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Bootstrap in financial time series
Krnáč, Ján ; Prášková, Zuzana (advisor) ; Hušková, Marie (referee)
In this diploma thesis we explain the main principles and properties of bootstrap methods, that can be used to conduct the statistical inference in linear and nonlinear financial time series. We will introduce basic ideas of bootstrap methods for the case when observations can be considered as independent random variables, and afterwards we will describe more advanced methods, that can be successfully used when we are dealing with time series. Thesis deals with both parametric bootstrap methods, that we can use when the underlying parametric model of observations is available, as well as with nonparametric bootstrap methods that are used when more general nonparametric model of time series data is considered. The main objective is to compare particular bootstrap methods and show the usage of these methods on real world data. There is also a basic time series theory included in the work. 1
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Selected methods of time series analysis with STATISTICA
Indrová, Magdalena ; Hudecová, Šárka (advisor) ; Zichová, Jitka (referee)
This work deals with the use of STATISTICA software for the basic analysis of time series. The thesis is focused on time series decomposition, mainly on the trend elimination. First, the basic methods of the analysis are described theoretically, namely, trend modeling using mathematical curves (polynomial, exponential, logistic and Gompertz) and adaptive approach (moving averages, simple exponential smoothing and Holt's method). These methods are then applied to three selected data sets (unnamed bank's balance sheet from 1998 to 1993, ship construction trends between 1820 and 1997, and CZK/EUR Exchange rate from 1998 to 2012). All analytical procedures are described in detail and individual program outputs are thoroughly explained and commented.
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Long-term memory detection with bootstrapping techniques: empirical analysis
Albert, Branislav ; Krištoufek, Ladislav (advisor) ; Avdulaj, Krenar (referee)
A time series has long range dependence if its autocorrelation function is not absolutely convergent. Presence of long memory in a time series has important consequences for consistency of several time series estimators and forecasting. We present a self-contained theoretical treatment of time series models necessary for study of long range dependence and survey a large list of parametric and semiparametric estimators of long range dependence. In a Monte Carlo study, we compare size and power properties of four estimators, namely R/S, DFA, GPH and Wavelet based method, when relying on asymptotic normality of the estimators and distributions obtained from the moving block bootstrap. We find out that the moving block bootstrap can improve the size of the R/S estimator. In general however, the moving block bootstrap did not perform satisfactorily for other estimators. GPH and Wavelet estimators offer the most reliable asymptotic confidence intervals.
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Demographic development in muslim countries with evaluation of possible influence of Islam
Boďová, Daniela ; Hulíková Tesárková, Klára (advisor) ; Kocourková, Jiřina (referee)
Demographic development in Muslim countries with evaluation of possible influence of Islam Abstract The objective of this study is to analyse and to evaluate the demographic development during the second half of 20th century in chosen Muslim countries. Primarily, processes of mortality and fertility are analysed; describing of processes of nuptiality and divorce are more likely additional. In the first part, chosen muslim countries are divided into groups, and the relationship of Islam and demographic processes is described. In the second part is an analysis focused on describing processes, prediction to the future and on proving possible influence of Islam on mortality and fertility. The analysis supported basic hypothesis that Islam hasn't decisive influence on these processes. Results of analysis are consulted with theoretical background from the first part and then compared with preliminary hypothese in the conclusion. Keywords: Muslim countries, Islam, mortality and fertility, time series, cointegration of time series
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Forecasting the Exchange Rate in the Czech Republic Using Non-linear Threshold Models
Žák, Petr ; Stráský, Josef (advisor) ; Kočenda, Evžen (referee)
The aim of this thesis is to analyze the performance of nonlinear threshold models in forecasting the exchange rate of Czech koruna against EUR. Data for this study were obtained from Statistical Data Warehouse of European Central Bank (ECB) website, from Czech National Bank (CNB) Board decisions minutes and from the press releases of Governing Council of ECB. The data set was split into two periods - from 1999 until November, 2013 when CNB started to use interventions and from November, 2013 until April, 2016. Models used in the thesis are Self-Exciting Threshold Auto Regressive (SETAR) models with one and two thresholds and two Threshold Auto Regres- sive (TAR) models with different threshold variables - meetings of CNB Board as dummy variable and average volatility over recent periods. The forecasting results indicate that SETAR models did not outperform Random Walk in any period. TAR models offered promising results in the period before interventions and surprisingly failed in the period during interventions. This study supports the general belief of exchange rates being difficult to forecast and that it holds in case of Czech koruna as well. JEL Classification F12, F21, F23 H25, H71, H87 Keywords forecasting, exchange rate, time series, nonlin- earity, SETAR, TAR Author's e-mail zaka.one@gmail.com...
