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Statistical analysis and modeling of inflation
Baniar, Matúš ; Zichová, Jitka (advisor) ; Hurt, Jan (referee)
Title: Inflation modeling Author: Matúš Baniar Department: Department of probability and mathematical statistics Supervisor: RNDr. Jitka Zichová Dr., Department of probability and mathematical statistics Abstract: Inflation, the growth of the general price level, is a common economic phenomenon, which is a macroeconomic problem. The thesis deals with the me- thods by which it is possible to model inflation and therefore to understand its de- velopment. In the first case, the correlation and regression analysis, which deal with the relationship of two or more variables and the following selection of the appro- priate mathematical model. The model of linear regression is described also with methods by which we analyze its adequacy. Another described method is the analy- sis of one-dimensional time series, which we apply so called Box-Jenkins methodol- ogy. Both approaches are illustrated on real financial data using the software Wol- fram Mathematica 8. Keywords: inflation, correlation analysis, regression analysis, time series
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Non-Linear Classification as a Tool for Predicting Tennis Matches
Hostačný, Jakub ; Baniar, Matúš (advisor) ; Krištoufek, Ladislav (referee)
Charles University Faculty of Social Sciences Institute of Economic Studies MASTER'S THESIS Non-Linear Classification as a Tool for Predicting Tennis Matches Author: Be. Jakub Hostacny Supervisor: RNDr. Matus Baniar Academic Year: 2017/2018 Abstract In this thesis, we examine the prediction accuracy and the betting performance of four machine learning algorithms applied to men tennis matches - penalized logistic regression, random forest, boosted trees, and artificial neural networks. To do so, we employ 40 310 ATP matches played during 1/2001-10/2016 and 342 input features. As for the prediction accuracy, our models outperform current state-of-art models for both non-grand-slam (69%) and grand slam matches (79%). Concerning the overall accuracy rate, all model specifications beat backing a better-ranked player, while the majority also surpasses backing a bookmaker's favourite. As far as the betting performance is concerned, we develop six profitable betting strategies for betting on favourites applied to non-grand-slam with ROI ranging from 0.8% to 6.5%. Also, we identify ten profitable betting strategies for betting on favourites applied to grand slam matches with ROI fluctuating between 0.7% and 9.3%. We beat both bench mark rules - backing a better-ranked player as well as backing a bookmaker's...
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Econometric Analysis of Financial Data
Baniar, Matúš ; Zichová, Jitka (advisor) ; Cipra, Tomáš (referee)
Econometric Analysis of Financial Data Author: Matúš Baniar Department: Department of Probability and Mathematical Statistics Supervisor: RNDr. Jitka Zichová, Dr. Abstract: In some occasions, financial data can be represented as a combination of cross-sectional and time-series information. Hence it could be convenient to consider a system of econometric equations for modeling such data sets. At the beginning of this thesis, we describe general definitions and we talk about different types of variables from the perspective of exogeneity. Later, we describe some specific cases of these equations: SUR system, simultaneous equation models and the model of vector autoregression. For selected models, we also discuss estimation methods and their properties. In the final section, the described approach is applied to real financial data making use of appropriate software. Keywords: exogeneity, SUR system, simultaneous equations, VAR
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Non-Linear Classification as a Tool for Predicting Tennis Matches
Hostačný, Jakub ; Baniar, Matúš (advisor) ; Krištoufek, Ladislav (referee)
Charles University Faculty of Social Sciences Institute of Economic Studies MASTER'S THESIS Non-Linear Classification as a Tool for Predicting Tennis Matches Author: Be. Jakub Hostacny Supervisor: RNDr. Matus Baniar Academic Year: 2017/2018 Abstract In this thesis, we examine the prediction accuracy and the betting performance of four machine learning algorithms applied to men tennis matches - penalized logistic regression, random forest, boosted trees, and artificial neural networks. To do so, we employ 40 310 ATP matches played during 1/2001-10/2016 and 342 input features. As for the prediction accuracy, our models outperform current state-of-art models for both non-grand-slam (69%) and grand slam matches (79%). Concerning the overall accuracy rate, all model specifications beat backing a better-ranked player, while the majority also surpasses backing a bookmaker's favourite. As far as the betting performance is concerned, we develop six profitable betting strategies for betting on favourites applied to non-grand-slam with ROI ranging from 0.8% to 6.5%. Also, we identify ten profitable betting strategies for betting on favourites applied to grand slam matches with ROI fluctuating between 0.7% and 9.3%. We beat both bench mark rules - backing a better-ranked player as well as backing a bookmaker's...
