Μοντέλα χρεοκοπίας με στρατηγικές μερισμάτων
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Keywords
Χρεοκοπία ; Συνάρτηση Gerber-Shiu ; Μετασχηματισμοί LaplaceAbstract
This diploma thesis deals with various ruin measures and the type of distribution of dividends paid to insured persons for stochastic surplus processes where there is a link between the intermediate times of risk exposure and the corresponding amounts of compensation required. In particular, the last 3 chapters examine the case where dependency is implemented through a FGM copula. The six chapters that follow for each of the cases examined and the corresponding stochastic surplus processes will examine the different forms of the Gerber-Shiu function as well as the expected dividends paid by the insurer up to the time of bankruptcy. The first chapter provides a detailed description of the classical model of risk theory and presents the results obtained by the Gerber-Shiu function for the aforementioned model. In the second chapter we study the classical model with a fixed dividend strategy and analytical results are presented for Gerber-Shiu's function and the moments of discounted dividends under the above-mentioned strategy in the case of the classical model. The third chapter examines the classical model with a threshold dividend strategy. Integral equations for the penalty function are written, the probability of total bankruptcy, the time of this and the surplus the moment before bankruptcy and deficit during bankruptcy are studied. In Chapter 4, as in the next two chapters, we study the classical model equipped with the FGM copula, the differences that arise in the various models with this coupling are presented, and are searched for all-differential equations for the penalty function, marginal conditions as well as analytical expressions of the Laplace transform for the time of bankruptcy. In particular, in the classic model with a dividend strategy strategy equipped with FGM copula, apart from the analysis of the Gerber-Shiu function, reference is also made to the expected dividends received.