Academic literature on the topic 'Longevity and mortality risk'

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Journal articles on the topic "Longevity and mortality risk"

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Yue, Jack C. "Mortality Compression and Longevity Risk." North American Actuarial Journal 16, no. 4 (October 2012): 434–48. http://dx.doi.org/10.1080/10920277.2012.10597641.

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Blake, D., A. J. G. Cairns, and K. Dowd. "Living with Mortality: Longevity Bonds and Other Mortality-Linked Securities." British Actuarial Journal 12, no. 1 (March 1, 2006): 153–97. http://dx.doi.org/10.1017/s1357321700004736.

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ABSTRACTThis paper addresses the problem of longevity risk — the risk of uncertain aggregate mortality — and discusses the ways in which life assurers, annuity providers and pension plans can manage their exposure to this risk. In particular, it focuses on how they can use mortality-linked securities and over-the-counter contracts — some existing and others still hypothetical — to manage their longevity risk exposures. It provides a detailed analysis of two such securities — the Swiss Re mortality bond issued in December 2003 and the EIB/BNP longevity bond announced in November 2004. It then looks at the universe of hypothetical mortality-linked securities — other forms of longevity bonds, swaps, futures and options — and investigates their potential uses. It also addresses implementation issues, and draws lessons from the experiences of other derivative contracts. Particular attention is paid to the issues involved with the construction and use of mortality indices, the management of the associated credit risks, and possible barriers to the development of markets for these securities. It suggests that these implementation difficulties are essentially teething problems that will be resolved over time, and so leave the way open to the development of flourishing markets in a brand new class of securities.
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Woo, G., C. J. Martin, C. Hornsby, and A. W. Coburn. "Prospective Longevity Risk Analysis." British Actuarial Journal 15, S1 (2009): 235–47. http://dx.doi.org/10.1017/s1357321700005584.

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ABSTRACTMortality improvement has traditionally been analysed using an array of statistical methods, and extrapolated to make actuarial projections. This paper presents a forward-looking approach to longevity risk analysis which is based on stochastic modelling of the underlying causes of mortality improvement, due to changes in lifestyle, health environment, and advances in medical science. The rationale for this approach is similar to that adopted for modelling other types of dynamic insurance risk, e.g. natural catastrophes, where risk analysts construct a stochastic ensemble of events that might happen in the future, rather than rely on a retrospective analysis of the non-stationary and comparatively brief historical record.Another feature of prospective longevity risk analysis, which is shared with catastrophe risk modelling, is the objective of capturing vulnerability data at a high resolution, to maximise the benefit of detailed modelling capability down to individual risk factor level. Already, the use by insurers of postcode data for U.K. flood risk assessment has carried over to U.K. mortality assessment. Powered by fast numerical computation and parameterised with high quality geographical data, hydrological models of flood risk have superseded the traditional statistical insurance loss models. A decade later, medically-motivated computational models of mortality risk can be expected to gain increasing prominence in longevity risk management.
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Levantesi, Susanna, Andrea Nigri, and Gabriella Piscopo. "Longevity risk management through Machine Learning: state of the art." Insurance Markets and Companies 11, no. 1 (November 25, 2020): 11–20. http://dx.doi.org/10.21511/ins.11(1).2020.02.

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Longevity risk management is an area of the life insurance business where the use of Artificial Intelligence is still underdeveloped. The paper retraces the main results of the recent actuarial literature on the topic to draw attention to the potential of Machine Learning in predicting mortality and consequently improving the longevity risk quantification and management, with practical implication on the pricing of life products with long-term duration and lifelong guaranteed options embedded in pension contracts or health insurance products. The application of AI methodologies to mortality forecasts improves both fitting and forecasting of the models traditionally used. In particular, the paper presents the Classification and the Regression Tree framework and the Neural Network algorithm applied to mortality data. The literature results are discussed, focusing on the forecasting performance of the Machine Learning techniques concerning the classical model. Finally, a reflection on both the great potentials of using Machine Learning in longevity management and its drawbacks is offered.
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Lin, Tzuling, and Cary Chi-Liang Tsai. "On the mortality/longevity risk hedging with mortality immunization." Insurance: Mathematics and Economics 53, no. 3 (November 2013): 580–96. http://dx.doi.org/10.1016/j.insmatheco.2013.08.006.

