Kaunas – svarbus transporto, mokslo ir kultūros bei Kauno apskrities, miesto savivaldybės, Kauno rajono savivaldybės centras, antrasis pagal dydį Lietuvos miestas, kuriame aktyviai vykdomi nekilnojamojo turto sandoriai ir šio turto vertinimas.. Tyrimo tikslas – išanalizuoti ir palyginti skirtingais metodais nustatytas nekilnojamojo turto vertes. Tyrimo objektas – vieno, dviejų, trijų, keturių kambarių butai ir namai esantys Kauno mieste. Atliekant šį butų ir namų vertinimo metodų palyginimą, buvo surinkti duomenys apie 2013 metų ir 2014 metų pirmojo ketvirčio nekilnojamojo turto vertes, vertinant skirtingais metodais. Baigiamajame darbe aptariama nekilnojamojo turto vertinimas bei jo metodai bei funkcijos. Pateikiama bendroji Kauno miesto apžvalga. Supažindinama smulkiau su nekilnojamojo turto vertinimo metodais naudotais darbe. Pateikti atlikto tyrimo rezultatai, parodo nekilnojamojo turto vertinimo metodų skirtumus. Taip pat skirtingų nekilnojamojo turto vertinimo metodų pliusus ir minusus. Bei Nekilnojamojo turto vertės priklausomybę nuo tam tikrų veiksnių, vertinant skirtingais vertinimo metodais. / Kaunas is an important center of transport, science and culture, Kaunas city is the center of municipality and district municipality, as well as the central part of the country and the second largest city in Lithuania. The aim of the research - to analyze and compare fixed property values by different methods. The object of the research – houses and apartments consisting of one, two, three, four bedrooms in the Kaunas city. In the comparison of the assessment methods, the data of real estate value of the year 2013 and the first quarter of 2014, based on evaluation by different methods, was collected. This thesis deals with real estate valuation, its methods and functions. A general overview of Kaunas is provided. The methods of real estate valuation applied in research are explained in detail. Research results show the differences between real estate valuation methods. Also, the pros and cons of each method of valuation of real estate are presented. The dependence of the value of real estate on some factors when using different methods is revealed as well.

The thesis aims to explore patterns and methods that lead to valuation of real estate assets through a process of hotel appraisal. It therefore focuses on a hotel as a special type of property. It seeks to derive a general procedure for determination of value of a property used as an asset for operation of a hotel through combination of established business valuation and property valuation methods. The first part of the evaluation mechanism will be quite similar to the valuation of a company process. Emphasis is placed on the analytical part involving examination at the locality, the strategic and financial analysis and the determination of the constituents that generate value. In the part on property valuation, the use of valuation methods, determination of investment costs and discount rates are discussed in greater detail. The second part focuses on the valuation of real estate assets, namely on the need to exclude the tangible and intangible assets unrelated to the hotel property. The thesis concludes with a recommendation of a procedure that would result in establishment of market value of the hotel's property itself.

不動產估價獨立客觀為金融體系穩定的關鍵因素，而客戶影響是探討估價獨立性的重要議題。過去多以問卷調查、實驗設計或深度訪談方式進行相關研究，卻難以證明不動產估值受到客戶影響之真實情形。本文蒐集公開資訊觀測站相同不動產其買賣雙方各自委託之估值及其成交價，在雙方均有影響估值之動機前提下，以獨立樣本t檢定及Wilcoxon-Mann-Whitney檢定驗證其估值溢價率以及估值差異比率在不同變數情況下之差異情形。實證結果顯示，不動產估值因客戶為買方或賣方不同而有顯著差異，另經驗老練客戶將使不動產估值差異更為擴大，而不動產採標售方式買賣者，其估值差異比率遠較採議價方式高。 / The independent objective of real estate appraisal is the key factor of the stability of the financial system, while the client influence is an important issue of the independence of valuation. In the past, more of the relevant research by questionnaire, experiment or interview, but it is difficult to verify the real situation of the client influence. This paper collected the cases of same real estate that both the buyer and the seller commissioned the valuation and the transaction price from MOPS, under the premise that both parties have the motivation to influence the valuation, to examine the valuation premium ratio and valuation difference ratio with the independent sample t test and Wilcoxon-Mann-Whitney test. The results show that the real estate valuation is significantly different from clients, and experienced clients will make the real estate valuation differences more widened. However, the valuation difference ratio of the transactions by auction is much higher than the valuation difference ratio of the transactions by bargain.

The main purpose of this study is to develop a predictive model capable to forecast residential real estate prices in the city of Prague using Artificial Intelligence methods. The first part of this study discusses fundamentals of Artificial Neural Networks and Fuzzy Inference Systems in the context of real estate valuation. The second part demonstrates a development and testing of such models using a dataset of real estate market transactions. In the third part, results are compared to Multiple Regression and an explanatory power of each model is evaluated. Conclusions of this research are: (1) Artificial Neural Networks and Fuzzy Inference Systems give more accurate estimates of market values of residential real estates than Multiple Regression; (2) Artificial Neural Networks and Fuzzy Inference Systems represent an efficient way of modeling and analyzing residential real estate prices in Prague.

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.

Master thesis focuses on selected real estate with mortgages. Opinions on displaying processes for buying a property for a mortgage loan in the created graphic process of the Czech Banking Association. Explaining legislation on mortgage banks or building societies.

The nature of that problem is to determine the value of the property in comparison to the value of construction supplies for the same property. The value is determined on the supply of building production and also by using the usual methods for the valuation of real estate.

Investing finances into housing is for most people in their life one of the volume largest investment and therefore it is important to rethink these individual financial steps properly, to ensure the continued ability to repay obligations and without unwanted load additional charges. With the rising market values of real estate is also rising popularity of invest in housing. Some problemes are reducing real wages, although the average wage increase in annual comparison, and so it is for most people the biggest problem ever to get a mortgage loan. More of young people haven't confident their job, they are temporary employment or their wages are to low a this people represent a high risk for banks to become insolvent and it is really hard to get a mortgage loan for young people. This master´s thesis is modelling some finances very usefully, effective and reaching the proceeds from the purchase of real estate.

In the doctoral thesis is an analysis of comparative method for family houses according to the valuation regulations. The analysis focuses on individual characteristics and qualitative zones and their impact on set price. The analysis is made by specially created database of offer prices of family houses and by comparing with the cost method according to the valuation regulations. Based on the results of the analysis is designed a new form of characters and qualitative zones. The thesis is concluded by summarizing and discussion of results and their contribution.

This thesis deals with a comparison of the market prices of Brno family houses. The compared prices are estimated using the comparative way based on the price regulations and using the comparative method. A new coefficient for the comparative method is proposed in the thesis. This coefficient takes into account the influence of the distance of the estimate property from the city centre in the connection with the position. One of the main reasons to introduce this coefficient was to obtain the best result when estimating the price, the result which is the closest to the required market price. The use of the coefficient of the global position may lead to better results of the price estimate, especially in bigger cities where this influence is revealed the most.