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Econometric analysis of the economy in game World of Warcraft
Buchníčková, Michaela ; Kuchina, Elena (advisor) ; Formánek, Tomáš (referee)
This thesis analyses the impact of real exchange rate and the official exchange ratio of fiat currencies and in-game golds on the price level in the game World of Warcraft. The work also includes a brief summary of the mechanisms of the in-game economy. The analysis is based on cointegration test and Granger causality test. Individual estimations are model based on the VAR and VEC models theory. The conclusions of this study are made for specific randomly selected pairs of servers with different populations. These results are not easily generalized for the entire regions, but they offer insight into the possible factors affecting the price level in each virtual economy. The results show that the price level on the American server Aegwynn affects the exchange rates of fiat and game currencies as well as that game currency exchange rate in the European region is sensitive to changes in exchange rates of the euro and the yuan. All calculations in this work were implemented in Eviews 8 software.
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An analysis of individual efforts of NHL players
Houdek, Jakub ; Černý, Michal (advisor) ; Formánek, Tomáš (referee)
The thesis is focused on application of econometric methods in the area of sport statistics, specifically in the area of ice hockey. Datasets were extracted from the National Hockey League (NHL) website, from the RTSS (Real Time Scoring System) from seasons 2002/2003 to 2014/15 by using the R package nhlscrapr. The Analysis of these datasets is based on previous work by Brian Macdonald [1]. The result is an adjusted +/- statistics (plus - minus), which describes the individual performance of each player. These statistics were later used for an estimation of probability of advance of selected teams to the playoffs, assuming the selected team uses anticipated players. These estimations were obtained by usage of logistic regression. It was found out, that the predictive ability of these models is weak.
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Analysis of migration in the Czech Republic on the district level
Houšková, Helena ; Formánek, Tomáš (advisor) ; Dlouhá, Zuzana (referee)
This bachelor thesis focuses on internal migration in the Czech Republic on the district level. The aim of the thesis is to explain the relative number of immigrants to particular districts, relative number of emigrants from districts and mainly their difference - growth in the year 2013 with the help of different factors, such as criminality, unemployment, area, and so on. The factors are named and their influence on the relative number of immigrants, emigrants and growth is predicted. Then these data are analysed and three different models are constructed to explain the growth of population. In the first model all districts are taken into account. In the second model three districts of Prague are removed and in the last one, in addition to Prague, central districts of Brno and Ostrava are also removed. After comparing the three models we find out that models are quite similar and not all factors influence the growth of population as we expected.
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The Estimation of Probability of Default Using Logistic Regression
Chalupa, Tomáš ; Dlouhá, Zuzana (advisor) ; Formánek, Tomáš (referee)
The aim of this work is to develop a suitable model that estimates a probability of default of client's loan. As estimation method was used a logistic regression and a probit regression and two definitions of default, 60 and 90 days overdue. The work describes the method of construction, estimation and testing of scoring models and a structure of dataset, which was used in the practical part. Firstly, it was created a theoretical model that was later confronted with estimates. Estimated models were compared by described statistics as McFadden R^2, the ability to diversify was investigated by the Lorenz curve and by the Gini coefficient. It was found that the logistic and the probit regressions have almost the same results, and that 90 days is preferable definition of default than 60 days.
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Měření finanční nákazy pomocí CAViaR metody: Aplikace na Evropu
Tomanová, Petra ; Zouhar, Jan (advisor) ; Formánek, Tomáš (referee)
The aim of this thesis is to measure changes in dependencies among returns on equity indices for European countries in tranquil periods against crisis periods and to investigate their asymmetries in the lower and upper tail of their distributions. The approach is based on a conditional probability that a random variable is lower than a given quantile while other random variables are also lower than their corresponding quantiles. Time-varying conditional quantiles are modeled by the Conditional Autoregressive Value at Risk via Regression Quantiles (CAViaR) method. In addition to the univariate conditional autoregressive models, the vector autoregressive extension is considered. In the second step, the conditional probability is estimated through the OLS regression. Moreover, the model which allows the distribution of returns in one country to lead or to lag the distribution of returns in another country, is defined and applied on European equity returns. Finally, the model measuring dependencies among more than two return series is derived and the relating dimensionality problems are discussed. The results document a significant increase in European equity return comovements in bear markets during the crisis in 1990s and 2000s. The explicit controlling for the high volatility days does not appear to have an impact on the main findings. For the comparison purposes, the results for Latin American countries are reported as well.
