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Natural Gas Comovement with Other Commodity Markets - A Wavelet Analysis
Otradovec, Michal ; Gutiérrez Chvalkovská, Jana (advisor) ; Kraicová, Lucie (referee)
This thesis studies the impact of shale gas on commodity and stock markets in the U.S. by employing wavelet approach and conducting a time-frequency analysis of dynamic correlations between natural gas and important representatives of commodity markets: crude oil, coal, corn, wheat, and several indices. It covers the period from 2006 to 2015 and is performed on daily data. Our thesis enlarges existing literature on comovement between natural gas with other energy commodities and stocks using wavelet coherence - a methodology which allows analyzing comovement among assets not only from a time series perspective but also over different frequencies. Financialization of natural gas and its involvement in investment portfolios under changing conditions on the U.S. gas market provide space for examination of gas proper correlation estimates in respect to other financial assets. Our results reveal natural gas comovement behaviour with examined commodities during the Financial Crisis. They show gradual decoupling between gas and crude oil prices in time. To the best of our knowledge we are the first to address natural gas using wavelet coherence in connection to agricultural commodities corn and wheat. These commodities together with natural gas are primary sources for bioethanol production being used in...
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Practical usage of optimal portfolio diversification using maximum entropy principle
Chopyk, Ostap ; Krištoufek, Ladislav (advisor) ; Kraicová, Lucie (referee)
"Practical usage of optimal portfolio diversification using maximum entropy principle" by Ostap Chopyk Abstract This thesis enhances the investigation of the principle of maximum entropy, implied in the portfolio diversification problem, when portfolio consists of stocks. Entropy, as a measure of diversity, is used as the objective function in the optimization problem with given side constraints. The principle of maximum entropy, by the nature itself, suggests the solution for two problems; it reduces the estimation error of inputs, as it has a shrinkage interpretation and it leads to more diversified portfolio. Furthermore, improvement to the portfolio optimization is made by using design-free estimation of variance-covariance matrices of stock returns. Design-free estimation is proven to provide superior estimate of large variance-covariance matrices and for data with heavy-tailed densities. To asses and compare the performance of the portfolios, their out-of-sample Sharpe ratios are used. In nominal terms, the out-of- sample Sharpe ratios are almost always lower for the portfolios, created using maximum entropy principle, than for 'classical' Markowitz's efficient portfolio. However, this out-of-sample Sharpe ratios are not statistically different, as it was tested by constructing studentized time-series...
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Are financial returns and volatility multifractal at all?
Sedlaříková, Jana ; Krištoufek, Ladislav (advisor) ; Kraicová, Lucie (referee)
Over the last decades, multifractality has become a downright stylized fact in financial markets. However, its presence has not been adequately statistically proved. The main aim of this thesis is to contribute to the discussion by an ex- tensive statistical analysis of the problem. We investigate returns and volatility of the collection of the four stock indices employing the three popular methods: the GHE, the MF-DFA, and the MF-DMA method. By comparing the results of the original series to those for simulated monofractal series, we conclude that stock market returns as well as volatility exhibit a multifractal nature. Additionally, in order to understand the origin of underlying multifractality, we study vari- ous surrogate series. We found that a fat-tailed distribution significantly affects multifractality. On the other, we were not able to confirm the impact of time correlations as the results strongly depend on the applied model. JEL Classification F12, G02, G10, C12, C22, C49, C58 Keywords econophysics, multifractality, financial markets, Hurst exponent Author's e-mail jana.sedlarikova@gmail.com Supervisor's e-mail kristoufek@ies-prague.org
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The Environmental Kuznets Curve Framework: Europe 2020 Greenhouse Gases Target in the EU-15 states
Korba, Pavel ; Dózsa, Martin (advisor) ; Kraicová, Lucie (referee)
In the thesis, we examine the necessity and impacts of measures adopted under the greenhouse gas emissions target in the Europe 2020 growth strategy in the EU-15 states. For testing the necessity of the measures, we use the Environmental Kuznets Curve (EKC) hypothesis for carbon dioxide (CO2) emissions as the theoretical framework, the Autoregressive distributed lag model as the econometrical technique and annual data from 1970 to 2010 (1991 to 2010 in the case of Germany). The existence of the EKC is detected in Belgium, Denmark, France, Germany, Netherlands, Spain, Sweden, and the United Kingdom. However, only in Denmark the EKC hypothesis is supported significantly (on ten percent level of significance). Following the main implication of the EKC hypothesis, only in Denmark is the economic development sufficient enough to safeguard environmental quality; therefore, no additional measures are needed. In the remaining states, we tested Granger causality using the Toda-Yamamoto procedure to inquire about the impacts of the measures on gross domestic product (GDP). Our results indicate that only in Austria, Germany (with caution due to a limited number of observations) and Ireland, the measures may impede economic development. In the remaining states, no causality or only a causality running from GDP...