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Deng, Yinglu, Patrick L. Brockett, and Richard D. MacMinn. "Longevity/Mortality Risk Modeling and Securities Pricing." Journal of Risk and Insurance 79, no. 3 (February 8, 2012): 697–721. http://dx.doi.org/10.1111/j.1539-6975.2011.01450.x.

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Wingenbach, Rachel, Jong-Min Kim, and Hojin Jung. "Living longer in high longevity risk." Journal of Demographic Economics 86, no. 1 (February 7, 2020): 47–86. http://dx.doi.org/10.1017/dem.2019.20.

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AbstractThere is considerable uncertainty regarding changes in future mortality rates. This article investigates the impact of such longevity risk on discounted government annuity benefits for retirees. It is critical to forecast more accurate future mortality rates to improve our estimation of an expected annuity payout. Thus, we utilize the Lee–Carter model, which is well-known as a parsimonious dynamic mortality model. We find strong evidence that female retirees are likely to receive more public lifetime annuity than males in the USA, which is associated with systematic mortality rate differences between genders. A cross-country comparison presents that the current public annuity system would not fully cover retiree's longevity risk. Every additional year of life expectancy leaves future retirees exposed to high risk, arising from high volatility of lifetime annuities. Also, because the growth in life expectancy is higher than the growth of expected public pension, there will be a financial risk to retirees.
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Choulli, Tahir, Catherine Daveloose, and Michèle Vanmaele. "Mortality/Longevity Risk-Minimization with or without Securitization." Mathematics 9, no. 14 (July 10, 2021): 1629. http://dx.doi.org/10.3390/math9141629.

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This paper addresses the risk-minimization problem, with and without mortality securitization, à la Föllmer–Sondermann for a large class of equity-linked mortality contracts when no model for the death time is specified. This framework includes situations in which the correlation between the market model and the time of death is arbitrary general, and hence leads to the case of a market model where there are two levels of information—the public information, which is generated by the financial assets, and a larger flow of information that contains additional knowledge about the death time of an insured. By enlarging the filtration, the death uncertainty and its entailed risk are fully considered without any mathematical restriction. Our key tool lies in our optional martingale representation, which states that any martingale in the large filtration stopped at the death time can be decomposed into precise orthogonal local martingales. This allows us to derive the dynamics of the value processes of the mortality/longevity securities used for the securitization, and to decompose any mortality/longevity liability into the sum of orthogonal risks by means of a risk basis. The first main contribution of this paper resides in quantifying, as explicitly as possible, the effect of mortality on the risk-minimizing strategy by determining the optimal strategy in the enlarged filtration in terms of strategies in the smaller filtration. Our second main contribution consists of finding risk-minimizing strategies with insurance securitization by investing in stocks and one (or more) mortality/longevity derivatives such as longevity bonds. This generalizes the existing literature on risk-minimization using mortality securitization in many directions.
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Fung, Man Chung, Katja Ignatieva, and Michael Sherris. "Managing Systematic Mortality Risk in Life Annuities: An Application of Longevity Derivatives." Risks 7, no. 1 (January 3, 2019): 2. http://dx.doi.org/10.3390/risks7010002.

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This paper assesses the hedge effectiveness of an index-based longevity swap and a longevity cap for a life annuity portfolio. Although longevity swaps are a natural instrument for hedging longevity risk, derivatives with non-linear pay-offs, such as longevity caps, provide more effective downside protection. A tractable stochastic mortality model with age dependent drift and volatility is developed and analytical formulae for prices of longevity derivatives are derived. The model is calibrated using Australian mortality data. The hedging of the life annuity portfolio is comprehensively assessed for a range of assumptions for the longevity risk premium, the term to maturity of the hedging instruments, as well as the size of the underlying annuity portfolio. The results compare the risk management benefits and costs of longevity derivatives with linear and nonlinear payoff structures.
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Hanewald, Katja, John Piggott, and Michael Sherris. "Individual post-retirement longevity risk management under systematic mortality risk." Insurance: Mathematics and Economics 52, no. 1 (January 2013): 87–97. http://dx.doi.org/10.1016/j.insmatheco.2012.11.002.

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Dissertations / Theses on the topic "Longevity and mortality risk"

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Hunt, A. "Mortality modelling and longevity risk management." Thesis, City University London, 2015. http://openaccess.city.ac.uk/13532/.

