National Repository of Grey Literature 69 records found  1 - 10nextend  jump to record: Search took 0.01 seconds. 
Trading volume and expected stock returns: a meta-analysis
Bajzík, Josef ; Havránek, Tomáš (advisor) ; Červinka, Michal (referee)
I investigate the relationship between expected stock returns and trading volume. I collect together 522 estimates from 46 studies and conduct the first meta-analysis in this field. Use of Bayesian model averaging and Frequentist model averaging help me to discover the most influential factors that affect the return-volume relationship, since I control for more than 50 differences among primary articles such as midyear and type of data, length of the primary dataset, size of market, or model employed. In the end, I find out that the relation between expected stock returns and trading volume is rather negligible. On the other hand, the contemporaneous relation between returns and volume is positive. These two findings cut the mixed results from previously written studies. Moreover, the investigated relationship is influenced by the size of country of interest and the level of its development. Besides the primary studies that employ higher data frequency provide substantially larger estimates than the studies with data from longer time periods. On the contrary, there is no difference among different estimation methodologies used. Finally, I employ classical and modern techniques such as stem-based methodology for publication bias detection, and I find evidence for it in this field. 1
Relationship of Economic Growth and Pollution in the Czech Republic
Moldan, Martin ; Červinka, Michal (advisor) ; Valíčková, Petra (referee)
The Environmental Kuznets Curve (EKC) is a hypothesized relationship between GDP per capita and pollution. It suggests that the relationship has a shape of a concave quadratic function-i.e. that firstly, with increasing GDP per capita, levels of pollution increase. And then, from some level of GDP per capita, as GDP per capita rises, levels of pollution decrease. This bachelor thesis examines whether the EKC holds for the Czech Republic or not. It uses panel data on air pollution for the period 1995-2017, in particular concentrations SO2 and NOx. This analysis is conducted using the fixed effects method. The results of this bachelor thesis suggest that for the case of SO2, there is a relationship between GDP per capita and the pollutant's concentrations. However, this relationship does not change over time significantly. Moreover, for the case of NOx, the relationship between the pollutant's concentrations and GDP per capita is not significant, hence, the EKC hypothesis can be rejected for both examined pollutants.
Rivals as Allies: Combining Fundamental and Technical Analysis for Stock Investing
Buinevici, Igor ; Červinka, Michal (advisor) ; Čech, František (referee)
The main aim of this thesis is to perform a detailed investigation of cer- tain investment strategies based on European stock data. There are four investment strategies overall that are examined from the performance per- spective: momentum strategy, momentum strategy with BOS ratio filtering, fundamental buy and hold strategy using F SCORE and a key combined strategy incorporating all the methods mentioned above. After the esti- mation of Fama and French three-factor model for the combined strategy using the aggregated group of stocks, it can be inferred that in the case of a monthly rebalancing this strategy generates statistically significant monthly risk-adjusted return of 0.938%. For the three-month, six-month and nine- month holding periods the conclusion for the aggregated group of stocks is similar - in all of these cases the combined strategy also generates statisti- cally significant risk-adjusted returns. Based on further comparative testing of strategies for the aggregated group of stocks, it can be stated that the combined investment strategy significantly outperforms all other strategies in terms of returns, especially in the case of a one-month holding period. Keywords: portfolio analysis, fundamental analysis, tech- nical analysis, stock investing, empirical testing JEL...
Impact of Terrorism on Economic Growth
Siegl, Jakub ; Červinka, Michal (advisor) ; Kolcunová, Dominika (referee)
The negative market atmosphere resulting from terrorism may potentially affect key macroeconomic variables and be reflected in economic growth both immediately and with time lags. This thesis utilizes quarterly data on variables related to terrorism and key macroeconomic metrics for the time period 1970-2017 and establishes the effect of terrorism on economic growth. Furthermore, it elaborates on the change of general perception of terrorism after the 9/11 2001 attack and assesses the difference of its effect before and after this key violent act. In general, it has been found that the deaths and wounds resulting from terrorism affect economic growth with lags. Further- more, following the 9/11 2001 terrorist attack, the time layout of the effect of deaths resulting from terrorism has changed. Keywords terrorism, economic growth, panel data analysis, fixed effects model, mac- roeconomic metrics
Artificial Neural Networks in Option Pricing
Vach, Dominik ; Gapko, Petr (advisor) ; Červinka, Michal (referee)
This thesis examines the application of neural networks in the context of option pricing. Throughout the thesis, different architecture choices and prediction parameters are tested and compared in order to achieve better performance and higher accuracy in option valuation. Two different volatility forecast mechanisms are used to compare neural networks performance with Black Scholes parametric model. Moreover, the performance of a neural network is compared also to more advanced modular neural networks. A new technique of adding rational prediction assumptions to neural network prediction is tested and the thesis shows the importance of adding virtual options fulfilling these assumptions in order to achieve better training of the neural network. This method comes out to increase the prediction power of the network significantly. The thesis also shows the neural network prediction outperforms the traditional parametric methods. The size and number of hidden layers in a neural network is tested with an emphasis to provide a benchmark and a structured way how to choose neural network parameters for future applications in option pricing. JEL Classification C13, C14, G13 Keywords Option pricing, Neural networks, Modular neu- ral networks, S&P500 index options Author's e-mail vach.dominik@gmail.com...
