The aim of this thesis is the valuation of Komerční banka, a.s. The specifics of the valuation of banks are described in the first part of this thesis. The second part is devoted to a description of the valuation methods. Komerční banka, a.s. is valued in the third practical part. The first is a brief description of Komerční banka a.s., followed by financial and strategic analysis. The financial plan is compiled on the basis of the analyses. In the final part the valuation by selected methods is done and the final value is determined.

The aim of the thesis is to valuate a company operating in the chemical industry using the income valuation approach as of January 1, 2015. At first, the company valuated will be analyzed from the perspective of strategic and financial analysis. Subsequently an opinion on the future prospects of the company will be issued, and provided that all the criteria needed for the usage of discounted cash flow methods are met, the company will be valuated using Discounted Cash Flows method, Economic Value Added method and Capitalization of earnings method. Book value method will be used as an additional method of valuation. In conclusion, a summary valuation of the company will be carried out, which will be subjected to a risk analysis using Monte Carlo simulation method.

The thesis focuses on business valuation. In the first part the methodology of valuation is described and then it is applicated to find out the market value of the company Hollandia Karlovy Vary a.s., which produces yogurts and yogurt products.

The challenge of resolving land use allocation and policy questions depends to a large degree on the conversion of data into information, and the effective integration of information into the decision process. Land evaluation is one of the fundamental means of generating information for land planning. Information products have however, been inconsistently and ineffectively used in the decision process. This thesis develops a decision centered approach to land evaluation as a response to this concern. Included in this development is a description of important theoretical concepts, as well as a practical demonstration of the use of decision support systems as a design approach. Initially, a conceptual model is introduced illustrating the technical and use components of information generation, as well as the adaptive design cycle. Various terms and techniques involved in the technical aspects of land evaluation are reviewed. Decision making concepts including decision structure, environment, analysis, and criteria are outlined. Three existing methods of land evaluation are then compared from a use or decision making perspective. Having completed a review of current approaches, Decision Support Systems are introduced as a logical progression towards a decision centered approach. Decision Support System design is demonstrated using a portion of the Central Fraser Valley Regional District as a case study area combined with an interactive microcomputer land planning tool (LANDPLAN). The demonstration emphasizes the advantages of the flexible, interactive capabilities of Decision Support Systems in aiding the decision process. Iterative design is also promoted with several needs identified if a more complete system is to be developed. In particular, data on strategic long term supply and demand factors is required, as well as continuous rating functions for assessing land performance. / Science, Faculty of / Resources, Environment and Sustainability (IRES), Institute for / Graduate

This master's thesis deals with the valuation of cultural institution the Oskar Nedbal Theatre in Tabor and its aim is to estimate the value of this theatre to 30th June 2012 for the purpose of its founder the South Bohemian Region and compare this value with a subsidy paid to the theatre as a contributory organization. The value of the organization is determined by the method of contingent valuation based on the question related to people's willingness to pay for the preservation of the theatre and supplemented by Victor S. Yocco method for measuring three factors of the hypothetical value. The issue of cultural institutions valuation is not yet much explored area and mainly in the Czech Republic has not yet been comprehensively worked out and this thesis offers a practical view on one of the possible methods of valuing cultural goods and organizations.

This master's thesis deals with the valuation of cultural institutions. Its aim is to estimate the value of cultural contributory organization Hussite Museum in Tabor to 30 th June 2012 for the purpose of its founder, which is the Ministry of Culture of the Czech Republic, and then compare this value with a subsidy paid from the state budget. For this purpose the forecast of population of the Czech Republic and the Tabor region and the forecast of attendance of Hussite Museum in 2012 is made. The value of the organization is determined by the method of contingent valuation based on the questions related to WTP and WTA and supplemented by Victor S. Yocco method for measuring three factors of the hypothetical value. The paper aims to describe the issue of cultural institutions valuation as complex as possible, because this issue has not yet been comprehensively worked out and in the Czech environment it is not yet much explored area.

