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Extending volatility models with market sentiment indicators
Röhryová, Lenka ; Krištoufek, Ladislav (advisor) ; Jakubík, Petr (referee)
In this thesis, we aim to improve forecast accuracy of a heterogenous au- toregressive model (HAR) by including market sentiment indicators based on Google search volume and Twitter sentiment. We have analysed 30 com- panies of the Dow Jones index for a period of 15 months. We have performed out-of-sample forecast and compiled a ranking of the extended models based on their relative performance. We have identified three relevant variables: daily negative tweets, daily Google search volume and weekly Google search volume. These variables improve forecast accuracy of the HAR model se- parately or in a Twitter-Google combination. Some specifications improve forecast accuracy by up to 22% for particular stocks, others impair forecast accuracy by up to 24%. The combination of daily negative tweets and weekly search volume is a superior model to the basic HAR for 17 stocks according to RMSE and for 16 stocks according to MAE and MASE. The daily nega- tive tweets specification outperforms the basic HAR for 17 and 19 stocks, respectively. And, the combination of daily negative tweets and daily search volume outpaces the basic HAR for 15 and 18 stocks, respectively. Based on the average MASE improvement, the combination of daily negative tweets and weekly search volume is a clear winner as it lowers the...
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Do mutual funds offered in Czech Republic add value to investors?
Nosek, Jiří ; Hronec, Martin (advisor) ; Jakubík, Petr (referee)
We estimate the proportions of skilled, unskilled, and zero-alpha funds preva- lent in the mutual Funds population easily accessible by Czech Investors. We estimate alphas from a regression against a concise set of Exchange Traded Funds and control for luck using False Discovery rate. We design a straight- forward ETF selection algorithm and find that if investors adhere to simple diversification rules, they can outperform a large proportion of mutual funds. We further document a negative relationship between the performance of mu- tual funds and its Total Expense ratio, suggesting that portfolio managers are on average unable to compensate their costs with better performance. JEL Classification C12, C20, G12, G23 Keywords Mutual Funds, Exchange Traded Funds, Perfor- mance evaluation Title Do mutual funds offered in Czech Republic add value to investors?
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Pricing Methods and Value of the Firm
Moleková, Táňa ; Jakubík, Petr (advisor) ; Hájek, Filip (referee)
One of the main features of currently running financial and economic crisis is the substantial drop of the value of assets held in form of stocks. The key issues for investors nowadays is, whether to hold the stocks in the expectations of consequent regain of their value, or whether to look for safer and more profitable targets for allocation of capital. This is the question that is being asked also by the hundreds of professional as well as small investors and households, which are keeping their money in form of stocks of companies tradable at Prague Stock Exchange. Having in hand the information about the potential over- or undervaluation of the market price of these stock in relation to their intrinsic valuesbased on true financial fundamentals can help them make the right decision. Finding the answers on these questions was set as a main goal of this diploma thesis. The analysis, which of the theoretical concepts and stock valuation methods are the most successful in explaining the development of the actual stock prices for the companies listed in Prague Stock Exchange comes to the forefront. Different valuation models and econometric tools are tested on several companies in order to estimate the potential relationship between the actual and intrinsic value of these stocks as well as to exhibit...
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Is It Possible to Generate Profit Using Common Investment Strategies? The Case of Prague Stock Exchange
Charamza, Petr ; Jakubík, Petr (advisor) ; Baxa, Jaromír (referee)
In this thesis we compared a profitability of several investment strategies that could be used at the stock markets and we adjusted them for the need of Prague Stock Exchange. The strategies that we used are based on some different principles and they provide different results. We found that the strategies based on the technical approach gave us better results than the strategies based on the fundamental approach. The next finding is that those strategies for which the investors would go also into the short sell perform better than the strategies for which the investors would take just the long positions. The best results we got for the momentum strategy, which is based on the autocorrelation of returns.
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Credit Risk Models and Their Relationship with Economic Cycle
Jakubík, Petr ; Teplý, Petr (advisor) ; Mejstřík, Michal (referee)
The significance of credit risk models has increased with the introduction of new Basel accord known as Basel II. The aim of this study is default rate modeling. This thesis follows the two possible approaches of a macro credit risk modeling. First, empirical models are investigated. Second, a latent factor model based on Merton's idea is introduced. Both of these models are derived from individual default probability models. We employed data over the time period from 1988 to 2003 of the Finnish economy in the first part of this thesis. Time series of bankruptcy and firm's numbers were used. Aggregate data for whole economy as well as industry specific data were available. First, linear vector autoregressive models was used in case of dynamic empirical model. We examined how significant macroeconomic indicators determined the default rate in the whole economy and in the industry specific sector. However these models cannot provide microeconomic foundation as latent factor models. We employed a one- factor model in our estimation although, multi-factor models were also considered. A one-factor model was estimated using disaggregated industrial data. This estimation can help understand relation between credit risk and macroeconomic indicators. Obtained results were used in the second part of this...
