Savo darbe mes nagrinėjame Gerber-Shiu baudos funkciją klasikiniame rizikos modelyje atveju, kai žalų dydžiai pasiskirstę pagal Pareto dėsnį. Pagrindinis uždavinys yra susikonstruoti algoritmą funkcijos reikšmių gavimui. Tiriamas Gerber-Shiu diskontuotos baudos funkcijos atvejis, kada vidinė baudos funkcija w tapačiai lygi vienetui. Dėl sudėtingos transformuoto Pareto skirstinio formos analitiškai paskaičiuoti sąsūkų nepavyko. Tam tikslui naudojamas interpoliavimas kubiniu splainu. N kartų kartodami sukonstruotą algoritmą gauname pirmąsias n sąsūkas laisvai pasirinktiems pradiniams parametrams: Pareto skirstinio laipsnio rodikliui α, pradiniam kapitalui u, santykinei draudimo priemokai θ, diskontavimo parametrui (palūkanų normai) δ ir Puasono proceso parametrui λ. Lentelių pagalba parodome funkcijos priklausomybę nuo skirtingų modeliuojančių parametrų reikšmių. Išvadose teigiame jog pasiūlytas metodas skaičiuoti Gerber-Shiu diskontuotos baudos funkciją nors ir išpildomas tačiau yra neefektyvus. Kai kuriais pradinių parametrų pasirinkimo atvejais susiduriama su tikslumo problema. Norint tiksliai paskaičiuoti funkcijos reikšmes reikia didesnių eilių transformuoto Pareto skirstinio sąsūkų, o tam reikalingi dideli resursai. Kita vertus, pradinio kapitalo u reikšmėms didėjant tikslumas didėja ženkliai. / In this paper we consider Gerber-Shiu discounted penalty function in the classical risk model for Pareto claims. Our main goal is to construct an algorithm for obtaining values of the discounted penalty function (considering penalty function w=1). Due to the complicated form of the transformed Pareto distribution function we cannot obtain its convolutions analiticaly. We use numerical methods provided by Maple (cube spline) to find interpolating functions instead. Continuously applying recursive formulas we obtain first 5 interpolated convolutions. Then we calculate values of Gerber-Shiu discounted penalty function for certain arbitrary parameters: α – degree of Pareto distribution function, initial surplus u, security loading θ, discounting parameter δ and Poison process parameter λ. We present data tables and graphs of the discounted penalty function for some variations of parameters in later sections. Finally we state that the method that we use is quite complicated. For better accuracy of the discounted penalty function values one may require to get many convolutions of the transformed Pareto distribution function and that may require too great of the resources. However the quantity of the convolutions needed rapidly decreases for large values of the initial surplus u.

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.

Main focus is to extend the analysis of the ruin related quantities, such as the surplus immediately prior to ruin, the deficit at ruin or the ruin probability, to the delayed renewal risk models. First, the background for the delayed renewal risk model is introduced and two important equations that are used as frameworks are derived. These equations are extended from the ordinary renewal risk model to the delayed renewal risk model. The first equation is obtained by conditioning on the first drop below the initial surplus level, and the second equation by conditioning on the amount and the time of the first claim. Then, we consider the deficit at ruin in particular among many random variables associated with ruin and six main results are derived. We also explore how the Gerber-Shiu expected discounted penalty function can be expressed in closed form when distributional assumptions are given for claim sizes or the time until the first claim. Lastly, we consider a model that has premium rate reduced when the surplus level is above a certain threshold value until it falls below the threshold value. The amount of the reduction in the premium rate can also be viewed as a dividend rate paid out from the original premium rate when the surplus level is above some threshold value. The constant barrier model is considered as a special case where the premium rate is reduced to $0$ when the surplus level reaches a certain threshold value. The dividend amount paid out during the life of the surplus process until ruin, discounted to the beginning of the process, is also considered.

Main focus is to extend the analysis of the ruin related quantities, such as the surplus immediately prior to ruin, the deficit at ruin or the ruin probability, to the delayed renewal risk models. First, the background for the delayed renewal risk model is introduced and two important equations that are used as frameworks are derived. These equations are extended from the ordinary renewal risk model to the delayed renewal risk model. The first equation is obtained by conditioning on the first drop below the initial surplus level, and the second equation by conditioning on the amount and the time of the first claim. Then, we consider the deficit at ruin in particular among many random variables associated with ruin and six main results are derived. We also explore how the Gerber-Shiu expected discounted penalty function can be expressed in closed form when distributional assumptions are given for claim sizes or the time until the first claim. Lastly, we consider a model that has premium rate reduced when the surplus level is above a certain threshold value until it falls below the threshold value. The amount of the reduction in the premium rate can also be viewed as a dividend rate paid out from the original premium rate when the surplus level is above some threshold value. The constant barrier model is considered as a special case where the premium rate is reduced to $0$ when the surplus level reaches a certain threshold value. The dividend amount paid out during the life of the surplus process until ruin, discounted to the beginning of the process, is also considered.