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The 20th century has witnessed some of the largest and most widespread gains in human longevity ever witnessed, which show no sign of slowing down during the early years of the 21st century. The risk of further, higher than anticipated improvements in life expectancy - known as longevity risk - is now a major and growing field of study. This thesis investigates a number of theoretical and practical problems within the field of longevity risk relating to the structure and identifiability issues within many of the most common models used to study mortality rates, the construction of new mortality models, the projection of these models into the future, the impact of differences in the level and evolution of mortality rates in different populations (such as pension schemes) and the market-consistent valuation and measurement of risk in longevity-linked liabilities and securities.
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Alrefai, Lila Ahmed. "Managing longevity risk for UK pension funds." Master's thesis, Instituto Superior de Economia e Gestão, 2018. http://hdl.handle.net/10400.5/17640.

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Mestrado em Actuarial Science
Atualmente, as entidades gestoras de fundos de pensões têm mostrado alguma preocupação em relação ao risco dos seus participantes viverem mais do que o inicialmente esperado, assim como em relação ao impacto desta situação nas reservas mantidas pelos fundos para pagamento de pensões a partir da reforma. Não é novidade para quem trabalha nesta área de negócios que as taxas de mortalidade têm vindo a decrescer nos últimos anos a um ritmo acelerado. Esta tendência é motivada pelas melhorias na área da saúde, avanços tecnológicos e na capacidade das empresas e consultores financeiros de anteciparem este risco e limitar os seus efeitos, Não existindo um mercado real para monitorizar e calcular o risco atribuído ao fato da população viver até mais tarde, várias pesquisas têm vindo a ser conduzidas de modo a conseguir gerir melhor este risco, ao qual chamamos risco de longevidade. Este trabalho explora o risco de longevidade no mercado de fundo de pensões do Reino Unido, no contexto de um estágio curricular numa grande consultora internacional, e introduz modelos estocásticos estudados no passado, relacionando os mesmos com algumas ferramentas e software relevantes. O principal objetivo deste relatório foi estudar as transações usadas tipicamente para gerir o risco de longevidade. Uma aplicação de um dos modelos estocásticos usando o software R é também usada para o propósito desta análise, assim como para estimar os parâmetros do modelo e usar os resultados como uma possível ilustração.
It is no news to anyone in this industry that mortality rates have been decreasing faster year by year. Such a trend is driven by health improvements, technological advances, and the ability of firms and investment advisers to anticipate risk and limit its effects. Since there is no real market per say to monitor or calculate that risk attributed with people living longer, research has been extensively conducted to manage such risk. This risk is called longevity risk and it directly affects the mortality assumptions set by the team of actuaries conducting a valuation. In this paper we explore longevity risk in the UK pension fund market, in the context of an internship at a major consultancy, and introduce stochastic based models that have been studied in the past, relating these to some relevant tools and software. We emphasize the importance of managing this risk and present innovations in recent years that are related to longevity risk. Several investment techniques / financial products are introduced within the research paper. The focus of this paper was on the transactions that are used typically to manage longevity risk. An application of one of the stochastic models is used using R software package for the purpose of our analysis, so as to estimate the parameters for that model and use the results as a possible illustration.
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Schupp, Johannes [Verfasser]. "Trend processes in mortality models and management of the longevity risk / Johannes Schupp." Ulm : Universität Ulm, 2020. http://d-nb.info/1212443667/34.

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Bahl, Raj Kumari. "Mortality linked derivatives and their pricing." Thesis, University of Edinburgh, 2017. http://hdl.handle.net/1842/25499.

