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Multifractal Analysis of Stock Market Prices
Čechová, Kristýna ; Krištoufek, Ladislav (advisor) ; Vošvrda, Miloslav (referee)
The aim of this thesis is to provide an empirical evidence of multifractality in financial time series and to discuss the relevance of this concept for the current financial theory. We have applied two methods, the Multifractal Detrended Fluctuation analysis and the Generalized Hurst exponent method, on components of the Dow Jones Industrial Average. We analyzed daily data of 30 companies traded on U.S. stock markets from 2002 to 2012. We present results supporting presence of multiscaling in open-close returns. Contrary to published literature, we were not able to find any significant multiscaling in volatility. Moreover based on our analysis, multiscaling is not present in standardized returns and as multifractality requires relatively complicated models, this is our most valuable result. 1
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System Priors for Econometric Time Series
Andrle, Michal ; Plašil, Miroslav
This paper introduces “system priors” into Bayesian analysis of econometric time series and provides a simple and illustrative application. Unlike priors on individual parameters, system priors offer a simple and efficient way of formulating well-defined and economically meaningful priors about model properties that determine the overall behavior of the model. The generality of system priors is illustrated using an AR(2) process with a prior that its dynamics comes mostly from business-cycle frequencies.
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Assessing Selected Indicators Using Time Series Analysis
Turisová, Alena ; Novotná, Veronika (referee) ; Doubravský, Karel (advisor)
Master's thesis deals with the assessment of selected financial indicators of the production company X in order to evaluate its performance and financial situation. Based on the results of the analyzes for the period 2008 to 2015 and the application of statistical methods of time series analysis and regression analysis, prognosis of future development of monitored indicators are obtained. Subsequently, the prognosis are used for the final formulating of proposals to improve future business efficiency of the company.
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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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Assessing the Economic Indicators of a Company Using Time Series Analysis
Mičák, Peter ; Kľačanská, Jana (referee) ; Doubravský, Karel (advisor)
The goal of this bachelor’s thesis is assessment of the state of the company based on analysis of the economic indicators using statististical method of regression analysis and time series. First part of this bachelor’s thesis contains theoretical basis of financial analysis, regression analysis and analysis based on time series. The second part is devoted to perform analysis on the basis of financial statements of the observed company. Consequently, forecast is created for each indicator for the upcoming periods. The results of the analysis are described and on their basis are created measures that can help the company to effective fulfillment of it’s objectives.
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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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Analysis and modeling of network data traffic
Paukeje, Ján ; Novotný, Vít (referee) ; Růčka, Lukáš (advisor)
Theses deals with network traffic modeling focused on elaboration by time series analysis. The nature of network traffic is discussed above all http traffic. First three chapters are theoretical, which describes time series and basic models, linear AR, MA, ARMA, ARIMA and nonlinear ARCH. Other chapters define terms like self-similarity and long range dependence. It is demonstrated a failure of conventional models which cannot capture these specific properties of network data traffic. On the basis of study in chapter 6. is closely described the combined ARIMA/GARCH model and its parameter estimation procedure. Applied part of this theses deals with procedure of estimation and fitting the estimation model to observed network traffic. After an estimation a few future values are predicted on the basis of estimated model. These predicted values are consequently compared with real data.
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