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Analysis of time series of production of municipal waste in EU
Lupačová, Klára ; Helman, Karel (advisor) ; Arltová, Markéta (referee)
The bachelor thesis is focused on analyzing time series of production of municipal waste in EU during the period from 1995 to 2014. Data are from public databases Eurostat. The objective of thesis is to examine development of time series of production of municipal waste in EU. Another aim of thesis is to determine whether it will be recycled by 2020 at least 50 % of municipal waste. This thesis consist of two pars. The (theoretical).first part is devoted to the description of the statisticla methods and second (practical) part is dedicated to the analysis of time series.
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AI techniques in algorhitmic trading
Šmejkal, Oldřich ; Pavlíčková, Jarmila (advisor) ; Berka, Petr (referee)
Diploma thesis is focused on research and description of current state of machine learning field, focusing on methods that can be used for prediction and classification of time series, which could be then applied in the algorithmic trading field. Reading of theoretical section should explain basic principles of financial markets, algorithmic trading and machine learning also to reader, which was previously familiar with the subject only very thoroughly. Main objective of application part is to choose appropriate methods and procedures, which match current state of art techniques in machine learning field. Next step is to apply it to historical price data. Result of application of selected methods is determination of their success at out of sample data that was not used during model calibration. Success of prediction was evaluated by accuracy metric along with Sharpe ratio of basic trading strategy that is based on model predictions. Secondary outcome of this work is to explore possibilities and test usability of technologies used in application part. Specifically is tested and used SciPy environment, that combines Python with packages and tools designed for data analysis, statistics and machine learning.
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Statistical analysis of unemployment development in Lovosicko with attention to risk groups
Beránková, Hana ; Prášilová, Marie (advisor) ; Luděk, Luděk (referee)
This diploma thesis analyses the development of proportion of unemployed people and of job applicants registered with the Labour Offices in Lovosice. It specially focuses on groups at risk - women, graduates and adolescents, disabled persons and people who have been registered with the Labour office for more than 12 months. The data used for the analysis were found on the Internet portals of the Czech Statistical Office, of Ministry of Labour and Social Affairs and the Labour Offices in Ústí nad Labem, Litoměřice and Lovosice. The thesis comprises of the development of overall unemployment analysis in the microregion. Using statistical methods, I evaluated the monitored figures in years from 2005 to 2015. Elementary characteristics of time series and trendy functions were used for the solution. Subsequently, the work includes prediction of further development of unemployment and survey evaluation. At the end, I suggested ways of decreasing unemployment of selected high-risk persons.
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Statistical analysis of drug addiction in the South Bohemia Region
Vrtišková, Šárka ; Prášilová, Marie (advisor) ; Irena, Irena (referee)
The aim of this thesis is the statistical analysis of drug users of drugs other than alcohol in the south bohemian region for the period 2005-2014. Drug addiction is analyzed according to the number of drug users and their average age and by individual drugs used. Another part of the thesis is the analysis of drug-related crime, which is estimated according to the number of drug offenders, according to their sex, age and nationality. Another indicator of statistical analysis are preventive programs operating in the South Region. With the help of elemental characteristics of time lines and trend functions is calculated estimated future development of these indicators for 2015 - 2017. Part of the diploma thesis is to evaluate the situation of drug addiction in the South Region, with suggestions for solving this problem.
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