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This thesis addresses the absence of explicit pricing formulae and the complexity of proposed models (incomplete markets framework) in the area of mortality risk management requiring the application of advanced techniques from the realm of Financial Mathematics and Actuarial Science. In fact, this is a multi-essay dissertation contributing in the direction of designing and pricing mortality-linked derivatives and offering the state of art solutions to manage longevity risk. The first essay investigates the valuation of Catastrophic Mortality Bonds and, in particular, the case of the Swiss Re Mortality Bond 2003 as a primary example of this class of assets. This bond was the first Catastrophic Mortality Bond to be launched in the market and encapsulates the behaviour of a well-defined mortality index to generate payoffs for bondholders. Pricing this type of bond is a challenging task and no closed form solution exists in the literature. In my approach, we adapt the payoff of such a bond in terms of the payoff of an Asian put option and present a new methodology to derive model-independent bounds for catastrophic mortality bonds by exploiting the theory of comonotonicity. While managing catastrophic mortality risk is an upheaval task for insurers and re-insurers, the insurance industry is facing an even bigger challenge - the challenge of coping up with increased life expectancy. The recent years have witnessed unprecedented changes in mortality rate. As a result academicians and practitioners have started treating mortality in a stochastic manner. Moreover, the assumption of independence between mortality and interest rate has now been replaced by the observation that there is indeed a correlation between the two rates. Therefore, my second essay studies valuation of Guaranteed Annuity Options (GAOs) under the most generalized modeling framework where both interest rate and mortality risk are stochastic and correlated. Pricing these types of options in the correlated environment is an arduous task and a closed form solution is non-existent. In my approach, I employ the use of doubly stochastic stopping times to incorporate the randomness about the time of death and employ a suitable change of measure to facilitate the valuation of survival benefit, there by adapting the payoff of the GAO in terms of the payoff of a basket call option. I then derive general price bounds for GAOs by employing the theory of comonotonicity and the Rogers-Shi (Rogers and Shi, 1995) approach. Moreover, I suggest some `model-robust' tight bounds based on the moment generating function (m.g.f.) and characteristic function (c.f.) under the affine set up. The strength of these bounds is their computational speed which makes them indispensable for annuity providers who rely heavily on Monte Carlo simulations to calculate the fair market value of Guaranteed Annuity Options. In fact, sans Monte Carlo, the academic literature does not offer any solution for the pricing of the GAOs. I illustrate the performance of the bounds for a variety of affine processes governing the evolution of mortality and the interest rate by comparing them with the benchmark Monte Carlo estimates. Through my work, I have been able to express the payoffs of two well known modern mortality products in terms of payoffs of financial derivatives, there by filling the gaps in the literature and offering state of art techniques for pricing of these sophisticated instruments.
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Steuten, Daniel [Verfasser], Antje [Akademischer Betreuer] Mahayni, and Peter [Akademischer Betreuer] Anker. "Stochastic Mortality Modelling and Management of Longevity Risk with Pricing and Reserving Applications to Annuity Products / Daniel Steuten. Gutachter: Peter Anker. Betreuer: Antje Mahayni." Duisburg, 2013. http://d-nb.info/1034029894/34.

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Silva, Fabiana Lopes da. "Impacto do risco de longevidade em planos de previdência complementar." Universidade de São Paulo, 2010. http://www.teses.usp.br/teses/disponiveis/12/12136/tde-29112010-182036/.

