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Cusp catastrophe theory: Application to the housing market
Kořínek, Vojtěch ; Kukačka, Jiří (advisor) ; Nevrla, Matěj (referee)
The bachelor's thesis applies the stochastic cusp catastrophe model to the housing market of the United States. Weekly data over the period from 2007 to 2017 are used. The current catastrophe theory literature related to the housing market is reviewed, the models found are assessed and expanded. Specifically, we have identified three deficiencies of the catastrophe models applied to housing market in the current literature and our contribution lies in the elimination of these deficiencies. In order to satisfy the constant volatility assumption of the model, the state variable is normalized by the estimated volatility derived from GARCH. Furthermore, multiple control variables are added to the model to represent the activity of fundamentalists and chartists. The results suggest that the cusp catastrophe model fits the data better than the linear and logistic models. The normalization of the state variable improves the model performance while the introduction of the additional control variables does not produce better results. Keywords Housing market, catastrophe theory, stochastic cusp catastrophe model, hous- ing bubble, real estate, fundamental investors, speculation. 1
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Consequences of Implementation of Video Assistant Referee in Fortuna Liga
Habáň, Ondřej ; Krištoufek, Ladislav (advisor) ; Nevrla, Matěj (referee)
The thesis deals with the issue of the Video Assistant Referee in football. It evaluates the consequences of its implementation in Czech Fortuna Liga on the sample of 678 matches held during two and half seasons. The results from the models designed to treat count data were compared with relevant literature. In the form of both simple and multiple regression with additional control variables was investigated the relationship between VAR and the set of match- changing incidents, including yellow cards, red cards and penalty kicks, and the relationship between VAR and errors of on-pitch referees. The terms presence of VAR, VAR interventions and VAR as the whole were di erentiated. Whereas a significant statistical association of VAR as the whole was not revealed for yellow and red cards, a 56% increase in the number of penalties associated with VAR as the whole significantly performed. Furthermore, the negative and highly significant 118% association of the presence of VAR was reckoned in the case of errors of on-pitch referees. Subsequently, the percentage decreased due to VAR interventions, however, not su ciently to reveal a negative and significant association in errors of on-pitch referees for VAR as the whole. The exception created errors based on factual decisions. JEL Classification Z21, F21, Z29,...
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Asset pricing: Downside risk across U.S. industries
Palovič, Peter ; Nevrla, Matěj (advisor) ; Kočenda, Evžen (referee)
This thesis investigates the comparative relationship between the traditional CAPM and the downside risk CAPM. It proposes an asset pricing model in which the traditional CAPM beta and DR-CAPM beta are the risk factors. The goal of this thesis is to examine whether DR-CAPM beta represents a significant risk factor that could be used when computing the risk premium of the portfolio in the market. Therefore, this thesis referred to the Fama- MacBeth two-stage regression model that was applied over monthly data of 48 US industries' realized returns ranging from January, 1970 to January, 2021. Results indicate a non-significant relationship between the risk fac- tors (traditional and downside beta) and expected return. Hence, there is no evidence that both factors have any significant explanatory power in the cross-section of stock returns. Moreover, we performed a robustness check of the results using univariate models, relative beta and unconditional approach. All of these models confirmed our results from the conditional approach. Keywords: Asset pricing, CAPM, DR-CAPM, Downside risk, Fama-MacBeth two-stage regression Author's email: 64770339@fsv.cuni.cz Supervisor's email: matej.nevrla@gmail.com
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Spatial analysis of Airbnb apartment locations in Prague
Kroutil, Filip ; Pertold-Gebicka, Barbara (advisor) ; Nevrla, Matěj (referee)
This paper investigates the determinants of the spatial distribution of Airbnb listings in Prague, the capital city of the Czech Republic, and compares it with the distribution of traditional accommodation units such as hotels. The analysis is based on two datasets, one containing all 14 864 Airbnb listings in Prague in November 2019 and the other including a snapshot of 864 hotels from March 2020. Local indicators of spatial association and traditional OLS regression were used to study the determinants and differences between the distributions. The results show a simpler and more centered distribution in the case of Airbnb units. The study also provides a model describing Airbnb density in each municipal district with high predicting power. Insights from this thesis could help understand the principles behind Airbnb dispersion and so create a basis for future regulations of this relatively new market segment.
