Recently the eld of actuarial mathematics has experienced a large development due to a signi cant increase of demands for insurance and nancial risk quanti cation due to the fact that the implementation of a complex of rules of international reporting standards (IFRS) and solvency reporting (Solvency II) has started. It appears that the key question for solvency measuring is determination of probability distribution of future cash ows of an insurance company. Solvency is then reported through an appropriate risk measure based e.g. on a percentile of this distribution. While as present popular models are based solely on aggregated data (such as total loss development from a certain time period), the main objective of this work is to scrutinize possibilities of modelling of the reserve risk (i.e. roughly said, the distribution of the ultimate incurred value of claims that have already happened in the past) based directly on individual claims. These models have not yet become popular and to the author's knowledge an overview of such models has not been published previously. The assumptions and speci cation of the already published models were compared to the practical experience and some inadequacies were pointed out. Further more a new reserve risk model was constructed which is believed to have practically more suitable assumptions and properties than the existing models. Theoretical aspects of the new model were studied and distribution of the ultimate incurred value (the modelled variable) was derived. An emphasis was put also on practical aspects of the developed model and its applicability in the case of industrial use. Therefore some restrictive assumptions which might be considered realistic in variety of practical cases and which lead to a signi cant simpli cation of the model were identi ed throughout the work. Furthermore, algorithms to reduce the number of the necessary calculations were developed. In the last chapters of the work, an e ort was devoted to the methods of the estimation of the considered parameters respecting practical limitations (such as missing observations at the time of modelling). For this purpose, survival analysis was (amongst other methods) applied.

The aim of this thesis is to develop algorithmic methods for computing particular performance measures of interest for a general class of discrete-based insurance risk models. We build upon and generalize the insurance risk models considered by Drekic and Mera (2011) and Alfa and Drekic (2007), by incorporating a threshold-based dividend system in which dividends only get paid provided some period of good financial health is sustained above a pre-specified threshold level. We employ two fundamental methods for calculating the performance measures under the more general framework. The first method adopts the matrix-analytic approach originally used by Alfa and Drekic (2007) to calculate various ruin-related probabilities of interest such as the trivariate distribution of the time of ruin, the surplus prior to ruin, and the deficit at ruin. Specifically, we begin by introducing a particular trivariate Markov process and then expressing its transition probability matrix in a block-matrix form. From this characterization, we next identify an initial probability vector for the process, from which certain important conditional probability vectors are defined. For these vectors to be computed efficiently, we derive recursive expressions for each of them. Subsequently, using these probability vectors, we derive expressions which enable the calculation of conditional ruin probabilities and, from which, their unconditional counterparts naturally follow. The second method used involves the first claim conditioning approach (i.e., condition on knowing the time the first claim occurs and its size) employed in many ruin theoretic articles including Drekic and Mera (2011). We derive expressions for the finite-ruin time based Gerber-Shiu function as well as the moments of the total dividends paid by a finite time horizon or before ruin occurs, whichever happens first. It turns out that both functions can be expressed in elegant, albeit long, recursive formulas. With the algorithmic derivations obtained from the two fundamental methods, we next focus on computational aspects of the model class by comparing six different types of models belonging to this class and providing numerical calculations for several parametric examples, highlighting the robustness and versatility of our model class. Finally, we identify several potential areas for future research and possible ways to optimize numerical calculations.

In the dissertation, we study the statistical evaluation of treatment comparisons by evaluating the relative comparison of survival experiences between two treatment groups. We construct confidence interval and simultaneous confidence bands for the ratio and odds ratio of two survival functions through both parametric and nonparametric approaches.We first construct empirical likelihood confidence interval and simultaneous confidence bands for the odds ratio of two survival functions to address small sample efficacy and sufficiency. The empirical log-likelihood ratio is developed, and the corresponding asymptotic distribution is derived. Simulation studies show that the proposed empirical likelihood band has outperformed the normal approximation band in small sample size cases in the sense that it yields closer coverage probabilities to chosen nominal levels.Furthermore, in order to incorporate prognostic factors for the adjustment of survival functions in the comparison, we construct simultaneous confidence bands for the ratio and odds ratio of survival functions based on both the Cox model and the additive risk model. We develop simultaneous confidence bands by approximating the limiting distribution of cumulative hazard functions by zero-mean Gaussian processes whose distributions can be generated through Monte Carlo simulations. Simulation studies are conducted to evaluate the performance for proposed models. Real applications on published clinical trial data sets are also studied for further illustration purposes.In the end, the population attributable fraction function is studied to measure the impact of risk factors on disease incidence in the population. We develop semiparametric estimation of attributable fraction functions for cohort studies with potentially censored event time under the additive risk model.