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A evolução do aumento da expectativa de vida registrada nas últimas décadas foi uma conquista significativa para a sociedade e trouxe novos desafios em diversas áreas do conhecimento humano. Dentre os impactos do aumento da longevidade, destaca-se sua influência no equilíbrio técnico dos planos previdenciários. Nas entidades de previdência complementar, a identificação oportuna de possíveis desvios da premissa da mortalidade à realidade subjacente visa garantir a solvência e a manutenção dos benefícios de longo prazo. Assim, o presente estudo tem por objetivo estimar os fatores de improvement (fator redutor de mortalidade) para a população coberta por planos privados de aposentadoria, com base no método Lee-Carter e na abordagem CMI (Continuous Mortality Investigation), bem como analisar o impacto da incorporação da estimativa do aumento da expectativa de vida no fluxo de caixa atuarial em uma carteira de benefício definido. Em virtude da carência de informações históricas de tábuas de mortalidade para o Brasil, fez-se uso da técnica de pareamento (propensity score), o qual consiste na identificação do país que mais se assemelha ao Brasil no que se refere às variáveis socioeconômicas relevantes para prever a evolução da expectativa de vida. Essa técnica foi aplicada para uma amostra de 21 países da OCDE. As variáveis socioeconômicas consideradas no estudo foram: Fertilidade, PIB per capita, Crescimento anual do PIB, Saúde, Desemprego, Gini, Analfabetismo e Escolaridade. Diante dos testes efetuados, Portugal foi escolhido para servir de base para as projeções da mortalidade e obtenção dos fatores de improvement, em decorrência da técnica de pareamento e do teste de aderência realizado. Comparando-se as médias dos fluxos de caixa da AT-2000 com e sem improvement e levando-se em consideração os cenários de taxas de juros de 3%, 4%, 5% e 6% ao ano, observou-se que, não considerar o improvement, gera uma elevação do fluxo atuarial entre 7,15% a 10,51% para a carteira simulada. A projeção pelo método CMI forneceu resultado semelhante, sendo que o impacto variou entre 7,05% a 10,32%. Embora os métodos de improvement sejam bem diferentes, é importante destacar que os resultados foram bem semelhantes. Um ponto que merece preocupação é a questão da taxa de juros, pois com a tendência de queda, no longo prazo, maior será a sensibilidade do impacto da projeção do risco de longevidade. Adicionalmente, compararam-se os resultados obtidos com a Tábua Geracional RP-2000 e a Tábua SUSEP BR-EMS. Assim, os resultados anteriores mostram que não considerar a tendência de aumento da expectativa de vida na constituição das provisões técnicas pode expor as entidades de previdência a riscos pouco suportáveis no longo prazo.
The evolution of increased life expectancy recorded in recent decades has been a significant achievement for the society and brought new challenges in various areas of human knowledge. Among those, living longer has impacted the technical balance of the pension plans. In the private pension entities, the timely identification of possible deviations from the assumption of mortality to the underlying reality is to ensure the solvency and the maintenance of long-term benefits. Thus, based on Lee-Carter method and approach CMI (Continuous Mortality Investigation Bureau), this study aims to estimate the factors of improvement (reduction factor of mortality) for the population covered by pension plans as well as analyze the impact of incorporating an estimated longer life expectancy on actuarial cash flow into a portfolio of defined benefits. Due to a lack of historical information about mortality tables of Brazil, the matching technique (propensity score) was used to identify the country which is the most similar to Brazil concerning relevant socioeconomic variables, in order to predict the evolution of life expectancy. This technique was applied on 21 OECD sample countries. Socioeconomic variables considered were: Fertility, GDP per capita, annual growth of GDP, Health, Unemployment, Gini, Illiteracy and Schooling. According to test results, Portugal was chosen as the basis for projections of mortality and acquisition of factors of improvement, due to the matching technique and the adherence test performed. Comparing the averages of the cash flows of the AT-2000 with and without improvement and taking into account the scenarios of interest rates of 3%, 4%, 5% and 6% a year, it was observed that not considering the improvement generates an increased actuarial flow between 7.15% and 10.51% for the simulated portfolio. The CMI method provided similar projection, and the impact varied from 7.05% to 10.32%. Even though the methods of improvement are quite different, it is important to emphasize that the results were much the same. One point that deserves concern is the issue of interest rate since, due to the declining trend in the long run more sensitive will be the impact of the projection of longevity risk. Additionally, those results were compared with the table Generational RP-2000 and BRTable SUSEP EMS. Thus, previous results show that not considering the trend of increasing life expectancy in the establishment of technical provisions can expose the private pension entities to a little bearable risk in the long term.
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Mellkvist, Lars. "Den andres bröd : Levnadsrisk utifrån Lee-Cartermodellen." Thesis, Uppsala University, Department of Economics, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-9227.

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Under det gångna århundradet ökade den förväntade livslängden avsevärt såväl i Sverige som i övriga världen. 1900-talets förbättrade livslängd drevs inledningsvis av en minskad barnadödlighet medan de senare årtiondena kännetecknades av minskad dödlighet i höga åldrar.

En åldrande befolkning innebär ökade krav på sjukvård, äldreomsorg och inte minst pensionssystem. Pålitliga prognoser för vår framtida livslängd behövs för att beräkna de resurser som nämnda verksamheter kommer att ta i anspråk och utgör förutsättningen för en rättvis prissättning av försäkringsprodukter med levnadsrisk.

Lee-Carter-modellen är en av vår tids tongivande modeller för mortalitetsprognostisering. Modellen används här för att göra livslängdsprognoser utifrån svenska mortalitetsdata; prognoserna jämförs sedan med observerade utfall.

Mot bakgrund av resultatet diskuteras levnadsrisk med fokus på pensioner.

Inte oväntat presterar prognoserna ingen felfri bild av verkligheten och prognosfelet varierar i storlek mellan skattningarna; att använda dem som underlag för pensionsberäkningar hade i förlängningen varit ohållbart. Exemplet illustrerar på samma gång vår osäkerhet inför framtidens livslängdsutveckling och svårigheten i att prognostisera den.


During the past century, Sweden along with many other countries experienced a sharp decline in mortality rates. The increased life expectancy was initially propelled by mortality reductions among infants and subsequently by a survival improvement in advanced ages.

An ageing population has large implications for those providing services to the elderly, such as medical care and pensions, whilst also addressing the need for accurate and reliable mortality forecasts and projection methods.

The Lee-Carter model is the current gold standard for mortality forecasting and has been widely adopted in several studies. Here, the model is applied on Swedish mortality data; the projections are then compared to the observed lifespan development. Against this backdrop, a discussion on longevity risk in pensions schemes follows.

