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Riders
Sviták, David ; Hebák, Petr (advisor) ; Kocúrová, Barbora (referee)
Riders are growing more important as a part of insurance markets. The aim of this thesis is to introduce riders offered by a chosen insurance company in the Czech Republic. The next part is dedicated to the study of a structure of arranged riders in one year. A characteristic of riders and main covers a, which affect the number of arranged riders, are specified by using statistical methods. In the last part, clients are classified based on their owned riders by using cluster analysis. This thesis contains some recommenddations to create new riders.
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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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Analysis of production and consumption of electricity in Czech republic
Melichar, Vojtěch ; Arltová, Markéta (advisor) ; Vošta, Milan (referee)
This master thesis is divided into two parts. First part focuses on production and consumption of electricity in the Czech republic, describing sources of the production and their progress since 1990, considering also the main electricity consumers. The end of the first part focuses on the Box-Jenkins methodology, time series of electricity consumption between 1981 and 2008 are created as well as forecasted up to 2011. The second part of this thesis describes the cluster analysis. This is used for finding similarities of the 27 states of the European Union. Cluster analysis is applied for years 1990 and 2007, for both electric power production and electric power consumption.
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Zjišťování skupin podobných proměnných v systémech SAS a SPSS
Marková, Monika ; Řezanková, Hana (advisor) ; Húsek, Dušan (referee)
My diploma thesis focuses on the comparison of possibilities of the statistical software SAS and SPSS in the area of the factor and cluster analysis and the multidimensional scaling. They deal with the methods for identifying groups of the similar statistical values (variables). The ascertained relations among the variables can serve to decrease the proportion vectors of the variables, which describe the individual monitored objects (statistical units), which helps us to apply other various methods, for example the regression or discriminant analysis. By one of the ways for finding the similarity of variables in the cluster analysis or the multidimensional scaling is searching for their relations. Whereas the base of the factor analysis is the formulation of the relation between two variables by means of the covariances, eventually Pearson correlation coefficient, it is possible to use also coefficients of correlation for the cluster analysis and the multidimensional scaling, in some case other measures. The thesis describes mainly the command syntax of the procedures implemented in SAS and SPSS. The meaning of the individual parametres and the partial specifications of each command are explained. The results gained by various types of analyses are compared on the basis of the real dataset. The possibilities of the statistical software SAS and SPSS are evaluated in the conclusion and it is referred to their advantages or disadvantages. The attention is also paid, for example, to the form of the input dataset, to the quaility of outputs or to the partial methods.
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Analýza hedgeových fondov a hedgeových stratégií
Austová, Lucia ; Jílek, Josef (advisor) ; Halás, Vladimír (referee)
An objective of my graduation thesis is an analysis of hedge funds and hedge strategies while reflecting the distribution of the investments to right portfolio taking into account the risk. The main aim is to provide clear and consistent classification of whole variety of different hedge styles and strategies. There are plenty of different investment and trading strategies of hedge funds and their classification differs from analyst to analyst and from database to database. The work focuses on finding an alternative consistent classification of hedge funds which will lead to improvement of investment decisions of financial market participants, to effective distribution of the investment portfolio and therefore to elimination of undiversified risks. For the practical analysis I use real data of hedge fund returns of particular relevant time period. I focus on research and description of possible methods of hedge fund classification mentioning their pluses and minuses. After passionate evaluation of each method I have chosen two methods according to which I classify the hedge funds datasets and finally I compare the results of both. The theoretical part of work focuses on definition of hedge funds, hedge styles and strategies, pluses and minuses as well as risk accompanying particular strategy.
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Lifestyle - A Research Topic And a Criteria for Market Segmentation
Kuncová, Jana ; Koudelka, Jan (advisor) ; Udatný, Jiří (referee)
The thesis considers lifestyle with emphasis on its applicability in marketing practices. The first part characterises the social research projects that took place recently in the Czech Republic. The second part concentrates on the principles and methods of market segmentation, followed by an example of financial market segmentation based on features of lifestyle. The final part contains recommendations related to marketing strategies towards chosen segments.
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Clustering methods for large datasets
Vilikus, Ondřej ; Fialová, Hana (advisor) ; Húsek, Dušan (referee)
S rostoucím množstvím shromažďovaných a ukládaných dat vzniká potřeba shlukovacích metod, které by se dokázaly vypořádat i s rozsáhlými datovými soubory. Proto se objevuje množství nových algoritmů, vycházejících jak ze statistických přístupů, tak i z oblasti strojového učení. Cílem této diplomové práce je stručně představit dostupné metody shlukové analýzy a zhodnotit jejich silné a slabé stránky při analýze velkých souborů. Obsahem teoretické části je shrnutí základních pojmů a principů, které jsou všem metodám společné, a popisu nejznámějších metod shlukové analýzy. Ten obsahuje stručné vysvětlení, na jakém principu fungují a jaké výhody nebo případné nedostatky můžeme při jejich použití očekávat. Praktická část práce je věnována vlastnímu testování osmi metod dostupných v komerčním (SPSS, S-PLUS, STATISTICA) nebo akademickém (Weka) softwaru. Pro testování jsou použity umělé soubory se specifickými charakteristikami, které jsem vygeneroval pomocí vlastního algoritmu. Ten je rozšířením Neyman-Scottova procesu a kromě sférických shluků generuje i shluky nepravidelných tvarů. Výsledky potvrzují očekávání vycházející z teoretických předpokladů. Přinášejí však možnost kvantifikace vlivu charakteru dat na vhodnost jednotlivých metod.
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Web Usage Mining
Benkovská, Petra ; Jelínek, Jiří (advisor) ; Soska, Ján (referee)
General characteristic of web mining including methodology and procedures incorporated into this term. Relation to other areas (data mining, artificial intelligence, statistics, databases, internet technologies, management etc.) Web usage mining - data sources, data pre-processing, characterization of analytical methods and tools, interpretation of outputs (results), and possible areas of usage including examples. Suggestion of solution method, realization and a concrete example's outputs interpretation while using above mentioned methods of web usage mining.
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