The aim of this thesis is to develop algorithmic methods for computing particular performance measures of interest for a general class of discrete-based insurance risk models. We build upon and generalize the insurance risk models considered by Drekic and Mera (2011) and Alfa and Drekic (2007), by incorporating a threshold-based dividend system in which dividends only get paid provided some period of good financial health is sustained above a pre-specified threshold level. We employ two fundamental methods for calculating the performance measures under the more general framework. The first method adopts the matrix-analytic approach originally used by Alfa and Drekic (2007) to calculate various ruin-related probabilities of interest such as the trivariate distribution of the time of ruin, the surplus prior to ruin, and the deficit at ruin. Specifically, we begin by introducing a particular trivariate Markov process and then expressing its transition probability matrix in a block-matrix form. From this characterization, we next identify an initial probability vector for the process, from which certain important conditional probability vectors are defined. For these vectors to be computed efficiently, we derive recursive expressions for each of them. Subsequently, using these probability vectors, we derive expressions which enable the calculation of conditional ruin probabilities and, from which, their unconditional counterparts naturally follow. The second method used involves the first claim conditioning approach (i.e., condition on knowing the time the first claim occurs and its size) employed in many ruin theoretic articles including Drekic and Mera (2011). We derive expressions for the finite-ruin time based Gerber-Shiu function as well as the moments of the total dividends paid by a finite time horizon or before ruin occurs, whichever happens first. It turns out that both functions can be expressed in elegant, albeit long, recursive formulas. With the algorithmic derivations obtained from the two fundamental methods, we next focus on computational aspects of the model class by comparing six different types of models belonging to this class and providing numerical calculations for several parametric examples, highlighting the robustness and versatility of our model class. Finally, we identify several potential areas for future research and possible ways to optimize numerical calculations.

In this thesis, the discrete time risk model with inhomogeneous claims is considered. This model is used for describing the insurer‘s capital and its components: initial capital, premiums received, and claims paid. The main risk measures, ruin probabilities and Gerber-Shiu function, are investigated and recursive formulas are obtained. These formulas give fast and accurate evaluation of the finite time ruin probabilities and Gerber-Shiu function. However, the infinite time investigations require that the Gerber-Shiu function's values for the initial capital equal to 0 must be known. This is slightly more difficult due to the claim inhomogeneity and for this reason a theorem with explicit expression of the infinite time Gerber-Shiu function for a zero initial capital is proposed. However, for the calculation of the infinite time values, some assumption about underlying claim structure must be made. As a solution the cyclically distributed claims are proposed, the algorithms for application of the theorems are given and numerical examples with graphical output are presented. Finally, a special case of discrete time risk model with inhomogeneous claims distributed according geometric law is investigated. In addition to the main results, another discrete time risk model with inhomogeneous claims acquiring rational values is investigated. Two theorems for evaluation of the finite time ruin probabilities are proved and some examples are presented. / Disertaciniame darbe nagrinėjamas diskretaus laiko rizikos modelis su skirtingai pasiskirsčiusiomis žalomis. Šis modelis aprašo draudimo įmonės turtą įtakojančius veiksnius: pradinį kapitalą, gaunamas įmokas, išmokamas žalas. Išvedamos rekursinės formulės, kurių pagalba galima tiksliai ir greitai rasti baigtinio laiko bankroto tikimybių ir Gerber-Shiu funkcijos vertes. Rekursinės formulės taip pat pateikiamos ir begalinio laiko rizikos matams, tačiau nevienodai pasiskirsčiusių žalų atveju iškyla papildomų sunkumų randant bankroto tikimybę ir Gerber-Shiu funkciją, kai pradinis kapitalas lygus 0. Tam įrodoma atskira teorema, tačiau nedarant jokių prielaidų apie žalų pasiskirstymus, apskaičiuoti vertes lengva tikrai nėra. Kaip išeitis pasiūloma cikliškai pasiskirsčiusių žalų struktūra ir pateikiami algoritmai, leidžiantys teoremas pritaikyti praktiškai. Demonstruojant teoremų ir rekursinių formulių veikimą, pateikiami skaitiniai pavyzdžiai su grafinėmis iliustracijomis bei programų kodai. Galiausiai nagrinėjamas atskiras diskretaus laiko rizikos modelio atvejis, kai žalos pasiskirsčiusios skirtingai pagal geometrinį dėsnį. Disertacijoje taip pat yra nagrinėjamas diskretaus laiko rizikos modelis su skirtingai pasiskirsčiusiomis žalomis, kurios įgyja racionalias reikšmes, bei kintančiomis įmokomis ir pradiniu kapitalu, taip pat įgyjančiais racionalias reikšmes su tam tikra sąlyga. Įrodomos dvi teoremos kaip rasti tokio modelio baigtinio laiko bankroto tikimybę ir keli... [toliau žr. visą tekstą]