In this thesis, we consider a generalization of the classical Gerber-Shiu function in various risk models. The generalization involves introduction of two new variables in the original penalty function including the surplus prior to ruin and the deficit at ruin. These new variables are the minimum surplus level before ruin occurs and the surplus immediately after the second last claim before ruin occurs. Although these quantities can not be observed until ruin occurs, we can still identify their distributions in advance because they do not functionally depend on the time of ruin, but only depend on known quantities including the initial surplus allocated to the business. Therefore, some ruin related quantities obtained by incorporating four variables in the generalized Gerber-Shiu function can help our understanding of the analysis of the random walk and the resultant risk management. In Chapter 2, we demonstrate the generalized Gerber-Shiu functions satisfy the defective renewal equation in terms of the compound geometric distribution in the ordinary Sparre Andersen renewal risk models (continuous time). As a result, forms of joint and marginal distributions associated with the variables in the generalized penalty function are derived for an arbitrary distribution of interclaim/interarrival times. Because the identification of the compound geometric components is difficult without any specific conditions on the interclaim times, in Chapter 3 we consider the special case when the interclaim time distribution is from the Coxian class of distribution, as well as the classical compound Poisson models. Note that the analysis of the generalized Gerber-Shiu function involving three (the classical two variables and the surplus after the second last claim) is sufficient to study of four variable. It is shown to be true even in the cases where the interclaim of the first event is assumed to be different from the subsequent interclaims (i.e. delayed renewal risk models) in Chapter 4 or the counting (the number of claims) process is defined in the discrete time (i.e. discrete renewal risk models) in Chapter 5. In Chapter 6 the two-sided bounds for a renewal equation are studied. These results may be used in many cases related to the various ruin quantities from the generalized Gerber-Shiu function analyzed in previous chapters. Note that the larger number of iterations of computing the bound produces the closer result to the exact value. However, for the nonexponential bound the form of bound contains the convolution involving usually heavy-tailed distribution (e.g. heavy-tailed claims, extreme events), we need to find the alternative method to reinforce the convolution computation in this case.

The seminal paper by Gerber and Shiu (1998) gave a huge boost to the study of risk theory by not only unifying but also generalizing the treatment and the analysis of various risk-related quantities in one single mathematical function - the Gerber-Shiu expected discounted penalty function, or Gerber-Shiu function in short. The Gerber-Shiu function is known to possess many nice properties, at least in the case of the classical compound Poisson risk model. For example, upon the introduction of a dividend barrier strategy, it was shown by Lin et al. (2003) and Gerber et al. (2006) that the Gerber-Shiu function with a barrier can be expressed in terms of the Gerber-Shiu function without a barrier and the expected value of discounted dividend payments. This result is the so-called dividends-penalty identity, and it holds true when the surplus process belongs to a class of Markov processes which are skip-free upwards. However, one stringent assumption of the model considered by the above authors is that all the interclaim times and the claim sizes are independent, which is in general not true in reality. In this thesis, we propose to analyze the Gerber-Shiu functions under various dependent structures. The main focus of the thesis is the risk model where claims follow a Markovian arrival process (MAP) (see, e.g., Latouche and Ramaswami (1999) and Neuts (1979, 1989)) in which the interclaim times and the claim sizes form a chain of dependent variables. The first part of the thesis puts emphasis on certain dividend strategies. In Chapter 2, it is shown that a matrix form of the dividends-penalty identity holds true in a MAP risk model perturbed by diffusion with the use of integro-differential equations and their solutions. Chapter 3 considers the dual MAP risk model which is a reflection of the ordinary MAP model. A threshold dividend strategy is applied to the model and various risk-related quantities are studied. Our methodology is based on an existing connection between the MAP risk model and a fluid queue (see, e.g., Asmussen et al. (2002), Badescu et al. (2005), Ramaswami (2006) and references therein). The use of fluid flow techniques to analyze risk processes opens the door for further research as to what types of risk model with dependency structure can be studied via probabilistic arguments. In Chapter 4, we propose to analyze the Gerber-Shiu function and some discounted joint densities in a risk model where each pair of the interclaim time and the resulting claim size is assumed to follow a bivariate phase-type distribution, with the pairs assumed to be independent and identically distributed (i.i.d.). To this end, a novel fluid flow process is constructed to ease the analysis. In the classical Gerber-Shiu function introduced by Gerber and Shiu (1998), the random variables incorporated into the analysis include the time of ruin, the surplus prior to ruin and the deficit at ruin. The later part of this thesis focuses on generalizing the classical Gerber-Shiu function by incorporating more random variables into the so-called penalty function. These include the surplus level immediately after the second last claim before ruin, the minimum surplus level before ruin and the maximum surplus level before ruin. In Chapter 5, the focus will be on the study of the generalized Gerber-Shiu function involving the first two new random variables in the context of a semi-Markovian risk model (see, e.g., Albrecher and Boxma (2005) and Janssen and Reinhard (1985)). It is shown that the generalized Gerber-Shiu function satisfies a matrix defective renewal equation, and some discounted joint densities involving the new variables are derived. Chapter 6 revisits the MAP risk model in which the generalized Gerber-Shiu function involving the maximum surplus before ruin is examined. In this case, the Gerber-Shiu function no longer satisfies a defective renewal equation. Instead, the generalized Gerber-Shiu function can be expressed in terms of the classical Gerber-Shiu function and the Laplace transform of a first passage time that are both readily obtainable. In a MAP risk model, the interclaim time distribution must be phase-type distributed. This leads us to propose a generalization of the MAP risk model by allowing for the interclaim time to have an arbitrary distribution. This is the subject matter of Chapter 7. Chapter 8 is concerned with the generalized Sparre Andersen risk model with surplus-dependent premium rate, and some ordering properties of certain ruin-related quantities are studied. Chapter 9 ends the thesis by some concluding remarks and directions for future research.

