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Software Application for Assessment of Selected Indicators
Vrtílková, Pavla ; Smolík, Kamil (referee) ; Doubravský, Karel (advisor)
The bachelor thesis deals with the creation of a software application that is able to analyze the financial indicators of a selected company using statistical methods. The thesis contains both theoretical and practical parts. The theoretical part provides the knowledge needed to understand the issues related to the analysis of financial ratios, the use of statistical methods and the creation of a software application. The practical part deals with the design, functionality and subsequent creation of the software application, the output of which is is the evaluation of the economic situation of the selected company, monitoring of the trend that predicts the future economic situation and recommendation of possible economic improvements.
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Time Series Analysis
Budai, Samuel ; Bartík, Vladimír (referee) ; Burgetová, Ivana (advisor)
This thesis deals with the issue of time series analysis and its use in the detection of anomalies in industrial networks. AR-X, ARIMA, SARIMA, Random Forest, Facebook Prophet and XGB Boost algorithms were used in the solution to create prediction models. In addition, the work includes the implementation of an algorithm for detecting anomalies from prediction models as well as solving the problem of high seasonal period in the case of the SARIMA algorithm. Through the conducted research, it was found that with the use of selected algorithms, it is possible to predict industrial traffic for the purpose of detection, within which up to 90% of attacks were detected. The work also provides a solution to a high seasonal period using partial time series. These results allow the experimental integration of prediction-based detection into real industrial networks.
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Assessment of Selected Company Indicators Using Statistical Methods
Rozkydal, Štěpán ; Michalíková, Eva (referee) ; Doubravský, Karel (advisor)
The diploma thesis deals with the assessment of selected financial indicators of the company STAVOČ spol. s r.o. using statistical methods in the years 2013–2020. In the theoretical part, financial indicators, time series analysis, regression analysis and correlation analysis are defined. In the analytical part, the theoretical knowledge is applied to the analysis of selected financial indicators. Some financial indicators are then subjected to statistical analysis on which the prediction of values of indicators for the following two years is carried out or the dependency between the selected indicators is determined. In the last part of the thesis, measures leading to the improvement of the current economic situation of the company are suggested.
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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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Assessing Selected Indicators Using Statistical Methods
Bednářová, Veronika ; Michalíková, Eva (referee) ; Doubravský, Karel (advisor)
The diploma thesis is focused on the assessment of selected indicators using statistical methods. The first part is devoted to theoretical background, which describes financial indicators, time series analysis and regression and correlation analysis. The second part deals with the analysis of selected indicators and statistical analysis, which predicts the values of indicators for the next two years. Then correlation analysis is created, which determines the dependence between selected financial indicators. The last part is devoted to proposals leading to the improvement of the current situation of the company.
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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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Determinants of residential real estate prices in the Baltic States
Rákosníková, Andrea ; Hlaváček, Michal (advisor) ; Hanzlík, Petr (referee)
The burst of the housing bubble on the US market, that contributed to the start of the Great Recession, was a warning sign to many economists. Consequently, the last decade birthed important studies analysing the real estate market in the search for the driving determinants of the housing prices. This thesis continues these efforts by time series analysis of the determinants of residential real estate prices in Estonia, Latvia, and Lithuania. The VECM analysis showed that the importance of classic housing determinants differs from country to country. The price persistence is a crucial determinant of the Baltics' housing prices in the short run, but only Estonia and Lithuania showed the persistence in the long run. Latvian house price index seems to be very affected by the construction cost index, and therefore supply side of the housing market. The model also suggested an unexpected negative relationship between house and rent prices. The analysis was however done on relatively short time series and that could cause some discrepancies in the results as well. The author also used the P/I and P/R ratios and the Hodrick-Prescott filter to analyse the housing prices in the search of possible overvaluation, and concluded that these measures do not seem to indicate the existence of the housing bubble in...
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Assessment of Selected Indicators of a Company Using Statistical Methods
Shalaginova, Daria ; Novotná, Veronika (referee) ; Doubravský, Karel (advisor)
Master’s thesis is aimed at assessing the selected financial indicators of the company using statistical methods. Based on the results, the current situation of the company is evaluated. The thesis consists of three parts. The first part contains the necessary theoretical bases for processing the analytical part. The second part is devoted to the analysis of selected indicators, which are then applied statistical methods to the prediction of the future development of these indicators and findings, here between these indicators there is a dependence. At the end of this part, there is an evaluation of the analyzed indicators. The third part presents appropriate proposals for solutions to existing problems caused by indicators that deviate from the recommended values.
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Assessment of Selected Indicators of a Company Using Statistical Methods
Rešková, Petra ; Novotná, Veronika (referee) ; Doubravský, Karel (advisor)
Master´s thesis deals with the assessment of selected financial indicators of the company using a statistical methods. The first part is focused on the theoretical description of financial indicators, time series analysis as well as regression and correlation analysis. The practical part contains a statistical analysis of selected indicators with subsequent prediction of indicators for the next two years. The practical part also contains a comparison of selected indicators with the industry average and a correlation analysis to determine the dependence of selected indicators. The last part contains suggestions to improve the situation of the company.
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Evolution of housing prices and its determinants in CEE
Šedivý, Jakub ; Polák, Petr (advisor) ; Pečená, Magda (referee)
As housing is one of the important parts of gross domestic product and one of the most significant components of people's wealth it is vital to investigate the determinants of its prices. Therefore, we analyze housing prices in Central and Eastern European coun- tries using pooled mean group estimator and vector autoregressive models. The objective of this thesis is to find out whether the fundamentals of housing prices are comparable across different countries and how the shocks in the economy affect housing pricese. For our analysis we used housing prices per square metre, GDP per capita, unemployment rates, 5-year interest rates, harmonised indices of consumer prices and construction cost indices. The conclusions of using pooled mean group estimator suggest that GDP, un- employment, interest rate and HICP indeed significantly affect the housing prices. The results of empirical analysis of individual countries using vector autoregressive model con- clude that shocks in the determinants affect housing prices with lags of 2 to 3 quarters and that the individual countries are driven by slightly different fundamentals.
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