KOVÁČ, Peter: Business valuation of DUDÁK Strakonice Burgher's Brewery [Diploma thesis] / Peter Kováč. University of Economics Prague. Faculty of Finance and Accounting; Department of Finance and Business valuation. Supervisor: Ing. Pavel Svačina, Ph.D. Qualification degree: Master. Prague : FFÚ VŠE, 2013. 100 pages. This diploma thesis deals with the business valuation of DUDÁK Strakonice Burgher's Brewery. The aim of the diploma thesis is to determine the market value as of 1. 1. 2011. The company is specific in that it is the last brewery in the Czech Republic to still be owned by a town. The purpose of the diploma thesis rests in finding appropriate value for owners and lenders, which can take in the event of a sale an informational character for the seller. The valuation is independently done by DCF Entity method, Multiples method and Book value method. The work is divided into seven chapters that follow on each other and lead to the determination of the enterprise value. The author uses informational and statistical databases that contribute to the greater credibility of the entire valuation.

This thesis deals with a relatively new issue in the Czech Republic, which is valuing cultural organizations. The general framework for the valuation of non-profit cultural organization is analysed in the theoretical part. It includes a discussion of the importance of culture for society, the characteristics of non-profit organizations and subsequently defining the potential value of the concept of cultural organizations, reasons and methods for valuation of such organizations. Special focus is paid to the transformation of the Prague theater net. The aim of the practical part is to determine the approximate value which the czech society would lose, if the prague theatre Činoherní klub terminates its activities due to financial reasons. Contingent valuation method is applied as a procedure, which is based on detection of individual willingness to pay (WTP) or willingness to accept compensation (WTA), through a questionnaire survey. There is also a determination of the status of the valued theater at the Prague theater market in the practical part.

Economic Valuation of the natural patrimony: Protected Natural AreasThis paper offers some knowledge about the utility of Economic Valuation of Assets out of  market methods, to allow management in general and as a guide to the planning of natural areas with valuable ecologic and landscaping aspects. Here, I show the importance of the Protected Natural Areas (ANP) in the national economy and their economic value. I describe the most used techniques in the valuation of ANPs with special attention to the direct using values through the application of cost of travel and contingent valuation methods.As an example of the use of these techniques, I present the application results at the Private Conservation Area-El Cañoncillo Natural Forest, with the objective to analyze the pertinence of the economic valuation by the adoption of conservation practices. / El presente artículo brinda conocimientos sobre la utilidad de los métodos de valoración económica de los bienes sin mercado, tanto para su gestión en general como para que sirva de guía para la planificación de áreas naturales ecológica y paisajísticamente valiosas en particular. Muestra la importancia de las áreas naturales protegidas (ANP) en la economía nacional y su valoración económica. Se describen las técnicas más usadas en la valoración de las ANP, con especial atención en los valores de uso directo a través de la aplicación de métodos de costo de viaje y de valoración contingente (CVVC).Como ejemplo de uso y potencial de estas técnicas se presentan los resultados de su aplicación en el Área de Conservación Privada Bosque Natural El Cañoncillo, con el objetivo de analizar la viabilidad de la valoración económica por medio de la adopción de prácticas de conservación.

