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Analysing the ESG stocks: Are they less volatile?
Stejskal, Jakub ; Čech, František (advisor) ; Hanus, Luboš (referee)
In this thesis, we investigate the relationship between ESG (Environmental, Social, and Governance) scores and stock volatility using panel data analysis. Focusing on data from 2 095 companies from three major stock exchanges - NAS- DAQ, NASDAQ Nordic, and Johannesburg stock exchange in the time window of 2016-2023, we employ fixed effects and random effects models with robust standard errors. We examine the overall impact of ESG scores on volatility, the influence of individual pillar scores, industry and stock exchange-specific effects, and time-specific effects. The thesis enhances existing literature by exploring three previously unexamined trends: non-linear dynamics between low-ESG score and volatility, the evolution of the trend over time by using an expanding time-window approach, and geographically and market-specific ef- fects by utilizing data from different stock exchanges. The results from our analysis indicate that while the influence of ESG scores on overall stock volatil- ity across the dataset is insignificant, significant correlations were observed in certain industry-specific models. The Technology, Industrials, and Healthcare sectors displayed a significant negative correlation between Governance scores and volatility. Moreover, for stocks listed on NASDAQ Nordic, there was a...
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xG Statistics in Football Matches: Predictions and Betting
Černý, Sebastian ; Hanus, Luboš (advisor) ; Šťastná, Lenka (referee)
The thesis studies the effectiveness of betting on the results of football matches using Expected Goals (xG) statistics from two sources Understat and FootyS- tats. It evaluates the performance of 6 different models in seasons 2021/2022 and 2022/2023 across the Ąve highest-ranked European leagues using binary logistic regression to predict two possible results, either the home team winning or away team not losing. For betting, several strategies are used based on ex- isting literature. The results are compared to the model containing traditional variables used commonly for predictions in football based on relevant litera- ture. Using both a combination of xG and traditional variables, and only xG variables the results suggest that xG variables are effective for predicting the outcome of football games. The model containing only Understat xG variables yielded 4.18% return on investment (ROI) when betting on every match in both seasons, which was 3.6% more than the model with traditional variables. For betting only on particular matches based on certain criteria, the combined models with both types of variables had the best results, reaching 10.87% ROI that again outperformed the model with traditional variables by approximately 4.5%. JEL ClassiĄcation C10, C53, L83, Z29 Keywords football, expected...
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Essays on Data-driven, Non-parametric Modelling of Time-series
Hanus, Luboš ; Vácha, Lukáš (advisor) ; Witzany, Jiří (referee) ; Ellington, Michael (referee) ; Trimborn, Simon (referee)
This thesis consists of four contributions to the literature on data-driven and non-parametric modelling of time series. In the first paper, we study the synchronisation of business cycles and propose a multivariate co-movement measure based on time-frequency cohesion. We suggest that economic inte- gration may lead to increased co-movement of business cycles, which may reflect the benefits of convergence and coordination of economic policies. The second paper presents a new methodology for identifying persistence in macroeconomic variables. Using time-varying frequency response func- tions, we identify heterogeneous persistence effects in US macroeconomic variables. The third and fourth papers propose data-driven techniques for probabilistic forecasting of time series using deep learning. We introduce a multi-output neural network that selects the most appropriate distribution for the data. The distributional neural network is valuable for modelling data with non-linear, non-Gaussian and asymmetric structures. The third paper demonstrates the usefulness of the method by estimating information-rich macroeconomic fan charts and distributional forecasts of asset returns. In the last paper, we present the distributional neural network to obtain the proba- bility distribution of electricity price...
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The Impact of Liquidity Risk on Bank Profitability: Some Evidence from European Banking Sector
Ivovič, Tomo ; Pečená, Magda (advisor) ; Hanus, Luboš (referee)
This thesis examines the effect of liquidity risk on the profitability of European commercial banks following the full implementation of the Liquidity Coverage Ratio. The aim is to analyse and compare this effect on banks in two different regions of the European Union. Therefore, three countries were chosen to represent the Southern European region, and six were chosen to represent the Northwestern European region. Data from 34 banks were collected for 2018-2022 and split into two datasets. Panel regression methods were utilized, and robustness tests were performed to improve the reliability of the results. This study uses two different measures as proxies for liquidity risk to obtain a more comprehensive understanding of the relationship. Both proxies, the Liquidity coverage ratio, and the Financing gap ratio, were found to be insignificant determinants of profitability in both regions. We also found that the Cost-to-income ratio negatively and significantly impacts banks' profitability in both regions. At the same time, credit risk and bank size showed a significant effect on the profitability of banks in the Southern European region. JEL Classification C12, C33, G21, G28, G32 Keywords banks, liquidity risk, liquidity, profitability, panel regression Title The impact of liquidity risk on bank...