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Demand for Non-Residential Parking in Prague
Šarboch, Matěj ; Šťastná, Lenka (advisor) ; Nevrla, Matěj (referee)
Parking is an important issue of everyday life. Nowadays, as the amount of cars is rising, to find a free parking space is paramount. There are issues such as cruising for parking and parking spillovers, which need to be dealt with using sensible parking regulation. This regulation should represent a compromise between the municipality, the residents and the drivers. To know the effects of any regulation, we first need to examine how the demand for non-residential parking is affected and by which factors. This thesis is trying to identify the factors that affect the demand for non-residential parking and to what extent. To model the parking demand, data from Golemio Prague City Data is used. The main results are that the demand for parking is negatively affected by price and that it is price inelastic. It is affected differently in different parking zones and varies during the week and the year. The results could serve as a tool for the municipality of Prague to handle this issue in eventual future reforms of the system.
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Cusp catastrophe theory: Application to the housing market
Kořínek, Vojtěch ; Kukačka, Jiří (advisor) ; Nevrla, Matěj (referee)
The bachelor's thesis applies the stochastic cusp catastrophe model to the housing market of the United States. Weekly data over the period from 2007 to 2017 are used. The current catastrophe theory literature related to the housing market is reviewed, the models found are assessed and expanded. Specifically, we have identified three deficiencies of the catastrophe models applied to housing market in the current literature and our contribution lies in the elimination of these deficiencies. In order to satisfy the constant volatility assumption of the model, the state variable is normalized by the estimated volatility derived from GARCH. Furthermore, multiple control variables are added to the model to represent the activity of fundamentalists and chartists. The results suggest that the cusp catastrophe model fits the data better than the linear and logistic models. The normalization of the state variable improves the model performance while the introduction of the additional control variables does not produce better results. Keywords Housing market, catastrophe theory, stochastic cusp catastrophe model, hous- ing bubble, real estate, fundamental investors, speculation. 1
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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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Impact of Terrorism on Stock Markets
Koščo, Marek ; Červinka, Michal (advisor) ; Nevrla, Matěj (referee)
Terrorism generally induces negative mood in the society. Financial markets performance exhibits the contingency on the mood of their trading parti- cipants. The thesis enhances the understanding of this interrelated entities by analysing the situation from 2000 to 2015 at the 20 world largest mar- kets. Their composite indices are put under scrutiny employing a multifactor model, a difference equation and a logit model. The impact is confirmed and further discussed, while the logit model provides a simple framework for forecasting index returns just after an attack with more than 25 casualties. Keywords global financial markets, terrorism, multifactor model, difference equation, logit model
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Modely dynamické podmíněné korelace a jejich aplikace při mitigaci rizika portfolia
Ševčík, Martin ; Frýd, Lukáš (advisor) ; Nevrla, Matěj (referee)
This bachelor thesis investigates asymmetry in returns of corn, gold and crude oil (both spot and futures) and hedging effectiveness of these commodities when employing DCC family models for hedge ratio estimation. The asymmetry in conditional variances was found to be significant only in case of crude oil spot and futures returns and asymmetry in conditional correlation of spot and futures returns was not shown to be significant in neither of the investigated commodities. With respect to the hedging performance, we conclude that differences in hedging performance measured by hedging effectiveness index are negligible and thus do not support superiority of DCC family models over OLS, which served as a benchmark. Historical Value at Risk, on the contrary, identified the DCC with asymmetry in conditional variance (despite asymmetry not being significant) to be appropriate for corn hedging, however not for the other two commodities, where the OLS based hedge ratio performed similarly or even better than the DCC family models. The main contribution of the thesis thus lays in empirical investigation of asymmetry in returns of selected commodities and testing hedging potential of DCC family based hedge ratio.
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Using the log-periodic power-law model to detect bubbles in stock market
Kožuch, Samuel Maroš ; Krištoufek, Ladislav (advisor) ; Nevrla, Matěj (referee)
Stock market crashes were considered as an chaotic even for a long time. However, more than a decade ago a specific behavior was observed, which accompanied most of the crashes: an accelerating growth of price and log-periodic oscillations. The log-periodic power law was found to have an ability to capture the behavior prior to crash and even predict the most probable time of the crash. The log-periodic power law requires a complicated fitting method to find the estimated values of its seven parameters. In the thesis, an alternative simpler fitting method is proposed, which is equally likely to find the true estimates of parameters, thus generating an equally good fit of log-periodic power law. Furthermore, four stock indices are fitted to log-periodic power law and examined for possible log-periodic oscillations in different time periods, including a very recent period of 2017. In all of the analyzed indices, a log-periodic oscillations could be observed. One index, analyzed in past period, was fitted to log-periodic power law, which was able to capture the oscillations and predict the critical time of crash. In the rest of the selected stocks, which were analyzed in a recent period, the critical time was estimated with varying results.
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