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Enhanced risk management through the application of mathematical optimization is the next competitive‐advantage frontier for the primary‐insurance industry. The widespread adoption of catastrophe models for risk management provides the opportunity to exploit mathematical optimization techniques to achieve superior financial results over traditional methods of risk allocation. The purpose of this paper is to conduct a numerical experiment to evaluate the relative performances of the steepest‐ascent method and genetic algorithm in the solution of an optimal risk‐allocation problem in primary‐insurance portfolio management.

The performance of two well‐established optimization methods – steepest ascent and genetic algorithm – are evaluated by applying them to solve the problem of minimizing the catastrophe risk of a US book of policies while concurrently maintaining a minimum level of return.

The steepest‐ascent method was found to be functionally dependent on, but not overly sensitive to, choice of initial starting policy. The genetic algorithm produced a superior solution to the steepest‐ascent method at the cost of increased computation time.

The results provide practical guidelines for algorithm selection and implementation for the reader interested in constructing an optimal insurance portfolio from a set of available policies.

Current covid-19 pandemic challenges health-care ethics. Ones of the most important challenges are medical resources allocation and a duty to treat, often addressed to medical personnel. This paper suggests that there are good reasons to rethink our health-care ethics for future global catastrophic risks. Current pandemic shows how challenging can be an issue of resources allocation even in a relatively small kind of catastrophic event such as covid-19 pandemic. In this paper, the authors show that any future existential bigger catastrophe may require new guidelines for the allocation of medical resources. The idea of assisted dying is considered as a hypothetical scenario.

This is a conceptual work based on conceptual analysis at the intersection of risk studies, health-care ethics and future studies. This study builds the argument on the assumption that the covid-19 pandemic should be treated as a sort of global catastrophic risk. Findings show that there are no such attempts in currently published peer-reviewed academic literature. This is crucial concept for the meta-analysis. This study shows why and how current pandemic can be interpreted in terms of global catastrophic risk even if, literally, covid-19 does not meet all criteria required in the risk studies to be called a global catastrophe.

We can expect an emergence of discriminatory selection policy which will require some actions taken by future patients like, for example, genetic engineering. But even then it is inevitable that there will still be a large number of survivors who require medical assistance, which they have no chance of receiving. This is why this study has considered the concept of assisted dying understood as an official protocol for health-care ethics and resources allocation policy in the case of emergency situations. Possibly more controversial idea discussed in this paper is an idea of assisted dying for those who cannot receive required medical help. Such procedure could be applied in a mass-scale during a global catastrophic event.

Philosophers and ethicists should identify and study all possible pros and cons of this discrimination rule. As this study’s findings suggested above, a reliable point of reference is the concept of substantial human enhancement. Human enhancement as such, widely debated, should be studied in that specific context of discrimination of patients in an access to limited medical resources. Last but not least, scientific community should study the concept of assisted dying which could be applied for those survivors who have no chance of obtaining medical care. Such criteria and concepts as cost-benefit analysis, the ethics of quality of life, autonomy of patients and duty of medical personnel should be considered.

Politicians and policymakers should prepare protocols for global catastrophes where these discrimination criteria would have to be applied. The same applies to the development of medical robotics aimed at replacing human health-care personnel. We assume that this is important implication for practical policy in healthcare. Our prediction, however plausible, is not a good scenario for humanity. But given this realistic development trajectory, we should do everything possible to prevent the need for the discriminatory rules in medical care described above.

This study offers the idea of assisted dying as a health-care policy in emergency situations. The authors expect that next future global catastrophes – looking at the current pandemic only as a mild prelude – will force a radical change in moral values and medical standards. New criteria of selection and discrimination will be perceived as much more exclusivist and unfair than criteria applied today.

Due to climate change and an increasing concentration of the world’s population in vulnerable areas, how to manage catastrophe risk efficiently and cover disaster losses fairly is still a universal dilemma.