Markttransparenz in Deutschland wird durch die Gutachterausschüsse und auch durch verschiedene private Akteure am Immobilienmarkt realisiert. Insbesondere in Teilmärkten mit geringen Transaktionszahlen stellt die Markttransparenz eine Herausforderung dar, da nicht ausreichend Daten zur Analyse der jeweiligen Märkte zur Verfügung stehen. Aus diesem Grund bedürfen diese Märkte einer tiefergehenden Untersuchung, um auch hier eine ausreichende Markttransparenz zu erreichen. Die Vielfältigkeit der Teilmärkte mit geringen Transaktionszahlen muss dafür differenziert betrachtet werden. Im Rahmen der Arbeit werden zunächst Unterschiede in den Eigenschaften der Märkte mit geringen Transaktionszahlen untersucht. Hierzu wird mittels einer qualitativen Untersuchung von Leitfadeninterviews sowie der Literatur zum Thema eine Theorie zur Systematisierung der Märkte gebildet. Differenziert für einzelne Märkte kann mit dieser Strukturierung eine passende Auswertestrategie entwickelt werden. Anschließend erfolgt die Untersuchung von verschiedenen Daten, die bereits in den Märkten mit geringer Transaktionszahl genutzt werden. Kauffälle, die unvollständig erfasst sind, werden derzeit bei Auswertungen vollständig ausgeschlossen (Fallweiser Ausschluss). Teilweise fehlt jedoch nur eine Information für eine multivariate Analyse. Im Rahmen der Arbeit wird untersucht, ob und mit welchen Methoden diese Datenlücken geeignet gefüllt werden können, um eine höhere Genauigkeit in den Analysen auch mit wenigen Daten zu erhalten. Als Methoden werden neben dem Fallweisen Ausschluss eine Mittelwertimputation sowie die Auffüllung der Datenlücken mittels Expectation-Maximization und Random-Forest-Regression untersucht. Darüber hinaus wird das Expertenwissen, das in verschiedenen Formen von Expertisen (Befragungen, Angebotspreise, Gutachten) geäußert werden kann, untersucht. Zur Erlangung eines Überblicks, wird zunächst das Expertenwissen im Rahmen einer quantitativen Befragung näher betrachtet, um Handlungsweisen und Unterschiede von Experten aus verschiedenen Gruppen aufzudecken. Anschließend werden intersubjektive Experten- und Laienbefragungen im Kontext der Immobilienbewertung ausgewertet sowie Angebotspreise, die von Maklern und ohne Makler vermarktet werden, im Verhältnis zu den realisierten Kaufpreisen untersucht. Da die untersuchten zusätzlichen Daten wie Angebotsdaten oder Expertenbefragungen in einigen Teilmärkten nicht zur Verfügung stehen oder nur mit hohem Aufwand erzeugt werden können, sind alternative Nutzungsansätze notwendig. Hierzu werden zwei Methoden auf ihre Eignung hinsichtlich räumlich zusammengefasster Auswertungen geprüft. Der Vergleich erfolgt zur in der Praxis etablierten multiplen linearen Regressionsanalyse. Zum einen werden die geographisch gewichtete Regressionsanalyse, die lokale Märkte besser abbilden kann, zum anderen die künstlichen neuronalen Netze, die Nichtlinearitäten besser abbilden können, angewendet. Im Ergebnis zeigt sich, dass eine Strukturierung der Märkte mit geringer Transaktionszahl möglich ist. Eine sinnvolle Strukturierung erfolgt anhand der Grundgesamtheit des jeweiligen sachlichen/-räumlichen Marktes. Ebenso kann eine Differenzierung nach ländlichen und urbanen Räumen erfolgen. Mit Imputationsmethoden können die Ergebnisse von Regressionsanalysen deutlich verbessert werden. Selbst bei einem großen Vorkommen von Datenlücken in unterschiedlichen Parametern kann eine Auswertung noch gute Ergebnisse in der Größenordnung der vollständigen Kauffälle liefern. Auch mit der simplen Methode der Mittelwertimputation kann ein gutes Ergebnis erzielt werden. Experten im Bereich der Immobilienbewertung haben die unterschiedlichsten beruflichen Herkünfte. In ihrer Arbeitsweise lassen sich jedoch keine wesentlichen Systematiken feststellen. Lediglich bei der Nutzung von Daten können Systematiken aufgedeckt werden. Expertenbefragungen weisen grundsätzlich hohe Streuungsmaße auf. Die Streuungsmaße werden dann reduziert, wenn bei den Befragungen Einschränkungen beispielsweise durch eine vorgegebene Skala oder durch vorgeschlagene Werte erfolgen. Weitere Untersuchungen sind dahingehend notwendig. Auch die Abschläge zwischen Angebotspreisen und Kaufpreisen, aber auch die Anpassung von Angebotspreisen im Vermarktungszeitraum, weisen hohe Streuungsbreiten auf. Einen signifikanten Unterschied zwischen der Vermarktung mit oder ohne Makler kann in der untersuchten Stichprobe nicht nachgewiesen werden. Sowohl die Nutzung der geographisch gewichteten Regressionsanalyse (GWR) als auch die Nutzung von künstlichen neuronalen Netzen (KNN) bieten bei der Auswertung von räumlich zusammengefassten Daten in einer Kreuzvalidierung einen Vorteil. Dies lässt darauf schließen, dass die Märkte sowohl räumlich inhomogen