To evaluate the utility and effectiveness of new financing tools, we studied various available financial mechanisms for raising funds for disaster management and resilience projects. In this paper, we provide a comprehensive review of the literature and application of financial tools in enhancing community resilience against weather-related disasters since 2000. We also present findings from our interviews with finance and bond experts to unpack the existing trends in financing disaster resilience projects. Our review of the application of issued and proposed bonds with resilience goals shows that these bonds have various project scopes, with most bonds utilized for financing flood and hurricane resilience measures. Additionally, in the reviewed literature, bonds with resilience goals are primarily issued by government entities, indicating a substantial gap and opportunities for the private capital market to invest in disaster resilience. [ABSTRACT FROM AUTHOR]

Securitization is an emerging alternative to transfer of insurance risk, especially in cases exceeding the capacity of reinsurance, thus extending the insurability of risks. The original subjects of securitization are the risks emerging from the aftermaths of natural disasters. The range of securitized risks has broaden rapidly over the past decade. The reason of securitization's feasibility in transfer of agricultural risks is the spatial correlation of harvests among the producers that can result in fatal loss suffered simultaneously by many producers and subsequent producer's insolvency to settle the insurance claims. The paper proposes the reduction of the insurer's risk exposure by its transfer to capital markets via catastrophe bonds. A catastrophic event is defined through the relative loss of the current national per hectare yield of the particular crop to the average yield from previous years. The number of years included in the average is subject to the minimization of the relative loss' fluctuation over the given period. The triggering probability of the catastrophe bond is calculated from the kernel estimation of the loss distribution, with the relative loss being the loss index. The general case is upgraded by the factor of soil quality. The insurer is proposed to offer the coverage according to the producers' soil. The soil classes are securitized separately, with the set of catastrophe bonds. Both cases are illustrated by the numerical example on the data set of wheat produced in the Slovak Republic over last 45 years. The outcome of the examples are the graphs of expected payoffs depending on various parameters.

• Presents a typology of emergent risk that highlights the iterative and inter-related nature of climate change risk, and propensity for impacts, such as legal action and reduced debt access, to emerge subsequent to, yet far removed from, initial physical impacts. • Highlights current practice and gaps in local government risk management concerning emergent risk. • Highlights the potential and need for local government to consider, the application of risk transfer mechanisms such as catastrophe bonds in the face of historical and conceivable climate change-perpetuated reduced access to, and increased cost of, traditional mechanisms such as insurance. • Provides insight into barriers and enablers to local government agencies gaining an appreciation of the potential application of alternative risk transfer mechanisms. Insurance represents an integral part of local government risk management strategy. As climate change progresses, increased loss and risk related to extreme weather events such as tropical cyclones, could motivate insurers to withdraw from certain markets. In some regions, such a withdrawal represents an emergent risk that, when coupled with increasing populations and other climate change impacts, could leave local governments and ratepayers particularly vulnerable. This paper investigates such a scenario and its ramifications in the context of a region particularly vulnerable to climate change, through an exploration of the degree that consideration of emergent risks, such as loss of insurance, and the potential application of insurance alternatives influence Queensland local government risk management. The study finds little appreciation amongst government officials of emergent risk implicit in extreme weather events such as cyclones, little understanding of the nuances of risk transfer mechanisms beyond familiar traditional insurance and disaster funding mechanisms, and by default, a lack of appreciation of the relationship between the two. A lack of resource and leadership with respect to emergent risk, and an absence of dialogue between insurance brokers and local government concerning climate change risk arise as the main reasons for this result. This research is significant because it challenges current local government risk management practice through an exploration of the risks inherent in the process itself. This has potential social, economic and ecological ramifications in drawing attention to aspects of possible "uninsurability" and prospects of alleviation thereto. Further research is recommended to consider the insurance industry's part in this study's findings in order to inform current industry practice and thinking and further enlighten the causes of local government disengagement in this critical area. [ABSTRACT FROM AUTHOR]

The rapid growth of catastrophe bonds in financial markets is due to increasing environmental disasters and consequent economic losses, barely covered by insurance and reinsurance companies. These securities represent an effective solution, allowing the risk transfer to the capital market. The objective of this paper is to prove real advantages of the investor who operates in this market segment, in terms of portfolio diversification. The present work indeed shows how investing in catastrophe instruments produces actual benefits for investors both in term of diversification and total return. In fact the final results of the quantitative analysis show how efficient cat-bonds are in terms of stability, being characterised by lesser volatility and fairly stable returns. Thus, the risk potentially connected to these bonds wouldn't be a limiting factor for their development. Particularly the trend of catastrophe bonds highlights how the possible implementation and spreading of these instruments could improve portfolio strategies.

Securitization is an emerging alternative to transfer of insurance risk, especially in cases exceeding the capacity of reinsurance, thus extending the insurability of risks. The original subjects of securitization are the risks emerging from the aftermaths of natural disasters. The range of securitized risks has broaden rapidly over the past decade. The reason of securitization's feasibility in transfer of agricultural risks is the spatial correlation of harvests among the producers that can result in fatal loss suffered simultaneously by many producers and subsequent producer's insolvency to settle the insurance claims. The paper proposes the reduction of the insurer's risk exposure by its transfer to capital markets via catastrophe bonds. A catastrophic event is defined through the relative loss of the current national per hectare yield of the particular crop to the average yield from previous years. The number of years included in the average is subject to the minimization of the relative loss' fluctuation over the given period. The triggering probability of the catastrophe bond is calculated from the kernel estimation of the loss distribution, with the relative loss being the loss index. The general case is upgraded by the factor of soil quality. The insurer is proposed to offer the coverage according to the producers' soil. The soil classes are securitized separately, with the set of catastrophe bonds. Both cases are illustrated by the numerical example on the data set of wheat produced in the Slovak Republic over last 45 years. The outcome of the examples are the graphs of expected payoffs depending on various parameters. [ABSTRACT FROM AUTHOR]