The forecasts performed in this study do not perfectly reflect the observed mortality change in the examined period; furthermore, the variation of the estimation errors limits the actuarial value of the projections. The findings illuminate the uncertainty that surrounds our future life expectancy as well as the difficulties associated with forecasting it.

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Lovász, Enrico. "Modellierung stochastischer Mortalitätsraten zur Verbriefung von Langlebigkeitsrisiken." Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2012. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-81666.

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In der Arbeit wird die Verbriefung von Mortalitätsrisiken mit dem Schwerpunkt der Modellierung des Langlebigkeitsrisikos bei Extremereignissen analysiert. Nach dem Aufzeigen der Vor- und Nachteile bereits existierender Wertpapiere für Mortalitätsrisiken wird der in dieser Arbeit verwendete hypothetische Langlebigkeitsbond präsentiert. Zentraler Bestandteil dieser Anleihe ist ein parametrisches Modell mit einem Sprungprozess und der Extremwerttheorie für die Berechnung zukünftiger Sterblichkeitsraten. Dieser Ansatz der Verbriefung von Mortalitätsrisiken ist neu. Es bietet die Vorteile die Steigerung der Überlebenswahrscheinlichkeit der vergangenen Jahre besser zu erfassen und seltene (extreme) Ereignisse, welche signifikante Auswirkungen auf die Sterberaten haben, zu berücksichtigen.
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Chen, Liang. "Small population bias and sampling effects in stochastic mortality modelling." Thesis, Heriot-Watt University, 2017. http://hdl.handle.net/10399/3372.

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Pension schemes are facing more difficulties on matching their underlying liabilities with assets, mainly due to faster mortality improvements for their underlying populations, better environments and medical treatments and historically low interest rates. Given most of the pension schemes are relatively much smaller than the national population, modelling and forecasting the small populations' longevity risk become urgent tasks for both the industrial practitioners and academic researchers. This thesis starts with a systematic analysis on the influence of population size on the uncertainties of mortality estimates and forecasts with a stochastic mortality model, based on a parametric bootstrap methodology with England and Wales males as our benchmark population. The population size has significant effect on the uncertainty of mortality estimates and forecasts. The volatilities of small populations are over-estimated by the maximum likelihood estimators. A Bayesian model is developed to improve the estimation of the volatilities and the predictions of mortality rates for the small populations by employing the information of larger population with informative prior distributions. The new model is validated with the simulated small death scenarios. The Bayesian methodologies generate smoothed estimations for the mortality rates. Moreover, a methodology is introduced to use the information of large population for obtaining unbiased volatilities estimations given the underlying prior settings. At last, an empirical study is carried out based on the Scotland mortality dataset.
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Herculano, Miguel Colburn. "Modelling long-term worker´s compensation : an application to a general insurance company." Master's thesis, Último nome, Primeiro nome. data de publicação. "Título". Dissertação de Mestrado. Universidade de Lisboa. Instituto Superior de Economia e Gestão, 2013. http://hdl.handle.net/10400.5/6043.

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Mestrado em Ciências Actuariais
This paper resumes the main findings from modeling life underwriting risks to which Worker´s Compensation is exposed. Models presented aim to shorten the path between ad hoc procedures in place and the new capital requirements foreseen by Solvency II. The legal framework of this line of business is primarily explained as it is determinant for modeling purposes. We then provide a discussion about risk models in use, major options, assumptions and other relevant issues that were regarded when modeling this line of business.
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Books on the topic "Longevity and mortality risk"

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Bhuyan, Vishaal B. Life markets: Trading mortality and longevity risk with life settlements and linked securities. Hoboken, N.J: John Wiley & Sons, 2009.

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Rablen, Matthew D. Mortality and immortality. Bonn, Germany: IZA, 2007.

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R, Brown Jeffrey. Mortality risk, inflation risk, and annuity products. Cambridge, MA: National Bureau of Economic Research, 2000.

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Voĭtenko, V. P. Faktory smertnosti i prodolzhitelʹnostʹ zhizni. Kiev: Zdorov'i︠a︡, 1987.

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Murphy, Kevin M. The value of health and longevity. Cambridge, MA: National Bureau of Economic Research, 2005.

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Hurd, Michael D. Mortality risk and consumption by couples. Cambridge, MA: National Bureau of Economic Research, 1999.

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Friedberg, Leora. Life is cheap: Using mortality bonds to hedge aggregate mortality risk. Cambridge, Mass: National Bureau of Economic Research, 2006.