als auch nichtlinear sind. Zielführend erscheint eine Kombination der geographischen Komponente mit nichtparametrischen Ansätzen wie dem Lernverfahren der KNN. / In Germany market transparency is realised by expert’s committees and due to the publication of market reports and market values and by various private players in the real estate market. In sub-markets with low transaction numbers, market transparency is a challenge because not enough data is available to analyse the respective markets. These markets require a more in-depth investigation to achieve sufficient market transparency. The diversity of sub-markets with low transaction numbers must be considered in a differentiated way. In the context of this work, differences in the characteristics of markets with a small number of transactions are examined. A theory for the systematisation of these markets is formed, using a qualitative investigation of guideline interviews and literature on the topic. Differentiated for individual markets, a suitable evaluation strategy can be developed using the proposed structuring. Subsequently, the analysis of different data, which is already used in real estate valuation, is carried out to investigate its usability for regions with few transactions. Purchase cases which are recorded incompletely, are today excluded from evaluations (case-wise exclusion). However, most of the time only one or two pieces of information for multivariate analysis are missing per case. It is examined whether and with which methods these data gaps can be filled suitably. Besides the case-by-case rejection (default method today), a mean-value-imputation, as well as the filling of data gaps using Expectation-Maximization and Random-Forest-Regression are investigated. Furthermore, the expert’s knowledge, which can be expressed in different forms of expert’s opinions (surveys, offer prices, expert reports), is examined. First of all, the expert knowledge, in general, is examined more closely within the framework of a quantitative survey to uncover patterns of action and differences between experts from different groups. Subsequently, intersubjective expert and layman surveys are evaluated in the context of real estate valuation. Additional offer prices, marketed with or without real estate agents, are compared to the realised purchase prices. Since the additional data examined, such as the supply data or the expert surveys, is not available in some sub-markets or can only be generated at great expense, alternative approaches to utilisation are necessary. For this purpose, two methods are tested for their suitability with regard to spatially summarised data. A comparison to the classically used linear regression analysis is made. On one hand, the geographically weighted regression analysis, which represents local markets more accurately, and the artificial neural networks, which are more suited to represent non-linearities, are applied. The result shows that a systematisation of markets with a low number of transactions is possible. A structuring based on the population of the respective functional/spatial sub-market takes place. It is also possible to differentiate between rural and urban areas. With imputation methods, the results of regression analyses can be improved significantly. Even if there are large numbers of data gaps in different parameters, an evaluation can still provide adequate results in comparison to an analysis with complete purchase cases if the overall sample is big enough. Already the simple method of mean-value-imputation leads to good results. Experts in the field of real estate valuation have a wide variety of professional backgrounds. However, significant systematics cannot be identified in their working methods. Different behaviour can only be identified by the usage of different data sources. Expert surveys generally show a high degree of dispersion. This degree of dispersion is reduced if the surveys are restricted, e.g. by a given scale or suggested values. Further investigations on these topics are necessary. The discounts between offer prices and purchase prices as well as the adjustment of offer prices within the marketing period are showing a high degree of dispersion. A significant difference between marketing with or without an agent cannot be proven in the examined sample. Both, the use of geographically weighted regression analysis and the use of artificial neural networks (ANN) offer an advantage when evaluating spatially summarised data in cross-validation. This leads to the conclusion that the markets are both geographically inhomogeneous and non-linear. A combination of the geographic component with non-parametric approaches such as the learning procedure of the ANN is appropriate.