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Macroeconomic Determinants of Probability of Default and Loss Gived Default for Households
Dvořák, Pavel ; Jakubík, Petr (advisor) ; Kopecsni, Juraj (referee)
This thesis is focused on the estimation of expected loss for the consumer credit card portfolio. For the expected loss modelling we have developed in this thesis a model that satisfies conditions defined by New Basel accord (Basel II). The final model is therefore compound of the key credit risk components as they are identified by Basel II document and s separate model is built for each of them. These credit risk components are probability of default (PD), exposure at default (EAD) and loss given default (LGD). For the model development were used credit scoring techniques, especially classification tree method represented by CHAID algorithm. The empirical model then gives us an opportunity to test several hypotheses regarding the influence of macroeconomic indicators and demographics on expected loss, or correlation between PD and LGD.
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New Collective Investment Possibilities in the Czech Republic
Vostrovská, Diana ; Pečená, Magda (advisor) ; Jakubík, Petr (referee)
Collective investment in the Czech Republic has gone through significant development during past decades and currently plays an important role on financial markets. The amendment of the Act on Collective Investment enabled the creation of property funds, which can be set up as special funds of qualified investor funds. The study starts with the general overview of the Czech collective investment market its structure, history and present. Furthermore, legal norms which determine the conception of property funds are specified. The study draws from the experience of foreign states and mostly focuses on Germany and USA. Property funds already have their own history there. Last but not least, the main aspects of property funds business are analyzed in context of international competitive advantages by analyzing the characteristics of indirect real-estate investments, tax system, development of the local realestate market and European legislation.
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The impact of the COVID-19 crisis on bank credit risk management
Lukášková, Karolína ; Teplý, Petr (advisor) ; Jakubík, Petr (referee)
iv Abstract This diploma thesis examines the impact of the COVID-19 crisis on the bank credit risk in the European Union. The analysis is performed using two sets of panel data. The first set contains data at the bank-level between 2012 and 2018 and is obtained from BankFocus batabase and the second set of data is obtained from the EBA Risk dashboard and contains data at the country-level between 2014 and 2020. Both datasets contain bank-specific variables and macroeconomic variables. We use the variables Cost of risk, Total capital ratio, Tier 1 ratio and NPE ratio as dependent variables. As representatives of the COVID-19 shock, we use the number of people infected with this disease, the number of deaths from this disease and the Stringency Index. We employ the GMM system for our analysis and test 5 hypotheses. We did not reject 3 hypotheses, namely that Cost of risk is a key determinant of credit risk and that the crisis caused by COVID-19 affects the variables Capitalo ratio and NPE ratio. We further concluded that the variables representing COVID-19 do not have a negative effect on credit risk, mainly due to the interventions of the ECB and the IASB. JEL Classification C12, C33, G01, G21 Keywords bank, COVID-19 crisis, credit risk management, Stringency index Title Author's e-mail Supervisor's e-mail...
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Mechanism of Negative Interest Rate's Influence on Bank Net Interest Margin
Fan, Yingxuan ; Holub, Tomáš (advisor) ; Jakubík, Petr (referee)
Net interest margin (NIM) is an important indicator of a bank's operational efficiency. Based on the balance sheet data of 189 major listed banks in Europe from 2010 to 2019, this thesis studies the bank's NIM mechanism in a negative interest rate environment. This thesis focuses on the system GMM method and the results show that the policy interest rate is positively related to NIM in the long run and negatively related in the short run, but the relationship between the two is not significant in the short run. Moreover, in a negative interest rate environment, bank NIM's sensitivity to policy interest rates has greatly increased, especially the policy of interest rate cuts. In addition, the sensitivity of NIMs of different banks to policy interest rates also differs significantly. Generally, the NIMs of banks with a high degree of internationalization and larger size are less sensitive to changes in policy interest rates, while the NIMs of banks with a higher share of retail business in their total business are more sensitive to changes in policy interest rates. Finally, through the value-at-risk analysis and stress test, this thesis concludes that the policy interest rate, net loan-to-asset ratio, non-performing loan ratio and inflation rate are sensitive factors of NIM. When NIM is subject to a...
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Measuring Bank Efficiency
Iršová, Zuzana ; Jakubík, Petr (advisor) ; Michalíková, Eva (referee)
This thesis provides an empirical insight on the frontier efficiency estimation methods in banking and their sensitivity toward the change in definition of particular characteristics in the techniques used. The two methods, stochastic frontier approach (SFA) and deterministic data envelopment analysis (DEA) are compared over several variations, results of which are supported by the meta-regression part including 32 studies on the USA and 14 on the transitional countries. The main findings of this study include: the efficiency score is highly dependent on the methodological design, the largest variation in the estimated scores of SFA and DEA are due to Fourier-flexible functional form application, and the rank order correlation between these methods raises with an increase of the homogeneity degree in the sample. JEL Classification C13, C61, G21, L25, P27 Keywords Bank Efficiency, Stochastic Frontier Approach, Data Envelopment Analysis, Meta-Regression Analysis Author's e-mail zuzana.irsova@gmail.com Supervisor's e-mail petr.jakubik@cnb.cz
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