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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
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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Evaluation of Company Business Financial Situation and Proposal to Its Improvement
Gondáš, Michal ; Zbreha, Ján (referee) ; Doubravský, Karel (advisor)
This work deals with the analysis of economic indicators of the company and the forecast of its development by using one of the most important applications of statistical methods in economics that is the time series analysis. The first, theoretical part of the work by using of skilled literature deals with defining basic terms, the various forms of analysis and the basic methods. The second, practical part deals with the analysis of selected economic indicators of the specific company. The last section presents the proposals, which could improve the company's results in the market environment in case of implementation into the practice.
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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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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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