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Economic Aspects of Blood Donation
Hanus, Luboš ; Janotík, Tomáš (advisor) ; Kukačka, Jiří (referee)
Sufficient blood supply is a continuous problem for health care systems around the world. The diversity of systems is also manifested as different methods of compensation and motivation of donors. During the last century the different types of compensation and motivation have brought about various high probabilities of transmission of infectious diseases. The goal of this thesis is to provide a sufficient description of donors' motivations in the Czech Republic and elsewhere. The first part aims to compare the risk of financially compensated blood donors and those who are not compensated. The second part gives a description of characteristics of the sample donors from the Institute of Hematology and Blood Transfusion in Prague. A probit model is used to analyse the sensitivity of donors to two benefits provided by the state, these benefits are either a paid working day-off on the day of donation or the possibility of deduction of 2000 CZK from one's taxable income for each donation.
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Okun's Law and Social Expenditure
Batíková, Marta ; Hanus, Luboš (advisor) ; Baxa, Jaromír (referee)
This thesis analyses Okun's law and its cross-country differences based on social expenditures. To estimate the law in time, Nadaraya-Watson kernel estimation is employed, which has not been applied to Okun's law in any previous study. Thus, to assess the robustness of the model, the statistical testing of hypotheses is used to evaluate the time-varying coefficients. The analysis is executed on OECD countries between 1995 and 2019, and the results are mainly in line with the previous literature. Periods with higher GDP growth and lower unemployment rates, on average, tend to have higher Okun's coefficients. Moreover, cross-country comparison reports the tendency of countries with, on average lower unemployment spending and higher GDP per capita to exhibit higher Okun's coefficients.
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The Impact of Renewable Electricity on the Czech Electricity Balancing Market
Kašparová, Amálie ; Hanus, Luboš (advisor) ; Janda, Karel (referee)
As global investments in renewable energy technologies continue to grow, their effects on electricity markets are a challenge for regulators and policymakers. The thesis examines the effects of forecast errors of Czech and German renew- able energy sources on the size and volatility of the system imbalance of the Czech balancing market. Using a quantile regression and ARFIMA-GARCH models on hourly data, I found that higher solar and wind forecast errors in- crease the system imbalance in absolute terms and affect the volatility. The results show that the Czech solar and wind forecast errors have significantly higher effect than the German forecast errors on the size and volatility of the system imbalance. The strongest effect on the size and volatility of the system imbalance have the Czech solar forecast errors. Therefore, the Czech govern- ment should insist on improving the accuracy and availability of renewable energy forecasts from the transmission system operator ČEPS. Klasifikace JEL C14, C50, Q42 Klíčová slova renewable sources, forecast errors, balanc- ing market, system imbalance
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Effects of LTV, DTI and DSTI ratios on retail mortgage market. Evidence from the Czech Republic
Mičková, Anna ; Pečená, Magda (advisor) ; Hanus, Luboš (referee)
The thesis analyses the effects of credit-related borrower-based macroprudential measures - loan-to-value (LTV), debt-to-income (DTI) and debt service-to-income (DSTI) ratios - on retail mortgage market in the Czech Republic. These lending instruments, which target mainly borrowers and restrict the amount of money borrowed relative to the value of underlying collateral (LTV) or client's disposable income (DTI, DSTI), represent a non-negligible part of macroprudential policy. This entry barrier should act in a preventive manner to protect borrowers from taking high-amount and high-risk mortgages and eventually curb excessive private sector leverage. After the introduction and implementation of limits in the Czech Republic, the supply of loans with risky parameters declined, the share of non-performing mortgage loans decreased, and the rise in house price index decelerated. In 2019, the volume of new mortgage loans declined by 13.6 % year-over-year compared to the previous year and the spiral between increasing credit financing of property purchases and rising property prices slightly weakened.
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Factors influencing the transport mode decision - case of the Czech Republic
Preclíková, Michaela ; Ščasný, Milan (advisor) ; Hanus, Luboš (referee)
The thesis describes shares of use of transport modes to reach different activities and analyses influence of socio-demographic variables on a choice of transport mode for commuting to work in the Czech Republic. Data from the INHERIT survey are used for the analysis. Factors which influence the transport mode decision were identified using the multinomial logit model. Results show that men, people with higher income and households with at least one child are significantly more likely to commute to work by car than women, people who earn less money and households without children. Living in large cities decreases the likelihood of using car for work trips and increases likelihood of travelling by public transport.
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