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Building Societies in Low Interest Rate Environment
Hanzlík, Petr ; Džmuráňová, Hana (advisor) ; Baniar, Matúš (referee)
The aim of this thesis is to analyse the impact of low interest rate environment in the Czech Republic in recent years on the sector of building societies as a specific segment of the financial market. First part of the thesis consists of description of main characteristics of building savings and building societies, e.g. their historical development, with special focus on main types of risk the building societies face. In the second part the impact of changing market interest rate on outstanding volumes of deposits in building societies is analysed. The analysis is conducted through simple time series models estimated by OLS. Final part includes comparison of demand for building savings loans with demand for mortgages as well as consideration of the development of profitability of the sector of building societies in recent years. Powered by TCPDF (www.tcpdf.org)
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Econometric Analysis of Financial Data
Baniar, Matúš ; Zichová, Jitka (advisor) ; Cipra, Tomáš (referee)
Econometric Analysis of Financial Data Author: Matúš Baniar Department: Department of Probability and Mathematical Statistics Supervisor: RNDr. Jitka Zichová, Dr. Abstract: In some occasions, financial data can be represented as a combination of cross-sectional and time-series information. Hence it could be convenient to consider a system of econometric equations for modeling such data sets. At the beginning of this thesis, we describe general definitions and we talk about different types of variables from the perspective of exogeneity. Later, we describe some specific cases of these equations: SUR system, simultaneous equation models and the model of vector autoregression. For selected models, we also discuss estimation methods and their properties. In the final section, the described approach is applied to real financial data making use of appropriate software. Keywords: exogeneity, SUR system, simultaneous equations, VAR
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Econometric Analysis of Financial Data
Baniar, Matúš ; Zichová, Jitka (advisor) ; Cipra, Tomáš (referee)
Econometric Analysis of Financial Data Author: Matúš Baniar Department: Department of Probability and Mathematical Statistics Supervisor: RNDr. Jitka Zichová, Dr. Abstract: In some occasions, financial data can be represented as a combination of cross-sectional and time-series information. Hence it could be convenient to consider a system of econometric equations for modeling such data sets. At the beginning of this thesis, we describe general definitions and we talk about different types of variables from the perspective of exogeneity. Later, we describe some specific cases of these equations: SUR system, simultaneous equation models and the model of vector autoregression. For selected models, we also discuss estimation methods and their properties. In the final section, the described approach is applied to real financial data making use of appropriate software. Keywords: exogeneity, SUR system, simultaneous equations, VAR
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Statistical analysis and modeling of inflation
Baniar, Matúš ; Zichová, Jitka (advisor) ; Hurt, Jan (referee)
Title: Inflation modeling Author: Matúš Baniar Department: Department of probability and mathematical statistics Supervisor: RNDr. Jitka Zichová Dr., Department of probability and mathematical statistics Abstract: Inflation, the growth of the general price level, is a common economic phenomenon, which is a macroeconomic problem. The thesis deals with the me- thods by which it is possible to model inflation and therefore to understand its de- velopment. In the first case, the correlation and regression analysis, which deal with the relationship of two or more variables and the following selection of the appro- priate mathematical model. The model of linear regression is described also with methods by which we analyze its adequacy. Another described method is the analy- sis of one-dimensional time series, which we apply so called Box-Jenkins methodol- ogy. Both approaches are illustrated on real financial data using the software Wol- fram Mathematica 8. Keywords: inflation, correlation analysis, regression analysis, time series
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