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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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Assessing the Efficiency of a Company Using Statistical Method
Pastyřík, Jaroslav ; Kopka,, Radomír (referee) ; Doubravský, Karel (advisor)
The master’s thesis deals with the evaluation of financial efficiency of the company Bučovice Tools, a.s. using statistical methods. The theoretical part describes financial analysis, time series analysis, regression analysis and correlation analysis. In the practical part, the selected indicators of financial analysis are subjected to statistical analysis to detect dependence between indicators and to determine the prediction of the future development. Based on the financial results, the company is compared with a chosen company and with average indicators of the industry and are designed possibilities to improve the economic situation.
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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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Assessing Selected Indicators Using Statistical Methods
Hlaváčková, Martina ; Součková, Markéta (referee) ; Doubravský, Karel (advisor)
The bachelor thesis is focused on evaluation of the financial situation of the company and the prediction of the potential development with the help of selected indicators of financial analysis and the use of statistical methods. The first part focuses on the theoretical background. In the second part - practical, there are selected indicators of financial analysis and statistical methods such as time series analysis and regression analysis. After that, on the basis of the results obtained at the end of the work, suggestions are suggested to improve the current situation of the company.
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Assessing Selected Indicators Using Statistical Methods
Hofmanová, Aneta ; Michalíková, Eva (referee) ; Doubravský, Karel (advisor)
Master's thesis deals with the assessment of selected financial indicators of the company through a financial analysis and statistical methods, on the basis of which then evaluates the current situation of the company. The thesis is divided into three parts. The theoretical part contains the issues necessary for the analytical part. The analytical part is focused on the analysis of selected indicators and the subsequent application of statistical methods to predict their future development and to detect dependencies between the indexes. The last part formulates possible solutions to problems caused by financial indicators that do not reach the required values.
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Pattern Finding in Dymanical Data
Budík, Jan ; Hynčica, Ondřej (referee) ; Honzík, Petr (advisor)
First chapter is about basic information pattern learning. Second chapter is about solutions of pattern recognition and about using artificial inteligence and there are basic informations about statistics and theory of chaos. Third chapter is focused on time series, types of time series and preprocessing. There are informations about time series in financial sector. Fourth charter discuss about pattern recognition problems and about prediction. Last charter is about software, which I did and there are informations about part sof program.
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Vliv změn úrokových sazeb na odvětví faktoringu
Hamerská, Marie
The diploma thesis deals with the relationship between interest rates and the factoring market in the Czech Republic. Using econometric modelling it describes and quantifies the effect of interest rates on factoring indicators. The modelling results are interpreted on the behaviour of a specific company.
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Determinants of the Residential Real Estate Prices in Selected EU Countries
Rákosníková, Andrea ; Hlaváček, Michal (advisor) ; Schwarz, Jiří (referee)
This thesis aims to identify the determinants of real housing prices in the 13 newest EU member states. Determinants were identified using individual time series and aggregate panel analyses to ensure the best results. Cointegrating relationships were confirmed through testing and factored into the choice of estimation methods. The time series regression was done using the VECM, and the same method was used to test the theory that the capitals are the price leaders in housing markets. Results revealed that this effect is limited to only some markets, particularly affecting Czechia and Slovakia. Panel analyses, done using the PDOLS and ECM, were used to examine determinants and the speed of convergence of variables to equilibrium. The results of the aggregate panel regression showed that numerous determinants, namely the construction prices, GDP, number of housing permits, rents, and population, affect housing prices significantly. However, area-specific panels and time series models highlighted significant variations in results across countries. For example, GDP is not a significant determinant in V4 countries, while its effect is vital for the Balkans. The most surprising results were observed for Cyprus and Malta, where the relationships between the prices and determinants seem to be distorted by...
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Short-term Electric Load Forecasting Using Czech Data
Řanda, Martin ; Krištoufek, Ladislav (advisor) ; Čech, František (referee)
Forecasting electric load accurately is a critical prerequisite to dependable power grid operation. It is thus in the best interests of the responsible institutions to develop and maintain performant models for predicting load. In this thesis, we analyze Czech electric load data and execute three pseudo-out-of-sample forecasting exercises. We employ standard econometric as well as machine learning methods and compare the results to benchmarks, including the predictions published by the Czech transmission system operator. The results of the first task examining the predictability of minute loads using 11 years of data indicate that the high-frequency load series is predictable. In the second and third exercises, we utilize hourly loads with additional explanatory variables. We generate one-step-ahead and 48-hours-ahead forecasts on the 2021 out- of-sample set and evaluate the performance of several methods. In both exercises, the most accurate results are produced by averaging forecasts of our specified recurrent neural network and the seasonal autoregressive integrated moving average model, achieving a mean absolute percentage error of less than 0.5% on the out-of-sample set in the one-step-ahead analysis and 2.3% in the 48-hours-ahead exercise, outperforming the operator's predictions.
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