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Riziko spojené se změnami počasí na trhu se zemním plynem
Vyležík, Tomáš ; Janda, Karel (advisor) ; Gapko, Petr (referee)
This thesis deals with the impact of weather on the natural gas market. We describe the development of the natural gas market in recent past and its current structure. Both these contingencies contributed to growing importance of hedging against weather risk today. Consequently, with help of regression models we assess the dependency of Czech natural gas consumption on temperature, which is unambiguously the primary determinant of demand in the natural gas market. Such an analysis frequently serves as the first indicator of the need for weather risk hedging, which is since the 90's commonly done with weather derivatives. Therefore we go through so called burn analysis that determines the fair price of an option with regard to past temperature measurements.
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Artificial Neural Networks in Option Pricing
Vach, Dominik ; Gapko, Petr (advisor) ; Červinka, Michal (referee)
This thesis examines the application of neural networks in the context of option pricing. Throughout the thesis, different architecture choices and prediction parameters are tested and compared in order to achieve better performance and higher accuracy in option valuation. Two different volatility forecast mechanisms are used to compare neural networks performance with Black Scholes parametric model. Moreover, the performance of a neural network is compared also to more advanced modular neural networks. A new technique of adding rational prediction assumptions to neural network prediction is tested and the thesis shows the importance of adding virtual options fulfilling these assumptions in order to achieve better training of the neural network. This method comes out to increase the prediction power of the network significantly. The thesis also shows the neural network prediction outperforms the traditional parametric methods. The size and number of hidden layers in a neural network is tested with an emphasis to provide a benchmark and a structured way how to choose neural network parameters for future applications in option pricing. JEL Classification C13, C14, G13 Keywords Option pricing, Neural networks, Modular neu- ral networks, S&P500 index options Author's e-mail vach.dominik@gmail.com...
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Sovereign credit risk drivers in a spatial perspective.
Záhlava, Josef ; Gapko, Petr (advisor) ; Janský, Petr (referee)
This thesis analyses what drives sovereign credit risk when contagion is con- trolled for. CDS spreads are used as a measure of credit risk and bond yields are used to estimate interconnectedness of the examined countries. The main contribution lies in the use of high-frequency data and a robust wavelet based estimator in addition to spatial econometric model. The aim of this thesis is to test for presence of contagion and to evaluate which fundamentals are decisive for market perception of sovereign credit risk. Another goal is to evaluate the possibility of a structural break caused by the Greek debt restructuring. The results show that the restructuring did bring change. Contagion is present during the post-crisis period and it diminishes as the economies recover. Sim- ilarly, fundamentals are of higher importance in the post-crisis period when compared with the following period. JEL Classification C22, C31, C33, G01, G32, G33 Keywords spatial econometrics, CDS spreads, sovereign credit risk, financial contagion, realised covari- ance Author's e-mail josef.zahlava@gmail.com Supervisor's e-mail petr.gapko@seznam.cz
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Interconnectedness of capital markets during the financial crisis
Kocholová, Soňa ; Gapko, Petr (advisor) ; Lešanovská, Jitka (referee)
We study the interconnectedness between the United States and thirty three international stock markets during the period of January 2003 to December 2012, with an emphasis on the global financial crisis of autumn 2008. By applying the DCC-GARCH model, our results show evidence of the increase in correlation during the period of crisis. The largest increase was reported for Argentina and India. The average increase was 0.164. Within the sample period, the US stock market was found to be the most correlated with markets of Brazil, Canada, France, Germany, Euro Area and Mexico and the least correlated with markets of China, Malaysia and New Zealand. In the second part of the thesis we study the relationship between the four selected markets (China, Euro Area, Japan and United States) and macroeconomic variables (exchange rate, total trade, industrial production and interest rates). The markets show positive relationship with the exchange rate, trade and the industrial production. The interest rate does not reveal any specific, negative nor positive, relationship. We conclude that more indices respond to a shock in one index in a very similar way. Powered by TCPDF (www.tcpdf.org)
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The Modern Money Creation Process: The Case of Collateral Crunch
Kroulíková, Šárka ; Teplý, Petr (advisor) ; Gapko, Petr (referee)
The aim of this thesis is to investigate the role of the wholesale funding in the modern credit intermediation process and to estimate the possible impact of pro- posed regulation of the wholesale funding on lending activity of a bank or its risk profile. Throughout the analysis we used data set of 132-1167 banks from the European Union (number of banks depends on the hypotheses tested) during the period 2006-2012. We found that the banks that are more exposed to the whole- sale funding are able to increase their lending relatively more in comparison to the less exposed banks; this advantage is wiped out during the times of liquidity or collateral crunch. Results of defined simultaneous equation model suggest that stricter eligibility criteria, higher margins and introduction of 100% threshold for the Net Stable Funding Ratio will significantly decrease the wholesale funding ra- tio and thus limit the supply of loans. We consider those results alarming since the majority of European enterprises is financed by the financial intermediaries, not on the capital market and therefore additional limitation of the wholesale funding activities could negatively influence the overall economic activity within the Euro- pean Union. We discovered that the commercial banks tent to transfer the costs of the wholesale...
