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Evaluating the predictability of virtual exchange rates using daily data
Řanda, Martin ; Polák, Petr (advisor) ; Kukačka, Jiří (referee)
Virtual worlds have garnered the attention of researchers from various disci- plines and are viewed as particularly valuable to economists due to their open- ended design. In this thesis, we review a popular online multiplayer game's economy and focus on exchange rate predictability in a virtual setting as only a limited body of literature investigated this topic. The well-established unpre- dictability puzzle is addressed by exploiting a unique daily time series dataset using a vector autoregressive framework. Apart from a significant Granger- causal relationship between the virtual exchange rate and the player popula- tion, the system is shown to be less interconnected than expected. Furthermore, an out-of-sample exercise is conducted, and the forecasting performance of our models is examined in comparison to that of a simple no-change benchmark in the short term. Based on the evaluation methods used, the two measures of the virtual exchange rate are found to be somewhat predictable. We suggest two explanations for this inconsistency between the virtual and real-world exchange rates: data frequency and lack of complexity in the considered online economy.
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Is hype really that powerful? The correlation between mass and social media and cryptocurrency rates fluctuations
Ilina, Viktoriia ; Král, Michal (advisor) ; Kukačka, Jiří (referee)
Twelve years after Satoshi Nakamoto published the paper describing the functioning mechanism and principals of cryptocurrency that maintains secure and anonymous digital transactions beyond any banks, cryptocurrencies have become a multi-billion-dollar industry comprising millions of investors, miners, developers and profiteers. However, the actual price determinants and ways to forecast future price changes remain an open question yet to discover the answer for. This study attempts to figure out whether media hype exerts that much influence upon cryptocurrencies price movements and whether it can be used as the basis for future movements prediction. Two cryptocurrencies, Bitcoin and Tezos, and 7 mass and social media factors for each of them were considered on daily basis from 08-01-2018 to 10-31-2020. To explore the interdependence between media drivers and cryptocurrencies' prices in short, medium and long timespan, this study deploys wavelet coherence approach. There was found, that price changes turn to be the supreme prior to hype, even though the growing ado may push the prices even higher. Thus, hype is failing to prove itself as a reliable cryptocurrency price predictor. Crypto investors, though, should anyways take the news background into account while building trading strategies,...
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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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