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Frijters, Paul. Socio-economic status, health shocks, life satisfaction and mortality: Evidence from an increasing mixed proportional hazard model. Bonn, Germany: IZA, 2005.

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Cropper, Maureen L. Valuing mortality risk reductions: Progress and challenges. Cambridge, MA: National Bureau of Economic Research, 2011.

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Statistics Canada. Analytical Studies Branch. Mortality risk distributions: A life table analysis. S.l: s.n, 1988.

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Book chapters on the topic "Longevity and mortality risk"

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Kovács, Erzsébet, and Péter Vékás. "Mortality and Longevity Risk." In The Palgrave Handbook of Unconventional Risk Transfer, 269–97. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-59297-8_9.

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Booth, Heather. "Coherent Mortality Forecasting with Standards: Low Mortality Serves as a Guide." In Developments in Demographic Forecasting, 153–78. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-42472-5_8.

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Abstract:
Abstract Mortality forecasts are an important component of population forecasting and are central to the estimation of longevity risk in actuarial practice. Planning by the state for health and aged care services and by individuals for retirement and later life depends on accurate mortality forecasts. The overall accuracy or performance of mortality forecasting has improved since Lee and Carter (1992) introduced stochastic forecasting of mortality to the demographic community, and further improvements can undoubtedly be made.
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Zhang, Ning. "Introduction and Computation of Longevity Risk Index Based on Mortality Rate Decomposition Model." In Communications in Computer and Information Science, 608–15. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-31968-6_72.

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Jonsson, Bror, and Nina Jonsson. "Recruitment, Mortality and Longevity." In Ecology of Atlantic Salmon and Brown Trout, 415–71. Dordrecht: Springer Netherlands, 2011. http://dx.doi.org/10.1007/978-94-007-1189-1_8.

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Anderson, Douglas, and Steven Baxter. "Longevity Risk Transfer." In The Palgrave Handbook of Unconventional Risk Transfer, 375–434. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-59297-8_13.

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De Rosa, Clemente, Elisa Luciano, and Luca Regis. "International Longevity Risk Pooling." In Mathematical and Statistical Methods for Actuarial Sciences and Finance, 317–21. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-89824-7_57.

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Viscusi, W. Kip. "Risk-Risk Analysis." In The Mortality Costs of Regulatory Expenditures, 5–17. Dordrecht: Springer Netherlands, 1994. http://dx.doi.org/10.1007/978-94-011-1360-1_1.

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Ceylan, Elif, and Seher A. Tezergil. "Longevity Risk in Life Insurance." In New Challenges in Banking and Finance, 87–104. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-66872-7_8.

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Milevsky, Moshe Arye. "Exotic Annuities for Longevity Risk." In Retirement Income Recipes in R, 281–96. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-51434-1_14.

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Coughlan, Guy, David Blake, Richard MacMinn, Andrew J. G. Cairns, and Kevin Dowd. "Longevity Risk and Hedging Solutions." In Handbook of Insurance, 997–1035. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-0155-1_34.

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Conference papers on the topic "Longevity and mortality risk"

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Zhang, Ning. "The modified mortality decomposition model and its application in the China longevity risk analysis." In 2nd International Conference on Computer and Information Applications (ICCIA 2012). Paris, France: Atlantis Press, 2012. http://dx.doi.org/10.2991/iccia.2012.362.

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Qin, Shang, and Zhang Guozhong. "Longevity risk management for government pension fund: Longevity bonds design." In 2013 6th International Conference on Information Management, Innovation Management and Industrial Engineering (ICIII). IEEE, 2013. http://dx.doi.org/10.1109/iciii.2013.6702972.

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Shang, Qin, and Xuezhi Qin. "Securitization of Longevity Risk in Pension Annuities." In 2008 4th International Conference on Wireless Communications, Networking and Mobile Computing (WiCOM). IEEE, 2008. http://dx.doi.org/10.1109/wicom.2008.2285.

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Zheng, Chengli, and Ting He. "Pricing Longevity Bonds Based on Stochastic Mortality Forecasting by Panel Data Procedures." In 2009 International Conference on Business Intelligence and Financial Engineering (BIFE). IEEE, 2009. http://dx.doi.org/10.1109/bife.2009.83.