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Robust portfolio selection
Horváthová, Inés ; Červinka, Michal (advisor) ; Kraicová, Lucie (referee)
In this thesis, we take the mean-risk approach to portfolio optimi- zation. We will first define risk measures in general and then intro- duce three commonly used ones: variance, Value-at-risk (V aR) and Conditional-value-at-risk (CV aR). For each of these risk measures we formulate the corresponding mean-risk models. We then present their robust counterparts. We focus mainly on the robust mean-variance models, which we also apply to historical data using free statistical software R. Finally, we compare the results with the classical non- robust mean-variance model.
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The Impact of Oil Prices on Macroeconomic Indicators in Azerbaijan and Georgia
Karimov, Farhad ; Horváth, Roman (advisor) ; Kraicová, Lucie (referee)
Using a multivariate vector autoregression (VAR) approach, this paper investigates the relationships between oil price and macroeconomic indicators of closely interrelated developing economies of oil exporting Azerbaijan and oil importing Georgia based on monthly time series from January 2001 to November 2012. The model is estimated for each country separately and the results are object for comparison. The empirical evidence suggests that oil price has significant effects on macroeconomy in both countries. In particular, these effects are positive for all 3 macroeconomic variables on the example of Azerbaijan. On the example of Georgia, these effects are positive for GDP and inflation rate, and, negative for exchange rate. On the other hand, macroeconomic indicators of Azerbaijan fail to affect oil price level.
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Forecasting stock market returns and volatility in different time horizons using Neural Networks
Hronec, Martin ; Baruník, Jozef (advisor) ; Kraicová, Lucie (referee)
This thesis is focused on multiple-step-ahead forecasting of Nasdaq Composite index returns and daily range-based volatility. In order to capture the complex patterns potentially hidden to traditional linear models we use artificial neural networks as nonlinear, nonparametric and robust forecasting tool. We contribute to the ongoing discussion about stock market predictability with following empiri- cal results. In case of Nasdaq Composite returns, all four applied neural networks fail to outperform benchmark model in all time horizons, suggesting high unpre- dictability in accordance with Efficient market hypothesis. Also in case of Nasdaq Composite daily range-based volatility, 1 day and 1 month ahead predictions are not significantly more accurate than benchmark model. However, we find 1-week and 2-weeks-ahead forecasts to be significantly more accurate than benchmark model and able to capture the predictive patterns. Keywords predictability of stock returns, predictability of daily range-based volatility, multiple- step-ahead forecasting, neural networks, RPROP, BFGS learning algorithm
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Capital Flows and Credit Development: Empirical Evidence from the CEE Region
Izák, Jan ; Geršl, Adam (advisor) ; Kraicová, Lucie (referee)
The aim of this bachelor thesis is to investigate the relationship between the structure of international capital flows and credit development in Central and Eastern Europe. Over last twenty years, the CEE region has often been a destination for capital flows from developed countries which have significantly influenced domestic economies. With respect to the rapid growth of credit over the same period, it makes sense to deal with this relationship in more detail. The data are analyzed separately for corporations and households as they experienced different credit development. In the analysis, I apply OLS and PCSE model on the quarterly data in the period 1997-2013. The results of the analysis imply the influence of FDI and OI inflows in both sectors but only negligible impact of PI inflows. However, the importance of FDI inflows have decreased over time. Powered by TCPDF (www.tcpdf.org)
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Inventory Control Problem with Random Demand
Kopecký, Tadeáš ; Červinka, Michal (advisor) ; Kraicová, Lucie (referee)
Teorie skladu je d·ležitou součástí některých druh· podnikání. Slouží k efek- tivnímu snížení náklad· spojených s objednáváním a skladováním zboží. V této práci jsou popisovány algoritmy a modely, které jsou používány k určení optimálního pohybu zboží ve skladu. Také je prezentováno několik rozdíl- ných metod určených k předpovědi poptávky. Tyto algoritmy a metody jsou aplikovány na reálná data. Cílem je ukázat zp·sob, jakým lze dosáhnout op- timálního pohybu zboží ve skladu. Declaration of Authorship I hereby proclaim that I wrote my bachelor thesis on my own under the leadership of my supervisor and that the references include all resources and literature I have used. I grant a permission to reproduce and to distribute copies of this thesis document in whole or in part. Prague, July 22, 2014 Signature Acknowledgment I would like to express my deepest gratitude to my supervisor, RNDr. Michal ervinka, Ph.D. for helpfulness and guiding. I am also very grateful to my mother and her colleague who provided me the data for the case study. Last but not least I deeply thank to my family and friends. Without their support this thesis could have never been written. Bachelor Thesis Proposal In the thesis, the author will describe models suitable for modeling utilization of inventory capacity, material...
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Sampling from finite population in economic problems
Krepl, Jan ; Červinka, Michal (advisor) ; Kraicová, Lucie (referee)
Survey sampling constitutes a basic method of obtaining values of population parameters. Social sciences including economics use survey sampling to collect information which is then used for research purposes. The goal of this thesis is to describe sample surveys in general and to focus on basic probability sampling schemes. For the empirical part, the author selected several suitable theses of IES FSV UK students where sample survey data was used. These theses serve as an illustration of described methods in theoretical part. At the end, the possibility of applications of probability sampling is discussed. Powered by TCPDF (www.tcpdf.org)
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