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Modely dynamické podmíněné korelace a jejich aplikace při mitigaci rizika portfolia
Ševčík, Martin ; Frýd, Lukáš (advisor) ; Nevrla, Matěj (referee)
This bachelor thesis investigates asymmetry in returns of corn, gold and crude oil (both spot and futures) and hedging effectiveness of these commodities when employing DCC family models for hedge ratio estimation. The asymmetry in conditional variances was found to be significant only in case of crude oil spot and futures returns and asymmetry in conditional correlation of spot and futures returns was not shown to be significant in neither of the investigated commodities. With respect to the hedging performance, we conclude that differences in hedging performance measured by hedging effectiveness index are negligible and thus do not support superiority of DCC family models over OLS, which served as a benchmark. Historical Value at Risk, on the contrary, identified the DCC with asymmetry in conditional variance (despite asymmetry not being significant) to be appropriate for corn hedging, however not for the other two commodities, where the OLS based hedge ratio performed similarly or even better than the DCC family models. The main contribution of the thesis thus lays in empirical investigation of asymmetry in returns of selected commodities and testing hedging potential of DCC family based hedge ratio.
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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.
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The impact of ECB communication on selected financial markets in eurozone
Luková, Veronika ; Moravcová, Michala (advisor) ; Hauzr, Marek (referee)
This thesis investigates the impact of the European central bank communication and macroeconomic news announcements on the price and volatility of selected financial markets. We examine the stock markets of Germany and countries of PIGS (Portugal, Italy, Greece, Spain), we selected the stock indices as the financial assets, we employed the GARCH (1,1) and EGARCH (1,1) models. Main result was that the communication of ECB has significant impact on the volatility of all examined stock markets. Volatilities of German and Italian stock markets are the most influenced ones. Volatility of Portugal stock market is the least influenced one. The ECB's communication affects also the level of examined stock markets except Portugal stock market. Our re sults also confirmed that the macroeconomic announcements have significant impact on the volatility, but they have no fundamental impact on the level of these stock markets. 1
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The Inflation-Output Variability Relationship in the CEE countries: A Bivariate GARCH Model
Kubovič, Jozef ; Čech, František (advisor) ; Červinka, Michal (referee)
This thesis examines the output-variability relationship and causal relationships among the inflation, the output growth and their uncertainties for the Central and Eastern European region during the period of time that covers the economic crisis of 2008. We apply the bivariate GARCH(1,1) model with the constant conditional correlation covariance matrix to obtain conditional variances that proxy the two uncertainties and use Granger causality test to determine the causal effects among four variables. We come up with a number of interesting results. First, we did not find statistical evidence neither for the inflation-output variability relationship nor for the Phillips curve. Second, we uncovered support for the positive causal effect of the inflation on its uncertainty and negative causal effect for the reverse direction. Additionally, we also found some support for the indirect negative causal effect of the inflation on the output growth. These results support the policy of low and stable inflation in the countries. Finally, we showed that crisis has a significant impact on the results, changing the behaviour of conditional variances and causal effects among the variables. Powered by TCPDF (www.tcpdf.org)
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Forecasting electricity prices in the Czech spot market
Černý, Kryštof ; Lebovič, Michal (advisor) ; Rečka, Lukáš (referee)
This master thesis is focused on analysis and forecasting of hourly and daily electricity price on the deregulated Czech daily electricity market. The methods used for estimating and forecasting hourly and daily prices are picked from the ARIMA-GARCH family of models and Neural Networks. For daily price data, the Redundant Haar Wavelet Transform decomposition of the time series is used in combination with ARIMA and Neural Networks models for forecasting. For hourly data, ARIMA and Neural Network models are considered. The forecasting results of daily data indicate that simpler models such as seasonal ARIMA outperform all other methods. Also the wavelet decomposi- tion of the daily series didn't prove useful in enhancing the forecast precision. For hourly data, the Multilayer Perceptron architecture of the neural network outperformed the ARIMA forecast. JEL Classification C20, C22, C45, C53, C65 Keywords Forecasting, Time Series, ARIMA, GARCH, Neural Net- works, Wavelet Transform Author's e-mail krystof.cerny@gmail.com Supervisor's e-mail lebovicm@gmail.com 1
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Government bonds and stock market volatility: A Multivariate GARCH Analysis
Aliakseyeu, Aliaksei ; Horváth, Roman (advisor) ; Čech, František (referee)
The correlation between stock market returns and changes in bond market yields are of big interest among investors because this indicator helps them allocate their assets and diversify investment risk more effectively. An in- vestor should keep track of development of the economies of individual coun- tries, understand the causes of dissimilarities in the correlations among them and take these differences into account for successful international financial investment. The current author contributes to the existing researches by the modeling of stock-bond market co-movements using the updated datasets with focus on Central European countries and differences in public debt levels. The paper contains the empirical analysis of stock and bond market returns condi- tional correlations, modeled by the use of the Asymmetric Generalized Dynamic Conditional Correlation (AG-DCC) Generalized Autoregressive Conditional Het- eroskedasticity (GARCH) specification, for nine Western and Central European countries (the United Kingdom, Germany, France, Spain, Portugal, Italy, Czech Republic, Poland and Hungary) that differ both by their geographic locations and economic development. The main distinctions in the correlations are ob- served during the European sovereign debt crisis. The three types of develop- ment are...
