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How much do we pay for a real estate ownership? A simulation approach
Gallová, Ivana ; Pleticha, Petr (advisor) ; Kukačka, Jiří (referee)
This thesis compares rent vs home ownership based on the net present value, within the periods of the Great Recession and current year. The analysis is focused on the Czech Republic real estate market as a whole. Rent and real estate price are forecasted, and factors determining the price of rent and real estate are identified. The ARIMA model used for forecasting performs accurate short-term predictions. The results expect 3,2 percent annual growth of rent in the following year and 7,2 percent increase for the real estate prices. The results of net present value analysis indicate, that for years 2008 and 2009 renting was superior choice, while for years 2011, 2013 and 2019 home ownership was to be preferred from financial aspect.
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Asset Prices, Network Connectedness, and Risk Premium
Procházková, Vendula ; Baruník, Jozef (advisor) ; Kukačka, Jiří (referee)
This diploma thesis introduces the measures of network connectedness in the context of asset pricing. It proposes an asset pricing model in which the factor of connectedness is included as one of the risk factors together with the three Fama-French factors. The goal of the analysis is to examine whether the con- nectedness represents a signifcant risk factor that should be considered while determining the risk premium of the portfolio in diferent sectors in the market. Using the realized volatilities and returns of 496 assets of SP 500 index over the period 2005 - 2018, that are divided into 11 sectors, we frstly determine the linkages of connectedness between the assets in the same sector. Applying Fama-MacBeth two-step regression model, we explore the signifcance of the connectedness factor for the determination of the risk premium. We argue that the sector overall connectedness represents a signifcant risk in most of the sec- tors and should be therefore taken into account by the investors in all sectors. Moreover, the total directional connectedness that captures the spillover of shocks to one asset from the other assets in the sector, is a signifcant risk fac- tor that should increase the risk premium of the portfolio, especially in sectors such as the fnancial, health care, consumer...
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The Effect of M&A on Competitors' Performance in China and the US
Wojnarová, Renáta ; Kukačka, Jiří (advisor) ; Teplý, Petr (referee)
We examine the effect of merger announcements on the stock performance of acquirers' industry rivals in the context of Chinese and US deals between 1994 and 2017. Our analysis reveals that investors of rivals are able to earn abnormal returns during days around merger announcement, meaning that markets are not fully efficient as implied by the Efficient market hypothesis. We conclude that in a reaction to the announcement, US rivals achieve generally negative abnormal returns with higher magnitude and volatility compared to Chinese rivals. Additionally, we observe that Chinese investors' perception of mergers turned out to be more conservative after the Global financial crisis. During days around the merger announcement, signs of rivals' abnormal returns also differ on whether the target is public or private in both countries. Rivals operating in industries that are substantially supported by Chinese government such as real estate, pharmaceuticals, and chemicals experience positive reaction on mergers of their competitors. Furthermore, we find that industries with increasing im- portance in Chinese developing economy such as banking, telecommunications, and cyclical consumer products show a positive reaction of rivals' returns on merger announcements while in the developed US economy, a negative...
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Predicting stock market crises using investor sentiment indicators
Havelková, Kateřina ; Kukačka, Jiří (advisor) ; Kočenda, Evžen (referee)
Using an early warning system (EWS) methodology, this thesis analyses the predictability of stock market crises from the perspective of behavioural fnance. Specifcally, in our EWS based on the multinomial logit model, we consider in- vestor sentiment as one of the potential crisis indicators. Identifcation of the relevant crisis indicators is based on Bayesian model averaging. The empir- ical results reveal that price-earnings ratio, short-term interest rate, current account, credit growth, as well as investor sentiment proxies are the most rele- vant indicators for anticipating stock market crises within a one-year horizon. Our thesis hence provides evidence that investor sentiment proxies should be a part of the routinely considered variables in the EWS literature. In general, the predictive power of our EWS model as evaluated by both in-sample and out-of-sample performance is promising. JEL Classifcation G01, G02, G17, G41 Keywords Stock market crises, Early warning system, In- vestor sentiment, Crisis prediction, Bayesian model averaging Title Predicting stock market crises using investor sentiment indicators
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Monetary Policy Under Behavioral Expectations: An Empirical Validation of the Heuristic Switching Model
Bolshakov, Sergey ; Kukačka, Jiří (advisor) ; Kučera, Tomáš (referee)
This work takes one of the most prominent behavioral New-Keynesian models from the shelf and estimates it via the simulated method of moments. The model exhibits a remarkably good ft to the auto- and cross-covariance pro- fles of the euro area macroeconomic time series, especially compared to the standard rational expectations model. This result corroborates the claim that central banks which implement strict infation targeting are better of reacting to the output gap, on top of infation. JEL Classifcation E52, E70, D84, C53 Keywords Behavioral macroeconomics, heterogeneous ex- pectations, New-Keynesian model, Heuristic Switching Model, simulated method of moments Title Monetary Policy Under Behavioral Expecta- tions: An Empirical Validation of the Heuristic Switching Model
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The Trump Sentiment: The Effect of News on the US Stock Market
Pinteková, Aneta ; Kukačka, Jiří (advisor) ; Horváth, Roman (referee)
This thesis examines how the American economy is affected by the market sentiment that arises from the news about actions and decisions of the American President Donald Trump. The news articles are obtained from Reuters for the period between the 1st of May and the 30th of November 2018, based on which a sentiment variable is created using natural language processing methods. Firstly, the impact of Trump sentiment on the returns on the S&P 500 Index is examined. The results show a positive and statistically significant impact of sentiment from the previous day on today's S&P 500 Index return. A statisti cally significant effect of the sentiment from a week ago is also found, however, this effect is negative. This result indicates that there is an initial overreaction to the new information, followed by subsequent market correction to the mean. Such result is consistent with the findings of the field of behavioural finance, which incorporates the idea that investor psychology is involved in investment decision making. Secondly, the impact of the news sentiment on the performance of individual sectors of the American economy, as measured by the returns on S&P 500 sector indices, is analysed. A statistically significant effect of sentiment on sector index return is found in the case of Consumer...
