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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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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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Do Gun Buybacks Have Effect on Crime Rate?
Chmelík, Pavel ; Komrska, Martin (advisor) ; Kadeřábková, Božena (referee)
This paper analyzes effect of gun buyback that took place in Great Britain in years 1996 and 1997 on crime rate and compares the results with theoretical arguments and previous empirical findings. It contains analysis of three independent time series: crime rate in England and Wales, Scotland and Northern Ireland. Models of the time series are built using Box-Jenkins methodology. The models are tested for presence of a structural break using visual analysis, Chow test and Quandt-Andrews test. These tests are used as an evaluation criterion of the effect of buyback on crime rate. The result of the analysis is that it is not possible to reject the null hypothesis that buybacks do not have effect on crime rate.
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Money multiplier and its predictability in Czech Republic
Maxa, David ; Potužák, Pavel (advisor) ; Chytilová, Helena (referee)
This paper examines the stability of money multiplier. The main aim is to verify the stationarity of money multiplier and evaluate the accuracy of its forecasts in Czech Republic. The stationarity of the time series is tested by augmented Dickey-Fuller and KPSS tests. Special unit root tests taking account for structural changes are also employed. The results indicate that all money multiplier time series are non-stationary at levels. The predictions are based on ARIMA models identified via Box-Jenkins methodology. The accuracy of predictions is measured by the range of prediction intervals. The range of 95% confidence prediction intervals varies from 0.5 to 1 based on the type of money multiplier. The accuracy of predictions cannot be labeled as highly precise.
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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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