Analysis of Term Structures in High Frequencies
Nedvěd, Adam ; Baruník, Jozef (advisor) ; Červinka, Michal (referee)
This thesis represents an in-depth empirical study of the dependence structures within the term structure of interest rates. Firstly, a comprehensive overview of term structure modelling literature and methods is provided together with a summary of theoretical notions regarding the use of high-frequency data and spectral analysis. Contrary to most studies, the frequency-domain approach is employed, with a special focus on dependency across various quantiles of the joint distribution of the term structure. The main results are obtained using the quantile cross-spectral analysis, a new robust and non-parametric method allowing to uncover dependence structures in quantiles of the joint distribution of multivariate time series. The results are estimated using a dataset consisting of 15 years worth of high-frequency tick-by-tick time series of US Treasury futures. Complex dependence structures are revealed showing signs of both cyclicity and dependence in various parts of the joint distribution of the term structure in the frequency domain. JEL Classification C49, C55, C58, E43, G12, G13 Keywords term structure of interest rates, yield curves, high-frequency analysis, spectral analysis, inter- est rate futures Author's e-mail adam.nedved@fsv.cuni.cz Supervisor's e-mail barunik@fsv.cuni.cz
The Facility Location Problem for an Alternative Delivery Service
Vaněk, Petr ; Červinka, Michal (advisor) ; Habibi, Arash (referee)
The main intention of the bachelor thesis is to introduce all necessary theory to under- stand and apply the facility location problem for an alternative delivery service. Solving the facility location problem we are able to find optimal warehouse locations to minimize transportation costs from a firm to customers. Our attention is focused on an alternative delivery service which is slowly becoming to be taken seriously in logistic disciplines be- cause many companies are trying to apply drones or robots for shipping goods. The first part of this thesis deals with an important theoretical background needed to understand the facility location problem. Microeconomic view of the problem is presented, basic knowledge of mathematical programming with algorithms is explained and the facility location problem itself is defined. Moreover, each step of the branch & bound algorithm for the facility location problem is explained on an example from Prague. In the practical part of the thesis, we solve a real problem for the Czech company which would like to im- plement a drone delivery service in Prague. Finally, we discuss future technical progress and its impacts on autonomous delivery service, legislative and privacy problems with a drone delivery system in Prague and other possible usage of autonomous vehicles in...
The Effect of Litigation Risk on Earnings Management in the Proximity to Debt Covenant Violation
Britskiy, Andrey ; Novák, Jiří (advisor) ; Červinka, Michal (referee)
This bachelor thesis aims to establish a relationship between earnings management in proximity to debt covenant violation and the presence of litigation risk. Central testable concept is Watts and Zimmerman (1990) debt covenant hypothesis according to which managers tend to manipulate earnings to reduce the possibility of violation of their company's debt agreement. This setting allows investigating whether the risk of litigation is an effective regulatory mechanism which improves the contracting usefulness of accounting numbers and better align the interests between creditors and company managers, thus making debt covenants more reliable as monitoring mechanisms. Due to inconclusive results, this thesis was unable to establish whether the threat of litigation can discipline managerial reporting practices and deter misreporting for the companies with substantial debt covenant incentives.
Comparison of continuous and frequent batch auctions
Gottlieb, Oskar ; Šmíd, Martin (advisor) ; Červinka, Michal (referee)
We simulate a fragmented market and study three types of agents and their interactions in continuous trading and frequent-batch auctions. We model the markets using the agent-based modeling approach. There are two exchanges on which one asset is being traded by zero-intelligence (ZI) traders, market makers and a latency arbitrageur. The former two agents are marked as slow traders, the arbitrageur is a fast trader - fast trader has perfect information about the market, slow traders are dependent on the (possibly lagged) NBBO information provided by the regulator. Our main metric is the surplus of ZI traders, we also measure other market's characteristics. We then simulate the market for different delays of the NBBO delay and we find that under certain conditions and until certain length, the batch auctions are beneficial to ZI traders, as they reduce the advantage and therefore the profit of the fast trader.
Efficiency of Prague Stock Exchange Market using Markov Chains
Kratochvíl, Jonáš ; Červinka, Michal (advisor) ; Hausenblas, Václav (referee)
The main intention of this thesis is to analyze the weak form efficiency of Prague Stock Exchange. We conduct our empirical analysis on daily, weekly and monthly return data of the PX index collected in time period 1994-2017. The theory of Markov chains is employed to decide whether the index returns follow a random walk, the evidence of weak form efficiency. Bayesian Informa- tion Criterion is used to establish the optimal order of the Markov chain, which is in turn tested against the order 0 by Likelihood ratio criterion. The model assumptions of time homogeneity, irreducibility and aperiodicity of transition probability matrix are validated. We reject the weak form efficiency for daily index returns and establish its optimal Markov chain order to be 1. The weak form efficiency is not rejected for weekly and monthly index returns so is the as- sumption of time homogeneity for the whole time period 1994-2017. We propose further analysis of daily returns for time period 2006-2017, which exploits the fact of the weak form inefficiency. Discussion of results and related literature is provided as well as the presentation of all contemplated methods. 1

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See also: similar author names
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