Disertaciniame darbe nagrinėjamas diskretaus laiko rizikos modelis su skirtingai pasiskirsčiusiomis žalomis. Šis modelis aprašo draudimo įmonės turtą įtakojančius veiksnius: pradinį kapitalą, gaunamas įmokas, išmokamas žalas. Išvedamos rekursinės formulės, kurių pagalba galima tiksliai ir greitai rasti baigtinio laiko bankroto tikimybių ir Gerber-Shiu funkcijos vertes. Rekursinės formulės taip pat pateikiamos ir begalinio laiko rizikos matams, tačiau nevienodai pasiskirsčiusių žalų atveju iškyla papildomų sunkumų randant bankroto tikimybę ir Gerber-Shiu funkciją, kai pradinis kapitalas lygus 0. Tam įrodoma atskira teorema, tačiau nedarant jokių prielaidų apie žalų pasiskirstymus, apskaičiuoti vertes lengva tikrai nėra. Kaip išeitis pasiūloma cikliškai pasiskirsčiusių žalų struktūra ir pateikiami algoritmai, leidžiantys teoremas pritaikyti praktiškai. Demonstruojant teoremų ir rekursinių formulių veikimą, pateikiami skaitiniai pavyzdžiai su grafinėmis iliustracijomis bei programų kodai. Galiausiai nagrinėjamas atskiras diskretaus laiko rizikos modelio atvejis, kai žalos pasiskirsčiusios skirtingai pagal geometrinį dėsnį. Disertacijoje taip pat yra nagrinėjamas diskretaus laiko rizikos modelis su skirtingai pasiskirsčiusiomis žalomis, kurios įgyja racionalias reikšmes, bei kintančiomis įmokomis ir pradiniu kapitalu, taip pat įgyjančiais racionalias reikšmes su tam tikra sąlyga. Įrodomos dvi teoremos kaip rasti tokio modelio baigtinio laiko bankroto tikimybę ir keli... [toliau žr. visą tekstą] / In this thesis, the discrete time risk model with inhomogeneous claims is considered. This model is used for describing the insurer‘s capital and its components: initial capital, premiums received, and claims paid. The main risk measures, ruin probabilities and Gerber-Shiu function, are investigated and recursive formulas are obtained. These formulas give fast and accurate evaluation of the finite time ruin probabilities and Gerber-Shiu function. However, the infinite time investigations require that the Gerber-Shiu function's values for the initial capital equal to 0 must be known. This is slightly more difficult due to the claim inhomogeneity and for this reason a theorem with explicit expression of the infinite time Gerber-Shiu function for a zero initial capital is proposed. However, for the calculation of the infinite time values, some assumption about underlying claim structure must be made. As a solution the cyclically distributed claims are proposed, the algorithms for application of the theorems are given and numerical examples with graphical output are presented. Finally, a special case of discrete time risk model with inhomogeneous claims distributed according geometric law is investigated. In addition to the main results, another discrete time risk model with inhomogeneous claims acquiring rational values is investigated. Two theorems for evaluation of the finite time ruin probabilities are proved and some examples are presented.

Darbe apskaičiuotas Gerber-Shiu diskontuotos baudos funkcijos pagrindinis narys klasikiniame kolektyvinės rizikos modelyje, kai draudimo kompanijos žalos pasiskirsčiusios pagal Veibulo skirstinį su parametrais &#951; = const, 0< &#951; <1 ir &#963; = 1, o pradinis kompanijos turtas . Minėtojo nario asimptotika gauta pasinaudojus subeksponentinių pasiskirstymo funkcijų savybėmis. Darbe pateiktuose grafikuose pavaizduota diskontuotos baudos funkcijos pagrindinio nario priklausomybė nuo įvairių klasikinio kolektyvinės rizikos modelio parametrų. / In this work the main member of the Gerber-Shiu discounted penalty function in a classic collective risk model with Weibull distribution (parameters &#951; = const, 0< &#951; <1 and &#963; = 1) is calculated. The expression of the main member is obtained by making use of properties of subexponential distribution functions. In the graphs a dependence of the main member of the Gerber-Shiu discounted penalty function on various parameters of classic collective risk model is represented.