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Three Essays on Credit Risk Quantification
Gapko, Petr ; Šmíd, Martin (advisor) ; Witzany, Jiří (referee) ; Tichý, Tomáš (referee) ; D'Ecclesia, Rita Laura (referee)
The dissertation thesis deals with modeling and estimating credit risk. In the thesis we particularly focus on the credit risk of retail, and more exactly mortgage, debtors. The thesis is organized into three separate papers with a common theme, which is a development of a credit risk measurement methodology from simpler enhancements of the current research to a model able to capture such details as e.g. the duration structure of the mortgage portfolio. All three papers use the same underlying dataset, a time series of the national US mortgage portfolio delinquency and foreclosure rates. As the research was done during several years, the latter parts of the thesis work with additional observations. In the first paper, we demonstrate that the current regulatory standards for credit risk quantification are based on assumptions that do not necessarily match the reality. Generalizing the well-known Vasicek's model, standing behind the Basel II, we build a model of a credit risk of a loan portfolio. The model, similarly to the Vasicek's model, decomposes the credit risk (expressed as the portfolio probability of default) into two risk factors, one common for all borrowers in the portfolio, and one individual for each single borrower. Our model involves dynamics of the common factor, which influences the...
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Multivariate Dependence Modeling using Copulas
Klaus, Marek ; Šopov, Boril (advisor) ; Gapko, Petr (referee)
Multivariate volatility models, such as DCC MGARCH, are estimated under assumption of multivariate normal distribution of random variables, while this assumption has been rejected by empirical evidence. Therefore, the esti- mated conditional correlation may not explain the whole dependence struc- ture, since under non-normality the linear correlation is only one of the de- pendency measures. The aim of this thesis is to employ a copula function to the DCC MGARCH model, as copulas are able to link non-normal marginal distributions to create corresponding multivariate joint distribution. The copula-based MGARCH model with uncorrelated dependent errors permits to model conditional cor- relation by DCC-MGARCH and dependence by the copula function, sepa- rately and simultaneously. In other words the model aims to explain addi- tional dependence not captured by traditional DCC MGARCH model due to assumption of normality. In the empirical analysis we apply the model on datasets consisting primarily of stocks of the PX Index and on the pair of S&P500 and NASDAQ100 in order to compare the copula-based MGARCH model to traditional DCC MGARCH in terms of capturing the dependency structure. 1
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Value at Risk: GARCH vs. Stochatistic Volatility Models: Empirical Study
Tesárová, Viktória ; Gapko, Petr (advisor) ; Seidler, Jakub (referee)
The thesis compares GARCH volatility models and Stochastic Volatility (SV) models with Student's t distributed errors and its empirical forecasting per- formance of Value at Risk on five stock price indices: S&P, NASDAQ Com- posite, CAC, DAX and FTSE. It introduces in details the problem of SV models Maximum Likelihood examinations and suggests the newly devel- oped approach of Efficient Importance Sampling (EIS). EIS is a procedure that provides an accurate Monte Carlo evaluation of likelihood function which depends upon high-dimensional numerical integrals. Comparison analysis is divided into in-sample and out-of-sample forecast- ing performance and evaluated using standard statistical probability back- testig methods as conditional and unconditional coverage. Based on empirical analysis thesis shows that SV models can perform at least as good as GARCH models if not superior in forecasting volatility and parametric VaR. 1
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The Determinants of Corporate Credit Lines Accessibility in the Czech Republic
Hanák, Pavel ; Gapko, Petr (advisor) ; Janda, Karel (referee)
This work focuses on the factors influencing the accessibility of credit lines for the companies in the Czech Republic. Its methodology follows the respected works written in the field of credit markets or in the field of econometrical methods suitable for the estimation of such markets. The main econometrical tool of this work is the Maximum Likelihood Estimation. Dependent variable is always the percentage change of the total volume of corporate loans and the independent variables are the percentage changes of different macroeconomic indicators. This work brings key findings important for the understanding the of the Czech corporate credit market. JEL Classification C32, C51, E40, E41, G10, G20, G21 Keywords Corporate Loans, Credit, Credit Lines, Credit Market, Credit Supply, Czech Banking Sector, Demand for Credit, Loans Author's e-mail pavelhanak@seznam.cz Supervisor's e-mail petr.gapko@seznam.cz
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