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Geopolitical risks and commodity prices: The case of Canadian recourse companies
Zhuk, Heorhiy ; Horváth, Roman (advisor) ; Kočenda, Evžen (referee)
This thesis examines the impact of geopolitical risks and commodity prices on the stock returns and volatility of Canadian resource companies from 2004 to 2023, with a focus on the oil and energy sector, gold sector, and other minerals mining sector. Employing a comprehensive analysis of non-segmented and segmented data which has three distinct periods-2004-2009, 2010-2018, and 2019-2023-this study addresses the nuanced effects of geopolitical risk (GPR) in times marked by both economic stability and major global disruptions. The findings reveal that GPR significantly influences stock return volatility and mean equation, and also has a sector specific difference with oil and energy sector being the most effected one. The local Canadian GPR index was found to exert a more substantial impact on both the mean and volatility of stock returns compared to the global GPR index, emphasizing the importance of local geopolitical events in the Canadian market context. This thesis contributes to the empirical literature by highlighting the sector-specific responses to GPR and commodity price fluctuations, offering valuable insights for policymakers, regulators, and investors. It underscores the critical need for incorporating commodities in investment portfolios and adapting investment strategies to account...
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Financial Distress Prediction in Digital Finance Platforms
Zhang, Lin ; Kočenda, Evžen (advisor) ; Krištoufek, Ladislav (referee)
Jaké faktory nejvíce přispívají k finanční tísni FinTech firem: kapitálová přiměřenost, provozní činnosti nebo ziskovost? Tato práce se snaží zodpovědět tuto otázku pomocí logistického modelu a zkoumáním účetních dat 973 FinTech firem z celého světa z let 2018 až 2023. Analýza také bere v úvahu nefinanční proměnné a robustnost je testována pomocí modelu uspořádané odezvy a metody Bayesovského průměrování modelů. Výsledky naznačují, že během krizí je finanční tíseň FinTech firem ovlivněna především ziskovostí a provozními činnostmi, přičemž kapitálová přiměřenost hraje méně významnou roli. Klasifikace C52, C53, C58, G21, G32, G33, M41 Klíčová slova FinTech, predikce selhání, CAMELS, logistická regrese, model uspořádané odezvy, ROC, vzácnáudálost, BMA
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The Specifics of Financial Management of Holdings Companies
Ficbauer, David ; Kočenda, Evžen (referee) ; Král, Bohumil (referee) ; Zinecker, Marek (referee) ; Režňáková, Mária (advisor)
The main purpose of the thesis is to explore the specifics of the financial management of holdings companies in the Czech Republic with an emphasis on the area of financial management. However, the author assumes that persistent reasons for holding creation is using of synergy effects consisting mainly of centralized management of cash flows to minimize the cost of capital and minimizing the risk of an individual investor who actively makes managerial functions in view guarantees of individual companies. It was found the lack of a comprehensive and systematic approach for a qualitative research. A total of 15 holding companies was use for the qualitative research. The outcome gives many answers concerning the specifics of the financial management of the holdings companies. It seems guarantee and minimizing cost of capital are key points. The synergistic effect of the holding companies can be used when transferring financial means between companies holding. The impact of the transfer of available financial means was simulated for holding No. 13. It was clearly shown to decrease WACC at one of the companies within the holding.
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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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Topics in Yield Curve Modeling
Kučera, Adam ; Kočenda, Evžen (advisor) ; Horváth, Roman (referee) ; Mandel, Martin (referee) ; Berka, Martin (referee)
The aim of the thesis is to examine the interaction of macroeconomic and fi- nancial factors through the lens of yield curve dynamics. The thesis consists of three essays that jointly demonstrate the complexity of information incorporated in the yield curve and the importance of attributing yield curve movements to those factors correctly. The first essay uses news-based approach to identify triggers of the U.S. Treasury yield curve movements and demonstrates shifts in the importance of various causes of the movements. The second essay further evaluates the transmission of fiscal policy shocks to the U.S. Treasury yield curve. The first and the second essay together contribute to the literature by showing that the factors beyond the U.S. economic conditions and monetary policy have been becoming an increasingly important cause of the U.S. yield curve movements. These factors include changes in portfolio allocation, cross-border flight to quality and changes in fiscal policy. The third essay proposes a novel method to apply the up-to-date yield curve models to a government bond yield curve in an economy with a relatively shallow government bond market, using the case of the Czech government bond yield curve. This enables decomposing the yield curve and interpreting its movements while accounting for...
