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Google Econometrics: An Application to the Czech Republic
Platil, Lukáš ; Horváth, Roman (advisor) ; Červinka, Michal (referee)
This thesis examines the applicability of Google Econometrics - the use of search volume data of particular queries as explanatory variables in time se- ries modeling - in the case of the Czech Republic. We analyze the contribu- tion of Google data by comparing out-of-sample nowcasting performance and in-sample fit with control variables in three related areas: using an auto- regressive model for unemployment, vector autoregression and logit models for GDP and household consumption, and Granger causality test for consum- er confidence. The improvement in quality of unemployment nowcasting is modest but statistically significant; sentiment index based on Google queries shows reciprocal relationship with the official Consumer Confidence Indicator, and it also provides superior nowcasts for household consumption as well as in- sample fit in logit models; its performance in GDP nowcasting is average among control variables. These conclusions proved stable also on an extended dataset. In overall, the results suggest that Google Econometrics is applicable also to the Czech Republic, despite the fact that the internet penetration rate and Google popularity was lower over the analyzed period compared with developed economies where these methods were usually tested. In the future, Google data may be used...
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The role of bank management in the European banks' stability during the global financial crisis 2007-2008
Melnychuk, Olena ; Brushko, Iuliia (advisor) ; Červinka, Michal (referee)
During the crisis of 2007-2008, many banks had to improve their management because their previous models could not cope with the increase in the number of defaults on mortgage loans and new risks produced by credit derivatives. The goal of this study is to define what factors were the most significant determinants of the stability of large banks of Europe during the crisis of 2007-2008. This study concentrates mostly on the indicators of the management of loan portfolio in major banks of Europe. For this purpose, the thesis uses a balanced panel data of 69 banks in 18 largest European countries during 2006-2009. Furthermore, from the results of tests on the significance of used variables, the model that evaluates the distance from the insolvency for banks is constructed.
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Volatility Spillovers in New Member States: A Bayesian Model
Janhuba, Radek ; Horváth, Roman (advisor) ; Červinka, Michal (referee)
Volatility spillovers in stock markets have become an important phenomenon, especially in times of crises. Mechanisms of shock transmission from one mar- ket to another are important for the international portfolio diversification. Our thesis examines impulse responses and variance decomposition of main stock in- dices in emerging Central European markets (Czech Republic, Poland, Slovakia and Hungary) in the period of January 2007 to August 2009. Two models are used: A vector autoregression (VAR) model with constant variance of resid- uals and a time varying parameter vector autoregression (TVP-VAR) model with a stochastic volatility. Opposingly of other comparable studies, Bayesian methods are used in both models. Our results confirm the presence of volatility spillovers among all markets. Interestingly, we find significant opposite trans- mission of shocks from Czech Republic to Poland and Hungary, suggesting that investors see the Central European exchanges as separate markets. Bibliographic Record Janhuba, R. (2012): Volatility Spillovers in New Member States: A Bayesian Model. Master thesis, Charles University in Prague, Faculty of Social Sciences, Institute of Economic Studies. Supervisor: doc. Roman Horváth Ph.D. JEL Classification C11, C32, C58, G01, G11, G14 Keywords Volatility spillovers,...
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Optimal Investment Portfolio with Respect to the Term Structure of the Risk-Return Tradeoff
Urban, Matěj ; Rippel, Milan (advisor) ; Červinka, Michal (referee)
My thesis will focus on optimal investment decisions, especially those that are planned for longer investment horizon. I will review the literature, showing that changes in investment opportunities can alter the risk-return tradeoff over time and that asset return predictability has an important effect on the variance and correlation structure of returns on bonds, stocks and T bills across investment horizons. The main attention will be given to pension funds, which are institutional investors with relatively long investment horizon. I will find the term structure of risk-return tradeoff in the empirical part of this paper. Later on I will add some variables into the model and investigate whether it can improve the results. Finally the optimal investment strategies will be constructed for various levels of risk tolerance and the results will be compared with strategies of Czech pension funds. I am going to use data from Thomson Reuters Datastream, Wharton Research Data Services and additionally from some other sources.