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Occupancy Rate in Paid Parking Zones in Prague
Kašparová, Amálie ; Pleticha, Petr (advisor) ; Kukačka, Jiří (referee)
The bachelor thesis deals with occupancy measurement in Paid Parking Zones (PPZ) in Prague with system of random monitoring by special vehicles equipped with cameras. It introduces distinction between immediate occupancy, i.e. the percentage use of parking spaces in a given area in a given time and effective occupancy, i.e. the percentage use of time parking capacity in a given time interval. Since the effective occupancy cannot be determined in real conditions of PPZ by random monitoring, the method of simulation of parking in the model area was chosen. The model was created based on parameters expected parking time of visitors and residents and parking interest. The model simulates the use of parking capacity and its output are simulated effective and immediate occupancy. The basic parameter values were obtained by analysing the real data for 2018 from PPZ. The goal of the thesis was to analyse under which conditions and number of measurements, the immediate occupancy is a good estimate of effective occupancy. In total, 10500 simulations were performed for 21 different parameter combinations resulting in an effective occupancy of about 45%-95%. The results of the simulation show, that five measurements in one working week are sufficient to estimate effective occupancy in the same time interval....
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Herd behavior of investors in the stock market: An analysis of cross-country effects in the CEE
Lerche, Vojtěch ; Kukačka, Jiří (advisor) ; Vácha, Lukáš (referee)
The thesis examines herding behavior of investors towards the market average in 10 CEE stock markets during the period 2000-2018. Least squares and quantile regression methods provide evidence of herding inside the majority of the countries. During the global financial crisis and the Eurozone crisis, the herding mentality was more intense only in Slovenia and Croatia. The thesis finds mixed results in asymmetric herding during days of positive and negative market returns. The main finding, and a contribution to the literature, is that the domestic cross-sectional dispersion of returns in the CEE is affected by the dispersion of returns of the foreign stock markets in the USA, the UK, and Germany. In addition, empirical results suggest that extreme market conditions in the U.K. market have an impact on the formation of herding forces within the CEE stock markets. Short-run arbitrageurs can benefit from collective decisions of investors that in turn drive stock prices away from their fair value, but the presence of herding undermines benefits of portfolio diversification. In the long-run, the contagious international effects may result in a severe instability of the whole region and in market inefficiency.
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Corporate Acquisitions and Expected Stock Returns: A Meta-Analysis
Parreau, Thibault ; Havránek, Tomáš (advisor) ; Kukačka, Jiří (referee)
This thesis aims at investigating the puzzling relationship between cor- porate acquisitions and expected stock returns by reviewing numerous studies on this topic through the use of state of the art meta-analysis tools. Such an analysis is required because many papers examined this relationship but their results varied. We therefore collected 421 estimates from 20 papers and led multiple regressions to test for the presence of publication bias. Throughout this analysis we indeed found evidence supporting the existence of publication bias. Furthermore, we decided to apply Bayesian Model Averaging to reduce the model uncertainty and find out why our abnormal returns estimates greatly vary across stud- ies. Our results suggest that one of the most important drivers are the standard-error terms. This subsequently proves that publication bias is the most responsible for the heterogeneity amongst our estimates. Our analysis fails to demonstrate any positive effects from M&A activity on a firm post-acquisition performance. We suggest that other motives are under-represented in the underlying theory that aims to assess M&A outcomes. Keywords Mergers and Acquisitions, Stock Returns, Abnormal Re- turns, Meta-Analysis, Publication bias Author's e-mail thibault.parreau@gmail.com Supervisor's e-mail...
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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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