In the dissertation, we study the statistical evaluation of treatment comparisons by evaluating the relative comparison of survival experiences between two treatment groups. We construct confidence interval and simultaneous confidence bands for the ratio and odds ratio of two survival functions through both parametric and nonparametric approaches.We first construct empirical likelihood confidence interval and simultaneous confidence bands for the odds ratio of two survival functions to address small sample efficacy and sufficiency. The empirical log-likelihood ratio is developed, and the corresponding asymptotic distribution is derived. Simulation studies show that the proposed empirical likelihood band has outperformed the normal approximation band in small sample size cases in the sense that it yields closer coverage probabilities to chosen nominal levels.Furthermore, in order to incorporate prognostic factors for the adjustment of survival functions in the comparison, we construct simultaneous confidence bands for the ratio and odds ratio of survival functions based on both the Cox model and the additive risk model. We develop simultaneous confidence bands by approximating the limiting distribution of cumulative hazard functions by zero-mean Gaussian processes whose distributions can be generated through Monte Carlo simulations. Simulation studies are conducted to evaluate the performance for proposed models. Real applications on published clinical trial data sets are also studied for further illustration purposes.In the end, the population attributable fraction function is studied to measure the impact of risk factors on disease incidence in the population. We develop semiparametric estimation of attributable fraction functions for cohort studies with potentially censored event time under the additive risk model.

Dans un marché de l'assurance vie en Afrique subsaharienne francophone à la traîne, mais promis à un bel avenir en cas d'émergence de solutions techniques et commerciales endogènes, la thèse propose des outils théoriques et opérationnels adaptés à son développement. Cette démarche s'inscrit en parallèle des actions entreprises par l'autorité de contrôle régionale (la CIMA) pour fournir aux assureurs de la région des outils adaptés. En effet, la CIMA a initié des travaux pour la construction de nouvelles tables réglementaires d'expérience, ce qui a permis de fournir des références fiables et pertinentes pour la mortalité de la population assurée dans la région. Toutefois, certaines problématiques techniques utiles n'ont pas été développées dans ces travaux de construction. La thèse leur accorde alors une attention particulière. Ainsi, d'une part, la thèse permet de fournir des outils pour tenir compte des différences de mortalité entre pays de la région, tout en limitant les risques systématiques liés aux fluctuations d'échantillonnage (dues à la petite taille des échantillons de données par pays). Il apparaît notamment que si la modélisation indépendante de chaque pays n'est pas appropriée, les modèles d'hétérogénéité à facteurs observables, tels que le modèle de Cox ou de Lin et Ying, permettent d'atteindre cet objectif. On précise toutefois ici que ces modèles d'hétérogénéité ne permettent pas de supprimer le risque systématique lié aux fluctuations d'échantillonnage lors de l'estimation du modèle, ils engendrent seulement une réduction de ce risque en contrepartie d'une augmentation du risque systématique lié au choix du modèle. D'autre part, la thèse permet également de fournir des outils pour modéliser la mortalité d'expérience future dans la région. En absence de données sur les tendances passées de la mortalité d'expérience, ni le modèle classique de Lee-Carter ni ses extensions ne sont applicables. Une solution basée sur un ajustement paramétrique, une hypothèse sur la forme de l'évolution du niveau de mortalité (évolution linaire ou exponentielle) et un avis d'expert sur l'espérance de vie générationnelle à un âge donné est alors proposée (ces travaux s'appuient sur le modèle de Bongaarts). Ensuite, dans un second temps, en supposant disposer de données sur les tendances passées (ce qui pour mémoire n'est pas le cas à ce stade dans la région, mais devrait l'être dans les prochaines années), la thèse propose une modélisation de la mortalité future à partir d'une référence de mortalité externe et une analyse des risques systématiques associés (risques liés aux fluctuations d'échantillonnage et au choix de la référence de mortalité) / In a market of life insurance in sub-Saharan Francophone behind, but with a bright future in the event of emergence of endogenous technical and commercial solutions, the thesis provides theoretical and operational tools adapted to its development. This approach is in parallel with actions taken by the supervisory authority regional (CIMA) to provide insurance tools in the region. Indeed, CIMA has initiated work to construct new tables regulatory experience, which has provided reliable and relevant references for mortality of the insured population in the region. However, some useful technical issues were not developed in such construction. The thesis then give them special attention. Thus, on the one hand, the theory can provide tools to account for differences in mortality between countries in the region, while limiting the risks associated with systematic sampling fluctuations (due to small sample sizes data countries). Particular, it appears that if the model independent of each country is not appropriate, models of heterogeneity with observable factors, such as the Cox or Lin and Ying model, can achieve this goal. However, it says here that these models of heterogeneity does not eliminate the systematic risk due to sampling fluctuations when estimating the model, they generate only a reduction of this risk in exchange for an increase in systematic risk associated the choice of model. On the other hand, the thesis can also provide tools to model future mortality experience in the region. In the absence of data on past trends in mortality experience, nor the classical Lee-Carter or its extensions are applicable. A solution based on a parametric adjustment, an assumption about the form of changes in the level of mortality (exponential or linear trend) and an expert opinion on the generational life expectancy at a given age is then proposed (this work based on the model of Bongaarts). Then in a second time, assuming availability of data on past trends (which for the record is not the case at this stage in the region, but should be in the coming years), the thesis proposes a model of future mortality from an external reference mortality and analyzes associated systematic risk (risk of sampling fluctuations and on the choice of the reference of mortality)