This paper applies a law and economic approach.

China’s mechanism for managing catastrophic disaster risk is in many ways unique. It emphasizes government responsibilities and works well in many respects, especially in disaster emergency relief. Nonetheless, China’s mechanism which has the vestige of a centrally planned economy needs reform.

I propose a catastrophe insurance market-enhancing framework which marries the merits of both the market and government to manage catastrophe risks. There are three pillars of the framework: (i) sustaining a strong and capable government; (ii) government enhancement of the market, neither supplanting nor retarding it; (iii) legalizing the relationship between government and market to prevent government from undermining well-functioning market operations. A catastrophe insurance market-enhancing framework may provide insights for developing catastrophe insurance in China and other transitional nations.

First, this paper analyzes China’s mechanism for managing catastrophic disaster risks and China’s approach which emphasizes government responsibilities will shed light on solving how to manage catastrophe risk efficiently and cover disaster losses fairly. Second, this paper starts a broader discussion about government stimulation of developing catastrophe insurance and this framework can stimulate attention to solve the universal dilemma.

This article provides a general introduction to using catastrophe models to optimally manage the risk of a portfolio of Property & Casualty (P&C) liabilities. There is increasing emphasis on the enterprise‐wide allocation of risk capacity for all financial intermediaries, e.g. banks, pensions, investment funds, as well as life and P&C insurers. The optionality (the skewness, kurtosis, and correlation with asset risk) of liability risks contribute substantially to earnings volatility. The severity of low‐probability events, i.e. natural catastrophes (e.g. hurricanes, earthquakes), combined with increases in geographic concentrations of wealth can adversely affect the diversification of the liability risk at the portfolio level. Since in both finance and insurance, optimally allocating risk at the portfolio level is generally based on (linear) combinations of nonlinear risks, finding an optimal allocation is not always tractable. The author describes a well‐established optimization algorithm and produces a reasonable approximation for an optimal solution.

The purpose of this paper is to demonstrate a particular shift in the language used in economic policy debates since the late 1970s. We call this phenomenon the “financialization of public discourse”, which refers to the use of particular metaphors and linguistic styles that are friendly to the economic interest of the financial industry.

We used a rhetorical analysis to discover and analyze the specific cases which exemplify what we call the financialization of public discourse. A case study, the USA Treasury’s justification for its AIG policy, is used to strengthen the thesis of the paper.

As the AIG case helps demonstrate, the language of finance limits the policy conversation and disguises the fact that the government’s role in this case is not different than its overall collective risk management function.

We assume that framing of economic events helps shape public perceptions of the desirability of various policies. This prediction, although reasonable, should be supported with more direct evidence.

This paper intends to articulate a vital risk management role that the government plays in the economy. Specifically, the government is strongly suited to spreading the consequences of aggregate risk over time and thereby insulating the individuals from drastic fluctuations in their welfare. Our approach could potentially inform an array of public policies.

The rhetorical strategies that policy makers use to justify their policy positions and their consequences have been certainly under-researched, particularly in economics. This paper intends to fill this gap in the literature.

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.

Is the U.S. property & casualty (P&C) insurance industry overcapitalized? Many practitioners and industry observers claim that the industry is awash in capital, and that this excess capital has driven prices to historical lows. Others claim that the industry is undercapitalized relative to a large but plausible natural disaster, such as a large Tokyo earthquake, or a Category 5 hurricane through Miami — a “super catastrophe” in industry jargon.

I build an equilibrium model trying to reconcile investor preferences with several features of the cat bond market. The driving force behind the model is a habit process, in that catastrophes are rare economic shocks that could bring investors closer to their subsistence level. The calibration requires shocks with an impact between −1% and −3% to explain a reasonable level of cat bond spreads. Such investor preferences are not only able to generate realistic cat bond returns and price comovement among different perils, but may also able to explain why cat bonds offer higher rewards compared to equally rated corporate bonds.