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National Repository of Grey Literature 2 records found  Search took 0.01 seconds. 
Modelování přírodních katastrof
 Zuzák, Jaroslav ; Zimmermann, Pavel (advisor) ; Masec, Frant (referee)
This thesis introduces various approaches to natural catastrophe risk assessment in (re)insurance environment. Most emphasis and further elaboration is put on probabilistic models in comparison to the standard model as proposed by Solvency II. The outcomes of natural catastrophe modeling play an important role in the design of proper actuarial models related to catastrophe risk. More specifically it is shown that they can be entirely understood in a wider actuarial context, namely risk theory. Within the Solvency II framework, probabilistic model outcomes are translated by means of the proposed decomposition methodology putting them into a similar language of the standard formula in order to create the ability to compare different results implied by either probabilistic model or standard formula. This enables both comparison of the implied dependence structure of probabilistic model to standardized correlations assumed in Solvency II, and scenario year loss factors of Solvency II to implied damage factors of probabilistic models in defined cresta zones. The introduced decomposition methodology is illustrated by flood and windstorm model outcomes calculated on exposure data of Czech insurance companies and compared to the respective standard formula parameters and outcomes. Finally, other applications of the proposed decomposition methodology are introduced, such as measurement of diversification effect or blending of different results calculated by different models or even approaches to natural catastrophe risk assessment.
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Market segmentation and cluster analysis
 Zuzák, Jaroslav ; Vilikus, Ondřej (advisor) ; Hebák, Petr (referee)
This bachelor thesis deals with possibilities of statistic-analytical tools in market segmentation (i.e. a marketing concept), which is introduced as well. The theoretical part focuses on cluster analysis and its best-known algorithms, their assumptions and from those following possible usefulness and potential limitations. In the practical part a segmentation study of gallery and museum visitors is conducted on the basis of lifestyle and leasuretime activities variables. The resulting segments are profiled using other variables to create a more real-life image of the visitors and nonvisitors of galleries and museums.
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