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Kozubík, Aleš. "LONGEVITY RISK IN THE LIFE INSURANCE MARKET OF THE V4 COUNTRIES." In 2nd International Scientific Conference - Economics and Management: How to Cope With Disrupted Times. Association of Economists and Managers of the Balkans, Belgrade, Serbia; Faculty of Management Koper, Slovenia; Doba Business School - Maribor, Slovenia; Integrated Business Faculty - Skopje, Macedonia; Faculty of Management - Zajecar, Serbia, 2018. http://dx.doi.org/10.31410/eman.2018.213.

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Hu, Shiqiang. "Longevity Risk and Capital Accumulation under the Current China Pension System." In 2013 Sixth International Conference on Business Intelligence and Financial Engineering (BIFE). IEEE, 2013. http://dx.doi.org/10.1109/bife.2013.67.

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Sullivan, SD, MD Eisner, JD Campbell, and TA Omachi. "Risk of Mortality Associated with Asthma Exacerbation." In American Thoracic Society 2009 International Conference, May 15-20, 2009 • San Diego, California. American Thoracic Society, 2009. http://dx.doi.org/10.1164/ajrccm-conference.2009.179.1_meetingabstracts.a4770.

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Socher, Roni, and Haesoon Lee. "Risk Factors For Mortality In Congenital Tuberculosis." In American Thoracic Society 2010 International Conference, May 14-19, 2010 • New Orleans. American Thoracic Society, 2010. http://dx.doi.org/10.1164/ajrccm-conference.2010.181.1_meetingabstracts.a5464.

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GAVRILOV, LEONID A., and NATALIA S. GAVRILOVA. "MATTERS OF LIFE AND DEATH: WHAT CAN WE LEARN ABOUT AGING FROM MORTALITY AND LONGEVITY STUDIES?" In HOMO SAPIENS LIBERATUS. TORUS PRESS, 2020. http://dx.doi.org/10.30826/homosapiens-2020-16.

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Rabl, Ari. "Mortality due to air pollution: how to interpret the results." In Environmental Health Risk 2001. Southampton, UK: WIT Press, 2001. http://dx.doi.org/10.2495/ehr010051.

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Reports on the topic "Longevity and mortality risk"

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Brown, Jeffrey, Olivia Mitchell, and James Poterba. Mortality Risk, Inflation Risk, and Annuity Products. Cambridge, MA: National Bureau of Economic Research, July 2000. http://dx.doi.org/10.3386/w7812.

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Gan, Li, Guan Gong, Michael Hurd, and Daniel McFadden. Subjective Mortality Risk and Bequests. Cambridge, MA: National Bureau of Economic Research, September 2004. http://dx.doi.org/10.3386/w10789.

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Hurd, Michael. Mortality Risk and Consumption by Couples. Cambridge, MA: National Bureau of Economic Research, March 1999. http://dx.doi.org/10.3386/w7048.

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Friedberg, Leora, and Anthony Webb. Life is Cheap: Using Mortality Bonds to Hedge Aggregate Mortality Risk. Cambridge, MA: National Bureau of Economic Research, January 2006. http://dx.doi.org/10.3386/w11984.

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Mullin, Charles, and Tomas Philipson. The Future of Old-Age Longevity: Competitive Pricing of Mortality Contingent Claims. Cambridge, MA: National Bureau of Economic Research, May 1997. http://dx.doi.org/10.3386/w6042.

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Poulain, Michel, Dany Chambre, Pino Ledda, and Anne Herm. Marital fertility decline and child mortality in the Sardinian longevity Blue Zone. Verlag der Österreichischen Akademie der Wissenschaften, September 2020. http://dx.doi.org/10.1553/populationyearbook2020.res05.

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Cropper, Maureen, James Hammitt, and Lisa Robinson. Valuing Mortality Risk Reductions: Progress and Challenges. Cambridge, MA: National Bureau of Economic Research, April 2011. http://dx.doi.org/10.3386/w16971.

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Amin, Sajeda, and Alaka Basu. Popular perceptions of emerging influences on mortality and longevity in Bangladesh and West Bengal. Population Council, 2004. http://dx.doi.org/10.31899/pgy2.1013.

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Bauer, Daniel, Darius Lakdawalla, and Julian Reif. Mortality Risk, Insurance, and the Value of Life. Cambridge, MA: National Bureau of Economic Research, September 2018. http://dx.doi.org/10.3386/w25055.

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Lichtenberg, Frank. The Quality of Medical Care, Behavioral Risk Factors, and Longevity Growth. Cambridge, MA: National Bureau of Economic Research, June 2009. http://dx.doi.org/10.3386/w15068.

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