National Repository of Grey Literature 512 records found  1 - 10nextend  jump to record: Search took 0.00 seconds. 
Echo state networks and their application in time series prediction
Savčinský, Richard ; Mráz, František (advisor) ; Matzner, Filip (referee)
Recurrent neural networks (RNN) enable to model dynamical sys- tems with variable input length. Their disadvantage is in inherently difficult trai- ning which means adjusting weights of connections between neurons connected in the network. Echo state networks (ESN) are a special type of RNN which are by contrast trainable rather simply. They include a reservoir of neurons whose state reflect the history of all signals in the network and that is why this type of network is suitable for simulation and prediction of time series. To maximize the computational power of ESN, very precise adjusting and experimenting are required. Because of that, we have created a tool for building and testing such networks. We have implemented a time series forecasting task for the purpose of examination of our tool. We have focused on stock price prediction, which repre- sents an uncertain and complicated area for achieving precise results in. We have compared our tool to other tools and it was comparably successful. 1
Echo state networks and their application in time series prediction
Savčinský, Richard ; Mráz, František (advisor) ; Matzner, Filip (referee)
Recurrent neural networks (RNN) enable to model dynamical sys- tems with variable input length. Their disadvantage is in inherently difficult trai- ning which means adjusting weights of connections between neurons connected in the network. Echo state networks (ESN) are a special type of RNN which are by contrast trainable rather simply. They include a reservoir of neurons whose state reflect the history of all signals in the network and that is why this type of network is suitable for simulation and prediction of time series. To maximize the computational power of ESN, very precise adjusting and experimenting are required. Because of that, we have created a tool for building and testing such networks. We have implemented a time series forecasting task for the purpose of examination of our tool. We have focused on stock price prediction, which repre- sents an uncertain and complicated area for achieving precise results in. We have compared our tool to other tools and it was comparably successful.
The Empirics of Deflation and Economic Growth
Ryska, Pavel ; Šíma, Josef (advisor) ; Salerno, Joseph (referee) ; Hülsmann, Jörg Guido (referee) ; White, William (referee)
Author: Pavel Ryska Doctoral thesis: The Empirics of Deflation and Economic Growth Abstract This doctoral thesis deals with the relationship between deflation and economic growth. Existing empirical research has focused on the simple link between price growth and GDP growth or introduced narrower price measures as control variables. The goal of the present work is to account for shifts in both demand and supply, so that the effect of price inflation on growth as such could be separated from effects of changes in certain elements of nominal demand and supply. The work takes two general approaches. First, I use a large macroeconomic panel data set of 20 countries over approximately 140 years to explore long-run and short-run effects of inflation on output growth, after controlling for money supply growth as a demand shifter and oil price growth as a proxy for shifts in supply. In doing so, I use a range of methods such as the vector error-correction model, autoregressive distributed lag model and the fixed effects panel model. Second, I propose a new approach that uses disaggregated sector data from national accounts on output, prices and other variables to explore the link between quantity produced and sector inflation rates. The advantage of the data set is that it is rich in modern-day observations of...
Moving averages in time series
Uhliarik, Andrej ; Cipra, Tomáš (advisor) ; Hudecová, Šárka (referee)
This thesis focuses on time series analysis usikng methods based on moving averages, especially the method based on the approximation of the trend compo- nent of a time series by polynomial functions. In the theoretical part of the thesis, we describe procedures for choosing right weights, degree and length of moving average for a specific time series. In the practical part, we are demonstrating this process on real data. A part of the thesis is a simple software for smoothing time series and tables with weights of moving averages for specific degrees and lengths. 1
Factors affecting demand for passenger cars in the Czech Republic, focusing on alternative fuel vehicles
BROMOVÁ, Michaela
The automotive industry is one of the key industries in the Czech Republic. The aim of this work is to identify and analyse the factors of demand for alternative fuel vehicles in the country. Initial presumptions are based on the existing economic theory as well as on the author´s own speculation. The first part is devoted to the demand - a description of the general characteristics and influencing factors. The second part focuses on the specifics of the demand in the passenger car market and analysis of the factors influencing the demand for cars in the Czech Republic. The statistical methods will be used to analyse and evaluate these factors. The analysed data represent time series data which are adjusted to the thesis needs by means of proper methods. The conclusion evaluates the effects of the factors on the demand.
Seasonal exponential smoothing
Rábek, Július ; Cipra, Tomáš (advisor) ; Zichová, Jitka (referee)
This thesis deals with the issues of time series modeling, where seasonal component is present. Principles of basic seasonal exponential smoothing methods: simple and double exponential smoothing, Holt's method, which are applicable on time series without seasonality, are described in the beginning. For seasonal time series, Holt-Winters exponential smoothing is the most suitable method. This method is introduced in both of its versions and the usage of either version depends on the characteristics of the seasonal component. Furthermore, state space modeling is presented as a statistical framework for exponential smoothing methods, joined with a discussion of some selected problems related with practical implementation of these techniques together with suggestions of their solution. Finally, Holt-Winters method on two real data time series with seasonality is presented.
Statistical Analysis of Risk Factors of a Company
Semchiv, Evgheni ; Šebestová, Monika (referee) ; Karpíšek, Zdeněk (advisor)
This master`s thesis deals with the use of statistical and economic methods of analysis for evaluation of the financial situation of Heineken Czech Republic a.s. Company's economic indicators are subjected to regression analysis, interval regression analysis, and time series analysis. The proposal part contains a detailed evaluation of the results of the analyzes, evaluation of the financial risk factors and recommendations for improving the financial situation of the company.
Statistical Analysis of Risk Indicators of a Company
Procházka, Martin ; Jančíková, Kateřina (referee) ; Karpíšek, Zdeněk (advisor)
This diploma thesis aims at analyzing accounting and financial indicators using time series, regression analysis and interval regression analysis of selected company VIDEN plus, a.s. The thesis analyzes the development trends of individual indicators, which are able to reveal the state of the company. Based on the data obtained, the issue of company risks arising from the analyzes and their correction is then addressed.
Selected Quantitative Methods and their Using into Financial Analysis of the Commercial Chain
Rečka, Ondřej ; Hanušová, Helena (referee) ; Chvátalová, Zuzana (advisor)
The bachelor’s thesis focuses on the evaluation of the results of the financial analysis and it’s interpretation for assessing the financial health of the company. The financial analysis is performed using ratio indicators, their time series, regression models of selected indicators for time development identification. Maple mathematical software and MS Excel software were selected to apply the selected quantitative methods. The resulting interpretation of the results of the financial analysis serves as a suggestion for possible improvement of the financial situation of the analyzed company.
Mathematical and Statistical Methods as Support of the Development of Software Applications
Medek, Jiří ; Šustrová, Tereza (referee) ; Novotná, Veronika (advisor)
The bachelor thesis focus on the analysis of development of financial indicators and selected items from profit and loss account. Analysis is realized using time series and regression analysis. Part of thesis is developing application that allows automation of calculations and graphical display of calculated values.

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