A valuable analytical tool to understand the event of ruin is a Gerber-Shiu discounted penalty function. It acts as a unified means of identifying ruin-related quantities which may help insurers understand their vulnerability ruin. This thesis provides an introduction to the basic concepts and common techniques used for the Gerber-Shiu analysis. Chapter 1 introduces the insurer's surplus process in the ordinary Sparre Andersen model. Defective renewal equations, the Dickson-Hipp transform, and Lundberg's fundamental equation are reviewed. Chapter 2 introduces the classical Gerber-Shiu discounted penalty function. Two framework equations are derived by conditioning on the first drop in surplus below its initial value, and by conditioning on the time and amount of the first claim. A detailed discussion is provided for each of these conditioning arguments. The classical Poisson model (where interclaim times are exponentially distributed) is then considered. We also consider when claim sizes are exponentially distributed. Chapter 3 introduces the Gerber-Shiu function in the delayed renewal model which allows the time until the first claim to be distributed differently than subsequent interclaim times. We determine a functional relationship between the Gerber-Shiu function in the ordinary Sparre Andersen model and the Gerber-Shiu function in the delayed model for a class of first interclaim time densities which includes the equilibrium density for the stationary renewal model, and the exponential density. To conclude, Chapter 4 introduces a generalized Gerber-Shiu function where the penalty function includes two additional random variables: the minimum surplus level before ruin, and the surplus immediately after the claim before the claim causing ruin. This generalized Gerber-Shiu function allows for the study of random variables which otherwise could not be studied using the classical definition of the function. Additionally, it is assumed that the size of a claim is dependant on the interclaim time that precedes it. As is done in Chapter 2, a detailed discussion of each of the two conditioning arguments is provided. Using the uniqueness property of Laplace transforms, the form of joint defective discounted densities of interest are determined. The classical Poisson model and the exponential claim size assumption is also revisited.

In this thesis, we consider a generalization of the classical Gerber-Shiu function in various risk models. The generalization involves introduction of two new variables in the original penalty function including the surplus prior to ruin and the deficit at ruin. These new variables are the minimum surplus level before ruin occurs and the surplus immediately after the second last claim before ruin occurs. Although these quantities can not be observed until ruin occurs, we can still identify their distributions in advance because they do not functionally depend on the time of ruin, but only depend on known quantities including the initial surplus allocated to the business. Therefore, some ruin related quantities obtained by incorporating four variables in the generalized Gerber-Shiu function can help our understanding of the analysis of the random walk and the resultant risk management. In Chapter 2, we demonstrate the generalized Gerber-Shiu functions satisfy the defective renewal equation in terms of the compound geometric distribution in the ordinary Sparre Andersen renewal risk models (continuous time). As a result, forms of joint and marginal distributions associated with the variables in the generalized penalty function are derived for an arbitrary distribution of interclaim/interarrival times. Because the identification of the compound geometric components is difficult without any specific conditions on the interclaim times, in Chapter 3 we consider the special case when the interclaim time distribution is from the Coxian class of distribution, as well as the classical compound Poisson models. Note that the analysis of the generalized Gerber-Shiu function involving three (the classical two variables and the surplus after the second last claim) is sufficient to study of four variable. It is shown to be true even in the cases where the interclaim of the first event is assumed to be different from the subsequent interclaims (i.e. delayed renewal risk models) in Chapter 4 or the counting (the number of claims) process is defined in the discrete time (i.e. discrete renewal risk models) in Chapter 5. In Chapter 6 the two-sided bounds for a renewal equation are studied. These results may be used in many cases related to the various ruin quantities from the generalized Gerber-Shiu function analyzed in previous chapters. Note that the larger number of iterations of computing the bound produces the closer result to the exact value. However, for the nonexponential bound the form of bound contains the convolution involving usually heavy-tailed distribution (e.g. heavy-tailed claims, extreme events), we need to find the alternative method to reinforce the convolution computation in this case.