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Time Series Analysis and Comparison by Means of Statistical Methods
Kopecký, Radek ; Bednář, Josef (referee) ; Žák, Libor (advisor)
The aim of the thesis mainly is to understand an issue of time series analysis. There are many methods in time series analysis, but purpose of this analysis persists the same, which is a construction of sufficient model of time series and his application in forecasting of time series. We have to make a basic identification of time series to establish right process in model constructing. The first and the second chapter is devoted to this basic identification. There are many methods, how we said before, for constructing of concrete model. In this thesis, exactly in the third chapter, we introduce one of the most flexible methodology of model constructing. That is The Box-Jenkins methodology, which was defined in 1976 by these men. In the last chapter we try to put to use insight in the issue of time series analysis for comparison and separation of the space of time series and this comparison use for the right interpretation of the parameters of time series model. The diploma project was supported by project from MSMT of the Czech Republic no. 1M06047 "Centre for Quality and Reliability of Production".
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Analysis of Financial Time Series During a Crisis
PRŮDEK, Lukáš
In this thesis, we will analyze financial time series during and before the crisis. These series will be analyzed using the Box-Jenkins methodology. The aim is to understand this method and then apply it to the prices of the DAX and PX stock indices. The DAX stock index values were compiled by the Frankfurt Stock Exchange and the PX index values were compiled by the Prague Stock Exchange. I will attempt to build models that can reliably describe the series in question for subsequent forecasting over sub-periods. These models and the predictions made from them will then be used to compare changes in time series behaviour.
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Analysis of Selected Climatological Time Series
Kraitz, Petr ; Helman, Karel (advisor) ; Šimpach, Ondřej (referee)
Dissertation is focused on analysis of time series of monthly mean temperatures of seven meteorological stations between years 1960 to 2015. With the use of selected statistical methods time series are modelled in moving ten year long intervals and a forecast of elevenths year is constructed. The goal of this dissertation is to compare the success of different methods/models predictions of values for one year period, based on the data from last 10 years.
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Time series annalyze by neural networks models
Jiráň, Robin ; Arltová, Markéta (advisor) ; Žižka, David (referee)
This thesis deals about using models of neural networks like alternative of time series model based on Box-Jenkins methodology. The work is divided into two parts according to the model construction method. Each of the parts contains a theory that explains the individual processes and the progress of the model construction. This is followed by two experiments demonstrating the difference in approach to the design of a given model and creating a forecast by estimated values. for the following year. The last part expertly evaluates the quality of the predictions and considers the use of neural networks against prediction models as an alternative to Box-Jenkins methodology based models
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Time Series Analysis and Comparison by Means of Statistical Methods
Kopecký, Radek ; Bednář, Josef (referee) ; Žák, Libor (advisor)
The aim of the thesis mainly is to understand an issue of time series analysis. There are many methods in time series analysis, but purpose of this analysis persists the same, which is a construction of sufficient model of time series and his application in forecasting of time series. We have to make a basic identification of time series to establish right process in model constructing. The first and the second chapter is devoted to this basic identification. There are many methods, how we said before, for constructing of concrete model. In this thesis, exactly in the third chapter, we introduce one of the most flexible methodology of model constructing. That is The Box-Jenkins methodology, which was defined in 1976 by these men. In the last chapter we try to put to use insight in the issue of time series analysis for comparison and separation of the space of time series and this comparison use for the right interpretation of the parameters of time series model. The diploma project was supported by project from MSMT of the Czech Republic no. 1M06047 "Centre for Quality and Reliability of Production".
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Statistical methods in demographic forecasting
Šimpach, Ondřej ; Langhamrová, Jitka (advisor) ; Arltová, Markéta (referee) ; Palát, Milan (referee)
Dissertation thesis creates a complex and modern scheme for stochastic modeling of demographic processes, which is universally applicable to any population in the world. All calculations are described in detail on the data of the Czech Republic. Throughout the work the attention is drawn to the issues, that every analyst must necessarily take into account in order to obtain correct results. Data comes mostly from the Czech Statistical Office database. However, some data matrices had to be calculated for the purposes of the thesis. Particular demographic processes (mortality, fertility and migration) are modeled using selected modern approaches (ARIMA models, Lee-Carter method) and based on the constructed models these processes are forecasted to the future. Using partially projected results a comprehensive demographic projection of the population of the Czech Republic is created up to the year 2050. However, not on the basis of the current state and expert expectations of the future development, but based on sophistically projected demographic events, which are explained using the trends and main components of their previous development. This demographic projection is created in three scenarios (marked SC1, SC2 and SC3), which are made from selected optimal models, presented in particular sections of the work. One part of the thesis is also the backward retropolation of age-specific number of net migrants by sex in the Czech Republic since 1948. On its basis the analysis and prediction of the migration can be done. The thesis is a synthesis of the projections of demographic processess of mortality, fertility, and migration. Final results are confronted with three scenarios of population projections of the Czech Republic created by the Czech Statistical Office and five scenarios of population projections by Eurostat. The purely statistical approach of demographic forecasting in comparison with deterministic models and expert expectations has its positives and negatives. Therefore, the different results due to various methodological approaches are discussed and compared in the conclusion of the thesis.
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Analysis of monthly precipitation totals from selected monitoring stations in Europe
Krause, Patrik ; Helman, Karel (advisor) ; Kladívko, Kamil (referee)
This thesis is focused on analysis of time series of monthly precipitation totals for four European stations for the years 1913 to 2012. The data were obtained from European database of ECA&D. The aim of this thesis is to find out development of time series and predict precipitation for the year 2013. Prediction of future development of time series is made by using regression modeling of seasonality and Box-Jenkins methodology and the results obtained by the two methods are then compared. The thesis is divided into theoretical and practical parts.
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Mathematical modelling of crown rate
UHLÍŘOVÁ, Žaneta
This thesis is focused on mathematical modelling of exchange rate CZK/USD in 1991 - 2014. Time series was divided into 5 parts. First Box-Jenkins methodology models were examined, especially ARIMA model. Unfortunately, the model could not be used because none of the time series showed correlation. The time series is considered as a white noise. The data appear to be completely random and unpredictable. The time series have not constant variance neither normal distribution and therefore GARCH volatility model was used as the second model. It is better not to divide time series when using model of volatility. Volatility model contributes to more accurate prediction than the standard deviation. Results were calculated in RStudio software and MS Excel.
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Analysis of average wage in Czech Republic
Zimmerhaklová, Tereza ; Arltová, Markéta (advisor) ; Jeřábková, Věra (referee)
This thesis is focused on analysis of the development of gross month wage and in particular on development and examining seasonality. There are also described the institutions and their surveys of wages, such as the Czech Statistical Office, Ministry of Finance and the Ministry of Labor and Social Affairs, which administers the Information System of Average Earnings. The monthly income is compared between regions and between major classes KZAM. The development of time series is modeled by the Box-Jenkins methodology, further charts of seasonal values and seasonal indexes . For comparison the average relative wage growth in regions are used cartograms. The base for these analyses is data obtained from business statistical return systems and structural statistics from the site of the Czech Statistical Office and the Ministry of Labor and Social Affairs.
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