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Determinants of the average daily rate of Peer-to-peer accommodation in the Czech Republic
Řežábek, Pavel ; Pavlíček, Jaroslav (advisor) ; Schwarz, Jiří (referee)
This thesis investigates which characteristics of peer-to-peer accommodation affect its average daily rate. The study utilizes a unique dataset created with data on all accommodation offers in the Czech Republic, made directly from data downloaded from airbnb.com, which is the largest platform presenting short-term rentals outside hotels. The information about amenities and reviews of individual properties offering accommodation are firstly categorized. The effects of each such category together with information about size and location on the average daily rate are then investigated using the ordinary least squares method. The following parameters are found to have have the most significant effect on the average daily rate: location in Prague, the maximum number of occupants, hotel-type equipment, and luxury amenities.
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Analysis and Aspects of Art as an Alternative Investment and its Price Determinants
Mozolikova, Alica ; Benáček, Vladimír (advisor) ; Moravcová, Hana (referee)
The purpose of this thesis is to examine the potential of art as an alternative investment. To do this, we start with a brief history of art market that is followed by an analysis of art market structure. We cover numerous risks affecting the behavior in the market subject to information asymmetry. As far as the feasibility of art as an investment is concerned, we identify different types of alternative investment and compare their potential. Despite high opacity of the art market, more data are being made available giving us an opportunity to present a clearer explanation of the current state of the art market. A question has to be asked, does the value of art solely depend on the subjectivity of human taste or on an opportunity to speculate? The subject of the detailed discussion are, both, internal and external factors, which influence the value of artworks, and hence the sale price. Using econometric analysis of auction records, we aim to uncover objective factors, which determine the sale price. The analyses lead to a conclusion that the price determinants, the most notable of which are auction houses and auction location, affect the sale price to a different extent. Yet, regardless the price, our subjective personal pleasure from a particular art piece might be crucial. JEL Classification Key...
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Price Determinants of Flats Purchased for the First Time in Prague
Pelnář, Daniel ; Cahlík, Tomáš (advisor) ; Nevrla, Matěj (referee)
Being able to correctly estimate the true intrinsic value of a flat is important for various economic agents. This paper is concerned with the price determinants of first-time- purchased flats in Prague. It is mostly about the hedonic pricing model and its applications using data from Vivus which is one of the larger flat developers operating in Prague. Ordinary least squares was the estimation method of choice in this study. The main results are as follows. The residual analysis showed no extremely overvalued or undervalued flats based on our chosen models. Moreover, the estimated increase in prices of average sized flats in Uhříněves was 36.76% from 2017 to 2019. This is a much larger magnitude if compared with the period of the financial crisis where an average sized flat in Na Vyhlídce increased in its price by 12.83% from 2007 to 2009. It is interesting to see that even during a recession, the prices of Prague flats were raising.
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Price Determinants of Art Photography at Auctions
Habalová, Veronika ; Šopov, Boril (advisor) ; Bauer, Michal (referee)
In the recent years, prices of art have repeatedly broken records, and the interest in investing in fine art photography has been growing. Although there is plenty of research dedicated to studying prices of paintings, fine art photography has been largely overlooked. This thesis aims to shed light on identifying price determinants for this particular medium. A new data set is collected from sold lot archives of Sotheby's and Phillips auction houses, which also provide images of some of the sold items. These images are then used to create new variables describing visual attributes of the artworks. In order to inspect the effect of color-related predictors on price, four different methods are discussed. Color is found to be significant in OLS model, but the effect diminishes when model averaging is applied. Machine learning al- gorithms - regression trees and random forests - suggest that the importance of color is relatively low. The thesis also shows that expert estimates can improved by incorporating available information and using random forests for prediction. The fact that the expert estimates are not very accurate sug- gest that they either do not use all the available information or they do not process it efficiently. 1
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Analysis of Price Determinants in the Art Market
Mizeráková, Elena ; Šopov, Boril (advisor) ; Moravcová, Hana (referee)
1 Abstract What qualities make the best-selling artworks worth so much? Does the in- terest of the general public influence the probability that the art will be sold in auction? The art market research focuses on various aspects that affect the potential of art as an investment. The boom of big data offers a unique op- portunity to utilize its global impact and improve the present models with a novel measure. Into the econometric analysis of auction results the thesis im- plements a change in the Internet searching volume provided by Google Trends as a reflection of the taste and the state of mind of society. The subject of the detailed discussion are not only the price determinants, but also the factors that affect the selling probability. The findings lead to a conclusion that the proposed measure based on Google Trends is significant for determining both, the odds of selling the artwork and its price. Beside that, an important effect on the price and the probability have auction houses, the personal brand of the artist or the medium of artwork. JEL Classification D44, C25, F23, Z10, Z11 Keywords art market, auctions, Google Trends, prices, price determinants, odds of selling Author's e-mail elena.mizerakova@gmail.com Supervisor's e-mail boril.sopov@gmail.com
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