Este trabalho apresenta as principais causas para a mortalidade das empresas paulistas criadas entre 2003 e 2007 a partir de base de dados cedida pelo SEBRAE-SP para o desenvolvimento dessa pesquisa. A amostra final, construída a partir de dados disponibilizados pela primeira vez para estudos desta natureza, contou com 662 empresas e 33 variáveis coletadas por meio de questionário aplicado diretamente às próprias empresas. A análise consistiu no teste de modelos econométricos, baseados na literatura dos modelos de duração, de forma a traduzir quais fatores são mais críticos para a sobrevivência das empresas a ponto de distingui-las em dois grupos: o das empresas vencedoras, cuja longevidade está pautada em ações que promovem ganhos de produtividade e eficiência, e aquelas desprovidas dessas ações e que muito provavelmente deixarão o mercado. Os três tipos de modelos abordados neste trabalho - não paramétrico, semi-paramétrico (riscos proporcionais) e paramétrico - apresentaram resultados similares, sendo que na abordagem de riscos proporcionais os resultados foram segmentados por tamanho e setor de atuação das empresas. Para as micro empresas, a idade do empreendedor e a iniciativa em investir na qualificação da mão de obra dos funcionários mostraram-se importantes mitigadores do risco de falha desse grupo de empresa, enquanto que para as pequenas empresas, a inovação em processos e a elaboração de um plano de negócios se destacaram dentre o conjunto de variáveis. Entre empresas dos setores de comércio e serviços, as empresas do primeiro grupo que faziam o acompanhamento das finanças (fluxo de caixa) apresentaram menor risco de falhar. Para aquelas do setor de serviços, a idade do empreendedor, o investimento em qualificação dos funcionários e o tamanho da empresa ao nascer foram importantes para reduzir o risco de falha no tempo. Outro resultado encontrado, por meio do modelo paramétrico utilizando distribuição Weibull, foi que o risco de a empresa deixar o mercado mostrou-se crescente, pelo menos nos cinco primeiros anos de existência da empresa. Entretanto, esse resultado não deve ser generalizado para períodos de tempo maiores que cinco anos. / This thesis presents the main results that determined the bankruptcy of enterprises located in the São Paulo State from 2003 to 2007. The models used in this work were possible due to the partnership with SEBRAE, Small Business Service Supporting, located in the State of São Paulo. This institution provided the data basis for this research and its final version was compound by 662 enterprises and 33 variables, which were collected from a survey done by SEBRAE and the related enterprise. For first time available for research like this The research was supported by econometrics models, more precisely duration models, which identified the most important factors regarding enterprises survival. Two enterprise groups were distinguished: that one that will survive and grow and another will fail. In this work, three models were used: parametric, non-parametric and proportional risk with all of them presenting similar results. The proportional risk approach was applied for economic sectors and enterprises size. For the micro size business, the entrepreneurship\'s age and the resources applied on the employee\'s qualification were important to reduce the risk to fail in the time, whereas for small enterprises, variables like innovation and business plan building were the most important variables. For the commerce and service sectors, the enterprises related to the first one, the enterprises which kept attention on financial results (cash flow) presented lower risk to fail. For service sector, variables such as: entrepreneur\'s age, investment on the employee\'s qualification and enterprise\'s size were the most important variables to explain the difference the risk to fail between the enterprises. Another result presented was the risk to fail, which indicates the likelihood of an enterprise to leave its business activity. In this case, the parametric model using Weibull distribution concluded that the risk grows in the first five years. However, this result must be carefully evaluated since it would be necessary a longer term data to ensure this result.