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The Price Determinants of Investment Rums
Polanka, Martin ; Baruník, Jozef (advisor) ; Kukačka, Jiří (referee)
This study investigates the pricing determinants of rum and explores its viability as an alternative investment asset. Utilizing a diverse methodological approach, the first inquiry employs Hedonic analysis through Weighted Least Squares, Stepwise regression, Lasso regression, and Bayesian Model Averaging. The second analysis adopts Repeat-sales regression to probe rum's potential as an investment asset. Key findings reveal that aging and reputation emerge as pivotal variables influencing rum pricing dynamics. Further, the study suggests that rum does not align with traditional collectible assets, as its price fails to exhibit consistent appreciation over time. In conclusion, this research contributes to a deeper understanding of the factors shaping rum pricing and offers insights into its suitability as an investment asset.
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Nudging the Czech Pension System Towards Sustainability
Král, Radim ; Kukačka, Jiří (advisor) ; Palanská, Tereza (referee)
This thesis explores possible improvements to the sustainability of the Czech pension system. The main focus is on nudges, which are suggestions that gently influence individuals' decision-making without restricting their freedom of choice. They have been successfully used in other countries, such as New Zealand and the United Kingdom. However, their effectiveness in the Czech Republic has not been comprehensively evaluated. To address this gap, a styl- ized agent-based model is utilized. This thesis extends an already existing model to incorporate real consumption and saving decision-making, as well as a simplified version of the Czech voluntary funded pension scheme. The model is parameterized using data specific to the Czech Republic. The analysis shows that in the current state of the Czech pension system, nudges exhibit only a marginal effect on improving its sustainability. However, as the government incentivizes individuals to save more and transition into higher-performing pen- sion funds, nudges become a crucial tool for enhancing system sustainability. For instance, a policy implementing nudges and promoting access to higher- performing pension funds alleviates almost 50% of the financial constraints the Czech pension system faces. JEL Classification F12, F21, F23, H25, H71, H87 Keywords...
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Hot hand bias in Czech sports betting market
Čakan, Jakub ; Kukačka, Jiří (advisor) ; Kmeťková, Diana (referee)
This thesis investigates behavioral biases, specifically the "hot hand" bias, in the Czech sports betting market. Further, it explores two hypotheses: whether the Czech sports betting market efficiently incorporates all relevant information into the odds and the impact of the "hot hand" belief on bettor behavior. The study employs weighted and ordinary least squares estimation, respectively, revealing that while bookmaker's odds efficiently reflect comprehensive infor- mation, confirming market efficiency, bettors display significant "hot hand" bias. More precisely, it leads bettors to disproportionately favor teams on win- ning streaks, indicating an overreaction to recent team performances and an inefficiency on the part of bettors. Additionally, the thesis evaluates the prof- itability of betting strategies aimed at exploiting these biases. It does not find such strategies consistently yielding profits, highlighting the complex nature of betting markets and the difficulty of capitalizing on behavioral biases. This research enhances the understanding of behavioral biases in sports betting, il- lustrating the interaction between bookmaker precision and bettor irrationality within the Czech betting landscape. JEL Classification C31, G14, G17, G41 Keywords market efficiency, sports betting, hot hand, be- havioral bias...
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ESG score and corporate financial performance in controversial industries
Ji, Jia Xin ; Kukačka, Jiří (advisor) ; Šíla, Jan (referee)
The thesis analyses the relationship between ESG performance and the cor- porate financial performance of companies listed in the S&P 500 index. The analysis first confirms the continued validity of the positive synergy hypothesis, even using the most up-to-date datasets covering the COVID-19 crisis followed by a period of increasing interest rates worldwide. Furthermore, it provides key insights through a comparative analysis between sin and other industries. While no significant differences emerge for companies in the sin industry as a whole, a closer examination of individual industries within the sin triumvi- rate reveals notable differences. For tobacco companies, the impact of the relationship between ESG performance and corporate financial performance in both directions appears to be significantly lower than for other industries. Conversely, the effect for alcoholic beverage producers is more complex, with the environmental and social pillars having a significantly stronger impact on financial performance than for other companies. Interestingly, the gambling industry shows no significant effect when controlling for other factors. JEL Classification A13, G30 Keywords ESG score, financial performance, controversial industry, panel VAR, Granger causality Title ESG score and corporate financial...
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Role of Central Bank Digital Currencies in Bridging the Formal-Informal Economy Divide in Developing Countries
Khaing, Pyae Soan ; Krištoufek, Ladislav (advisor) ; Kukačka, Jiří (referee)
Neformální ekonomika existovala mimo regulační rámce vedle formálních struktur. Přetrvává toto rozdělení, ve kterém se neformální ekonomika často vyznačuje svou neregulovaností, která omezuje výběr daní, finanční začleňování a sociální zabezpečení. Vzhledem k tomu, že vláda a finanční instituce většinou přehlížejí roli financí při formalizaci neformální ekonomiky, poslední trendy ukazují rostoucí uznání důležitosti formalizace prostřednictvím finančního začleňování. V této souvislosti se jednou z iniciativ staly digitální měny centrální banky (CBDC). Tato práce zkoumá roli CBDC při překlenutí propasti mezi formálními a neformálními ekonomikami v rozvojových zemích. Abychom porozuměli potenciálu, který CBDC přináší, zkoumá výzkum projekty CBDC na Bahamách, v Nigérii a v Číně pomocí kvalitativních metod a hodnotí je podle mezinárodních směrnic a rámců Banky pro mezinárodní platby (BIS) a Mezinárodního měnového fondu (MMF). . Výsledky ukazují, že CBDC mohou snížit neformálnost tím, že zjednoduší přístup k základním finančním službám, sníží transakční náklady a zvýší transparentnost mezi účastníky.
