|
| |
|
|
Assessing Economic Situation of a Company and Proposals for Its Improvement
Hynek, Jan Jaroslav ; Franková, Tereza (referee) ; Doubravský, Karel (advisor)
The master’s thesis deals with the assessment of the financial situation of XZY s.r.o. using financial analysis and statistical methods. The theoretical part is divided into financial and statistical theory. In these parts, it presents the definition of selected financial ratios and statistical methods, which include time series regression and correlation analysis. The theoretical part is followed by an analytical part in which the financial situation of the selected company is evaluated along with the prediction of selected ratios. Furthermore, the selected ratios are subjected to correlation analysis where the interdependence between them is examined. The paper concludes with suggestions for improving the financial situation of the enterprise.
|
|
|
Assessing Economic Situation of a Company and Proposals for Its Improvement
Pokorný, Dominik ; Fuchs, Ondřej (referee) ; Doubravský, Karel (advisor)
The thesis deals with the assessment of the economic situation of CQQ in the years 2013–2022 based on the results of selected financial analysis indicators and statistical methods. The theoretical part of the thesis focuses on financial and statistical theory. The analytical part contains calculations of financial indicators of the company, some of which are further processed in the statistical analysis. The last part is devoted to the proposed solutions for correcting or improving the economic situation of the company.
|
|
|
Assessing Economic Situation of a Company and Proposals for Its Improvement
Rýpal, Matěj ; Novotná, Veronika (referee) ; Doubravský, Karel (advisor)
This thesis focuses on the evaluation of the economic situation of the company GUMEX, spol. s.r.o. and the prediction of future development using statistical methods. The theoretical part of the thesis deals with the description of selected financial ratios and statistical methods such as time series analysis, regression and correlation analysis. In the practical part, the individual ratios are calculated to assess the financial condition of the analysed company and the selected ratios are then analysed using statistical methods to predict future developments. The final part of the thesis is devoted to the proposals based on the results of the analytical part of the thesis and aimed at improving the financial situation of the company.
|
|
|
Analysis of economic data using statistical methods
Pavlásek, Boris ; Doubravský, Karel (referee) ; Michalíková, Eva (advisor)
This bachelor thesis deals with the analysis of the economic data of a company and the subsequent evaluation of its financial situation. In doing so, it uses the tools of financial analysis and statistical methods, namely regression analysis and time series. The theoretical part presents the theory needed to perform the analysis and also explains different financial indicators, statistical methods and regression functions. In the analytical part, data from the company's financial statements are used for financial analysis and subsequent forecasting of their future progress. In the last parts of the thesis, a comprehensive assessment of the financial situation of the company and suggestions for solving the identified problems are presented.
|
|
|
Time Series Forecasting Using Maching Learning for Network Communication
Kašpárek, Aleš ; Burgetová, Ivana (referee) ; Matoušek, Petr (advisor)
Tato diplomová práce zkoumá komplexní svět síťových komunikačních systémů, které vyžadují pokročilé metody předpovědi, aby fungovaly efektivně, spolehlivě a bezpečně. Se sítěmi stále složitější, přesné předvídání podmínek sítě a jejího provozu je rozhodující pro plánování, řízení zdrojů, detekci anomálií a zlepšování systémů. Práce začíná představením konceptu časových řad dat, který pokládá základ pro pochopení dynamiky v síťových systémech. Pokračuje tím, že představuje řadu analytických nástrojů a technik pro rozbor tohoto druhu dat, se zvláštním zaměřením na tradiční statistické metody. Mezi nimi je modelům Moving Average (MA), Auto Regressive (AR) a Auto Regresive Integrated Moving Average (ARIMA) věnována zvláštní pozornost pro své schopnosti v předpovídání budoucích stavů. Posun od tradičního předpovídání k používání strojového učení (ML) je ústředním bodem této práce. Práce zkoumá několik přístupů strojového učení (ML), jako jsou sítě Long Short-Term Memory (LSTM), konvoluční neuronové sítě (CNN), aby ukázala, jak mohou tyto metody identifikovat složité vzorce v síťovém provozu.
|
|
|
Mathematical Methods in Economics
Kosíř, Michal ; Doubravský, Karel (referee) ; Novotná, Veronika (advisor)
This bachelor thesis focuses on the analysis of the economic situation of a company using mathematical and statistical methods. The main task was to analyze the economic situation of the company for the period 2020,2021 and 2022 and to develop a tool in Visual Basic for Applications to automate this analysis. The first part is devoted to the theoretical background further needed for the analysis. The second part deals with the introduction of the company and the analysis of the economic indicators of the three entioned years. The final part describes the proposed solution to simplify the analysis.
|
|
|
Analysis of economic data using statistical methods
Halámka, Jaroslav ; Novotná, Veronika (referee) ; Michalíková, Eva (advisor)
My bachelor thesis deals with the application of financial analysis and statistical methods to selected company. The thesis is divided into three parts. The first part deals with theoretical characteristics of concepts, indicators and methods used throughout this thesis. The second part is focused on the analysis itself and deals with the evaluation of the current state of the company and the third part is focused on providing additional recommendations for future improvement.
|
|
|
Assessing Economic Situation of a Company and Proposals for Its Improvement
Sachambula, Nelson Mendonca ; Měrtlová,, Libuše (referee) ; Doubravský, Karel (advisor)
This diploma thesis focuses on the assessment of the economic situation of XYZ Med s.r.o. for the period from 2013 to 2022. The economic situation of the company is evaluated on the basis of selected financial indicators, which are then subjected to statistical analysis in order to create a basis for the proposal of measures to improve the situation. The theoretical part describes the financial ratios, correlation analysis, regression analysis and time series. In the analytical part of the thesis, the calculation of financial ratios is performed and then a statistical analysis is carried out on the basis of which the future development of the company is predicted. The analysis also tests the dependence for selected ratios. The practical part contains suggestions for improving the economic situation of the company.
|
|
|
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...
|
guest ::