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The Impact of Migration on Economic Growth
Jančíková, Denisa ; Cahlík, Tomáš (advisor) ; Formánek, Tomáš (referee)
Human migration, the movement of people from one place to another with intention of settling there temporarily or permanently, is an integral part of development of human society. The beginning of the Industrial Revolution in late 18th century has resulted in economic growth and improvement of living standards. Countries, in which was industrialisation most intense attracted most immigrants. Second wave of migration was in second half of 20th century caused by development of communication technologies, which gave opportunities to less developed countries improve their economic development. This diploma thesis is aimed exactly on this period. Its goal is to research the impact of migration on economic growth and find out if the flow of migrants is beneficial for the economy or the exact opposite. The impact is examined by regression analysis on panel data for almost 200 hundred countries from whole world for time period 1955-2004.
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Application of the Time Series Analysis for Prediction
Nováčková, Monika ; Hušek, Roman (advisor) ; Formánek, Tomáš (referee)
This thesis attempts to predict daily number of firefighter incidents in the Central Bohemia Region and in the Region of Hradec Králové to improve firefighter shift planning. The analysis is based on a dataset of firefighter incidents from the period between the years 2008 and 2012. Econometric models, capturing yearly and weekly patterns and weather impact were estimated and used for long-term prediction. The first part of the thesis provides a description of tests applied to residuals and other econometric tests used in this study. Then linear regression is applied to model weather impact and effects of days of week and months of year. In the next part regression with AR errors, (S)ARMA models and regression with (S)ARMA errors are estimated. All these models are compared according to properties of residuals and out-of-sample mean absolute percentage error (MAPE). The most accurate models predict daily number of incidents two months ahead with MAPE slightly above 20% which is considerably better than the benchmark Holt-Winters method. Regression models with (S)ARMA errors produce relatively accurate long-term forecasts and its error terms are uncorrelated. Therefore, they can be considered suitable for long-term prediction of firefighter incidents.
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Econometric analysis of oil price
Novotný, Lukáš ; Formánek, Tomáš (advisor) ; Čížek, Ondřej (referee)
This bachelor thesis is focused on econometric analysis of oil price WTI. The purpose of the work is to find what factors have influence on the oil price. These factors are tested by econometric methods and after choosing the selected variables I tried to build up some models which describe the oil price WTI movements. In building up the models I am using econometric approaches to correct the models. The bachelor thesis is divided into 3 main chapters -- two of them are theoretical and the last chapter is practical. In the theoretic parts there is a summary of oil facts, extraction, processing of oil, oil market and there is a description of selected econometric methods. In practical part there are my own models and comments on the results. The resulting models show weaker effect of traditionally expected factors like supply and demand for oil and on the other hand greater influence of other factors like global financial crisis or oil stocks. The bachelor thesis leads to proving some thesis from the used literature. It also shows the complexity of creating oil price.
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Econometric Estimation of Loss Given Default
Jacina, Viktor ; Dlouhá, Zuzana (advisor) ; Formánek, Tomáš (referee)
One of the most mentioned credit risk parameters in banking sector is loss given default (LGD). The regulatory framework allows to use own LGD estimation procedures after approval. The classification and regression trees are appropriate and flexible in this context and they offer some advantages comparing to the traditional approaches such as linear regression model. This work includes a theoretical background on tree based methods. In the last section, loss given default from debit accounts is estimated using the random forests which show the best performance in this case.
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The empirical analysis of the project: Stáže ve firmách
Švarc, Michal ; Formánek, Tomáš (advisor) ; Čížek, Ondřej (referee)
This paper is dedicated to the empirical analysis of the pilot trainee project Stáže ve firmách, which is considered as treatment in this analysis. The main objective of the empirical analysis is estimation of average treatment effect(ATE) and average treatment effect on treated(ATET) for characteristics like socioeconomic status and wage. Counterfactual methods for policy impact evaluation like Difference in Differences Estimator(DiD), First Differences Estimator(FD) and Propensity Score Matching(PSM) are used to estimation mentioned effects. This paper contains extension of Assignment Problem that is used for people matching purposes as alternative for PSM. This way of matching provides better control over creation of couples. Resulting pairs are more similar in selected characteristics due to better control during couples creation process.
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