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Volatility models in R
Vágner, Hubert
;
Bašta, Milan
(advisor) ;
Flimmel, Samuel
(referee)
This diploma thesis focuses on modeling volatility in financial time series. The main approach to modelling volatility is using GARCH models which can capture the variability of conditional volatility of time series. For modelling a conditional mean value in time series are used ARMA models. In the series there are usually not fulfilled the assumption of earnings normality, therefore, are the earnings in most cased characterized by the leptokurtic shape of distribution. The thesis introduces some more distribution types, which can be more easily used for the earnings distribution - above all the Students t distribution. The aim of the thesis in the first part is to present the topic of financial time series and description of the GARCH models including their further modification. There are used e.g. IGARCH or other models capturing asymmetric impact of shocks such as GJR-GARCH. The second part deals with generated data, where are more in detail explored the volatility models and their behavior in corresponding financial time series. The third part focuses on the volatility estimation and forecasting for the financial time series. Firstly this concerns development of stock index MICEX secondly currency pair Russian Ruble to Czech Crown and eventually price development of the Brent crude oil. The goal of the third part is to present the impacts on volatility of chosen time series applied on the example of economic sanctions against Russia after annexation of the Crimea peninsula which happened in the first quarter 2014.
Detailed record
Comparing of length of employment before and during the financial crisis
Vágner, Hubert
;
Čabla, Adam
(advisor) ;
Malá, Ivana
(referee)
In this bachelor thesis I introduce survival analysis and distribution of time-to-event. The analyzied subject is the resignation from work. It means that I find out and compare how long on average people had work before the financial recession of 2008-2009 and during the time period of the 2010-2011 recession. The data gathered is from the Labor Force Survey, which is produced by the Czech Statistical Office. I used interval censoring to gather the data for the average length of the working ratio. This means that we know that the observed event happened in a given interval, in this case the intervals are individual survays. First of all, it's necessary to estimate the survival function. We shall do this with the help of the nonparametrical Turnbull's estimate for data in interval censoring. Than we calculate individual averages. The empirical part will consist of individual comparisons of the survival function and the average lengths of the working ratio, first for the overall population, second for separate genders and finally for various education levels.
Detailed record
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