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Selected problems of financial time series modelling
Hendrych, Radek ; Cipra, Tomáš (advisor) ; Arlt, Josef (referee) ; Prášková, Zuzana (referee)
Title: Selected problems of financial time series modelling Author: Radek Hendrych Department: Department of Probability and Mathematical Statistics (DPMS) Supervisor: Prof. RNDr. Tomáš Cipra, DrSc., DPMS Abstract: The present dissertation thesis deals with selected problems of financial time series analysis. In particular, it focuses on two fundamental aspects of condi- tional heteroscedasticity modelling. The first part of the thesis introduces and discusses self-weighted recursive estimation algorithms for several classic univariate conditional heteroscedasticity models, namely for the ARCH, GARCH, RiskMetrics EWMA, and GJR-GARCH processes. Their numerical capabilities are demonstrated by Monte Carlo experiments and real data examples. The second part of the thesis proposes a novel approach to conditional covariance (correlation) modelling. The suggested modelling technique has been inspired by the essential idea of the multivariate orthogonal GARCH method. It is based on a suitable type of linear time-varying orthogonal transformation, which enables to employ the constant conditional correlation scheme. The correspond- ing model is implemented by using a nonlinear discrete-time state space representation. The proposed approach is compared with other commonly applied models. It demon- strates its...
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Does Bitcoin Have Potential To Co-Function with Fiat Money?
Kurka, Josef ; Dědek, Oldřich (advisor) ; Vacek, Pavel (referee)
This paper examines the potential of Bitcoin, a decentralized digital currency, to pose competition to fiat currencies. To accomplish that, Bitcoin would have to become efficient as a store of value. Thus far, high volatility makes it inferior in that respect. We analyze the dynamics and drivers of Bitcoin volatility using GARCH and HAR models. Moreover, we test for presence of asymmetries displayed by stock, commodity and currency markets. That way we can conclude, whether volatility of Bitcoin behaves similarly to currencies, commodities or stocks. Lastly we reveal interconnections between these markets and market for Bitcoin. We find significant evidence for the leverage effect documented for stock market. Furthermore, the effect of trading volume, documented for currency markets, displays an opposite sign in our research. Results of spillover estimation suggest Bitcoin is the most interconnected with commodity market. Thus, we conclude Bitcoin does not behave similarly to currencies in terms of volatility; hence is not a good candidate to substitute them. JEL Classification E1, G1, G2, O3 Keywords Bitcoin, volatility, GARCH, leverage effect Author's e-mail 24805288@fsv.cuni.cz Supervisor's e-mail dedek@fsv.cuni.cz
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The Effects of Foreign Exchange Interventions in a Small Open Economy: The Case of the Czech Republic in a World Context
Timko, Jan ; Holub, Tomáš (advisor) ; Dědek, Oldřich (referee)
In this thesis we examine the effect of foreign exchange interventions in small open economy, focusing on the Czech experience. In the first part we model volatility development before and after the intervention using GARCH model. In the second part we estimate relationship between macroeconomical variables using vector autoregressive model. In this part we estimate impulse response function of exchange rate and inflation. In second part of VAR modeling we provide counterfactual analysis, which compare actual development of variables with alternative scenario in which the interventions would not happen . Our results suggest that the interventions is associated with few months delayed decrease in volatility. Base on scenario analysis the interventions increased inflation by approximately 1.5 % and without the intervention the economy would in deflation around -1 % nowadays. KEYWORDS: Vector autoregression, Volatility modelling, Monetary policy, Intervention Author's e-mail: jantimko16@gmail.com Supervisor's e-mail: tomas.holub@cnb.cz
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The Impact of Macroeconomic News on the Price of Financial Assets
Říha, Jakub ; Moravcová, Michala (advisor) ; Džmuráňová, Hana (referee)
This thesis investigates the effect of Czech macroeconomic news announcements and Czech National Bank (CNB) communication on the price of financial assets and its volatility. As the financial assets we selected the EUR/CZK and USD/CZK exchange rates and also the Prague stock PX Index. To analyze the aforesaid effect we employed the GARCH (1,1) and EGARCH (1,1) models, each with Normal and Student's t error distribution. The main results were that the CNB's communication indeed have significant effect on the price of all three examined assets and surprisingly also tend to increase their volatility. Also the macroeconomic announcements significantly influence examined assets however significant macroeconomic indicators differ for each asset. The most influencing ones are: CPI, 1YPRIBOR and the unemployment rate. Another finding of our research was that volatility of examined time series data shows the characteristics of leverage effect, volatility clustering and persistence. Powered by TCPDF (www.tcpdf.org)
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