National Repository of Grey Literature 94 records found  1 - 10nextend  jump to record: Search took 0.00 seconds. 
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.
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...
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.
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.
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.
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.
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.
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,...
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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