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Pricing Options Using Monte Carlo Simulation
Dutton, Ryan ; Dědek, Oldřich (advisor) ; Červinka, Michal (referee)
Monte Carlo simulation is a valuable tool in computational finance. It is widely used to evaluate portfolio management rules, to price derivatives, to simulate hedging strategies, and to estimate Value at Risk. The purpose of this thesis is to develop the mathematical foundation and an algorithmic structure to carry out Monte Carlo simulation to price a European call option, investigate Black-Scholes model to look into the parallel between Monte Carlo simulation and Black-Scholes model, provide a solution for Black-Scholes model using Lognormal distribution of a stock price rather than solving Black-Scholes original partial differential equation, and finally compare the results of Monte Carlo simulation with Black- Scholes closed-form formula. Author's contribution can be best described as developing the mathematical foundation and the algorithm for Monte Carlo simulation, comparing the simulation results with the Black-Scholes model, and investigating how path-dependent options can be implemented using simulation when closed-form formulas may not be available. JEL Classification C02, C6, G12, G17 Keywords Monte Carlo simulation, Option pricing, Black-Scholes model Author's e-mail ryandutton4@gmail.com Supervisor's e-mail oldrich.dedek@fsv.cuni.cz
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News Feed Classifications to Improve Volatility Predictions
Pogodina, Ksenia ; Šopov, Boril (advisor) ; Červinka, Michal (referee)
This thesis analyzes various text classification techniques in order to assess whether the knowledge of published news articles about selected companies can improve its' stock return volatility modelling and forecasting. We examine the content of the textual news releases and derive the news sentiment (po larity and strength) employing three different approaches: supervised machine learning Naive Bayes algorithm, lexicon-based as a representative of linguistic approach and hybrid Naive Bayes. In hybrid Naive Bayes we consider only the words contained in the specific lexicon rather than whole set of words from the article. For the lexicon-based approach we used independently two lexicons one with binary another with multiclass labels. The training set for the Naive Bayes was labeled by the author. When comparing the classifiers from the machine learning approach we can conclude that all of them performed similarly with a slight advantage of the hybrid Naive Bayes combined with multiclass lexicon. The resulting quantitative data in form of sentiment scores will be then incorpo rated into GARCH volatility modelling. The findings suggest that information contained in news feeds does bring an additional explanatory power to tradi tional GARCH model and is able to improve it's forecast. On the...
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Income Elasticity of Water Demand: A Meta-Analysis
Vlach, Tomáš ; Havránek, Tomáš (advisor) ; Červinka, Michal (referee)
If policymakers address water scarcity with the demand-oriented approach, the income elasticity of water demand is of pivotal importance. Its estimates, however, differ considerably. We collect 307 estimates of the income elasticity of water demand reported in 62 studies, codify 31 variables describing the estimation design, and employ Bayesian model averaging to address model uncertainty inherent to any meta-analysis. The studies were published between 1972 and 2015, which means that this meta-analysis covers a longer period of time than two previous meta-analyses on this topic combined. Our results suggest that income elasticity estimates for developed countries do not significantly differ from income elasticity estimates for developing countries and that different estimation techniques do not systematically produce different values of the income elasticity of water demand. We find evidence of publication selection bias in the literature on the income elasticity of water demand with the use of both graphical and regression analysis. We correct the estimates for publication selection bias and estimate the true effect beyond bias, which reaches approximately 0.2. 1
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Flow-shop Problems
Dyntar, Tomáš ; Tegze, Miron (advisor) ; Červinka, Michal (referee)
A description of flow shop and lot streaming including an example is given. Methods and algorithms ofr solving various modifications of the single job two-machine flow shop transfer lot sizing problem are shown. It starts with the calsulation of two lots (discrete), three lots (continuous) problem and then Trietsch s polynomial algorithm or an arbitrary number of sublots is introduced. This alogithm is then used for solving modifications with finding the proper number of sublots for given makespan, with constant or linear transfer times including variants with limited number of transfer machines or their limited capacity, with constant or linear set up times. A domed with both transfer and setup times is then developed and Trietschs algorithm modified. A theoreme by R. G. Vickson for solving multiple job lot streaming problem by treating the lot streaming problem for each job separately and then using Johnsons alogorithm is proposed to extend the results of the single job cases to those of multiple jobs. A known way to extend results to the three machine problem by treating each pair of successive machines separately or developing Trietschs algorithm for three machines is shown. Most of the procedures are illustrated in examples.
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