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Nowcasting the Real GDP Growth of the European Economies based on Machine Learning
Baylan, Su Hazal ; Kočenda, Evžen (advisor) ; Baruník, Jozef (referee)
This thesis analyzes the nowcasting of quarterly GDP growth for nine European economies using a dynamic factor model and four different machine learning models. These machine learning models are as follows: Ridge, Lasso, Elastic Net, and Random Forest. The data includes ten hard and fifteen soft indicators for each country in order to calculate GDP for each nowcasting iteration for pre-covid and covid periods. For machine learning, models are fed with the extracted factors that are obtained from the dynamic factor model, and for all nowcasting models expanding window approach is selected to estimate nowcasting iterations. The empirical finding indicates that overall machine learning models provide better forecasting accuracy compared to dynamic factor models and benchmark models for more stable periods, such as the period before Covid-19. On the other hand, for more volatile periods where the uncertainties are higher in economies, the dynamic factor model outperforms machine learning models in order to nowcast GDP growth. In addition to this, Random Forest is able to outperform all the alternative models for small economies such as Slovenia and Portugal for stable periods. JEL Classification C01, C33, C53, C83, E37 Keywords Nowcasting, DFM, Ridge, Lasso, Elastic Net, Random Forest Title Nowcasting...
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Stock Ownership Structure and Related Risk Premium
Rosický, Ondřej ; Baruník, Jozef (advisor) ; Kočenda, Evžen (referee)
Goal of this thesis is to discover the possible risk premium for stocks with respect to their ownership structure. We work with two types of investors, retail and institutional. Those types of investors have different expectations, preferences and behave differently in certain market events. We built the long-short IMR (institutional minus retail) factor as difference in returns of top and bottom portfolios based on proportion of institutional ownership and added this factor to Fama and French Three Factor Model. There is approximately 0.23 % risk premium for stocks with high share of institutional owners. Further we also try to find the possible impact of nominal stock price on ownership structure. With higher nominal price there is higher institutional ownership. On the other hand, this impact is negligible for low and high percentage share of institutional ownership, therefore IMR factor could not be substituted by the nominal stock price. Lastly, we tried to discover what causes the abnormal returns after the execution date. We found out that with increase in retail ownership by 1 p.p., the abnormal returns are higher in one week after stock split execution date by 0.8 p.p. That is in line with earlier discovered risk premium because with the decrease in the portion of institutional ownership...
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Fiscal policy and inflation: The case of the Czech Republic
Slaba, Martin ; Kočenda, Evžen (advisor) ; Hlaváček, Michal (referee)
This thesis investigates the relationship between government spending and inflation in the Czech Republic. We estimate a block-restriction VAR model in several specifications. The model confirmed the prediction of the Fiscal Theory of Price Level, that a shock to government spending will produce an inflationary response. However, the impulse responses are in all specifications insignificant or borderline significant. Second part of the thesis utilizes a non- econometric analysis to examine the post-covid inflationary period. The conclusion of this analysis is that the expansionary government spending combined with a tax cut provided the population with significant disposable income at a time when the economic output was compressed and consumption was severely restricted due to the lockdowns. The forcibly delayed consumption lead to an unprecedented increase in savings of both household and firms. The drawdown of these savings once the restrictions were lifted created demand-side inflationary pressures. The supply-side shock that came with the the war in Ukraine only enhanced the already heightened inflation.
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Drivers of Private Equity Activity across Europe: An East-West Comparison
Kočenda, Evžen ; Shivendra, R.
We investigate the key macroeconomic and institutional determinants of fundraising and investment activities and compare them across Europe, covering 13 Central and Eastern European (CEE) and 16 Western European (WE) countries. Five macroeconomic variables and nineteen institutional variables are selected. These variables are studied using panel data analysis with fixed effects and random effects models over an eleven-year observation period (2010–2020). Bayesian Model Averaging (BMA) is applied to select the key variables. Our results suggest that macroeconomic variables have no significant impact on fundraising and investment activity in either region. Investment activity is a significant driver of fundraising across Europe. Similarly, fundraising and divestment activity are significant drivers of investments across Europe. Institutional variables, however, affect fundraising and investment activity differently. While investment freedom has a significant effect on funds raised in the WE and CEE countries, government integrity and trade freedom are both significant determinants of investments in both European regions. In addition, the results demonstrate that, in contrast to the WE region, fundraising in the CEE region is not country specific.
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