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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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Good vs. Bad Volatility in Major Cryptocurrencies: The Dichotomy and Drivers of Connectedness
Šíla, Jan ; Kočenda, Evžen ; Kukačka, Jiří ; Krištoufek, Ladislav
Cryptocurrencies exhibit unique statistical and dynamic properties compared to those of traditional financial assets, making the study of their volatility crucial for portfolio managers and traders. We investigate the volatility connectedness dynamics of a representative set of eight major crypto assets. Methodologically, we decompose the measured volatility into positive and negative components and employ the time-varying parameters vector autoregression (TVP-VAR) framework to show distinct dynamics associated with market booms and downturns. The results suggest that crypto connectedness reflects important events and exhibits more variable and cyclical dynamics than those of traditional financial markets. Periods of extremely high or low connectedness are clearly linked to specific events in the crypto market and macroeconomic or monetary history. Furthermore, existing asymmetry from good and bad volatility indicates that information about market downturns spills over substantially faster than news about comparable market surges. Overall, the connectedness dynamics are predominantly driven by fundamental crypto factors, while the asymmetry measure also depends on macro factors such as the VIX index and the expected inflation.
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Comparison of Different Investment Opportunities during Unstable Times
Filonau, Ilya ; Kalabiška, Roman (advisor) ; Kukačka, Jiří (referee)
The goal of this diploma thesis is to take an insight into the world of investment during unstable economic times based on the example of the selected country, Germany. The thesis seeks to analyze the performance of five different investment options, real estate, REIT, Stock market, Gold and Bitcoin, and compare them, while identifying the most important macroeconomic factors influencing the value of the investment options. The methodology of the diploma thesis is represented by a time series analysis based on the time period between the first quarter of 2000 and the first quarter of 2023. Additionally, the technique of econometric estimation is applied, where, in total, six models are created. In the end, it is concluded that gold is the most superior investment choice, while the least attractive one is the REIT Index, representing indirect real estate investment due to its relatively unstable nature and unpredictability. JEL Classification J11, R30, D81, G11, E27 Keywords Real Estate, COVID-19, Investment, REIT, Stock Index, Gold, Bitcoin, Economic Recessions, Germany, Portfolio, Risk Title Comparison of Different Investment Opportunities during Unstable Times
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Prediction of Czech GDP using mixed-frequency machine learning models
Kotlan, Ivan ; Polák, Petr (advisor) ; Kukačka, Jiří (referee)
The goal of this study is first to provide superior predictions of Czech GDP growth to the o cial estimates of the Czech Statistical O ce and the proxy estimation of the Czech National Bank. Secondly, to expand the literature that focuses on machine-learning predictions that utilizes data with various sampling frequency. Although in the first goal, this thesis did not succeed as all models, namely Ridge and Random Forest, failed to beat the predictions of o cial institutes, the thesis contributes to the yet scarce literature on mixed-frequency machine-learning prediction. Since no machine-learning model accounts for data with various frequencies, the thesis shows how to transform variables so that any machine-learning model can utilize them. Furthermore, di erent dataset modifications are explored, such as the prediction time: end of the reference quarter (nowcast) and 40 days after the reference quarter (backcast), standardized and non-standardized datasets. And finally, for the superior Ridge model, the e ect of so-called high-frequency variables (sampled every week) is explored. While Random Forest showed little e ect by using di erent versions of the dataset, in the case of the Ridge model, the type of dataset had a significant e ect. While the non-standardized Ridge produces better overall...
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The Impact of News on Videogame Stock Market Prices and Volatility
Mertová, Veronika ; Čech, František (advisor) ; Kukačka, Jiří (referee)
The thesis investigates the impact of social media and news headline sentiment on stock prices, specifically comparing gaming firms to companies from other industries. Tweets and news headlines containing keywords referring to four selected gaming and four non-gaming companies were collected over 5 and 3 months, respectively. Both tweets and news collected came from the general users or media rather than focusing solely on financial ones. The data were aggregated into daily values. Daily stock price data were also collected for each examined company to derive returns and volatility. The data were analysed using a vector autoregression model in combination with Granger causality. The study found no significant differences between gaming and non-gaming sectors. The polarity of sentiment showed no effect on stock prices. However, when sentiment was divided into different emotions, some significance was observed, although the findings varied across individual firms regardless of their sectors. It was concluded that when using sentiment for market predictions, it is beneficial to either utilize specifically financial media or determine the specific type of sentiment that influences a particular stock. JEL Classification G14, G17, C32, C58 Keywords Tweets, News Headlines, Gaming Industry, Sentiment...
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