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Reduced-form Approach to LGD Modeling
Hlavatá, Ivana ; Seidler, Jakub (advisor) ; Šopov, Boril (referee)
The rigorous thesis deals with the advanced methods for estimating credit risk parameters from market prices: probability of default (PD) and loss given default (LGD). Precise evaluation of these parameters is important not only for banks to calculate their regulatory capital but also for investors to price risky bonds and credit derivatives. We develop two forward looking reduced-form analytical methods for calculation of PD and LGD of corporate defaultable bonds based on their quoted market prices, prices of equivalent risk-free bonds and quoted senior and subordinated credit default swap spreads of the issuer of these bonds. This is reversed to most of the studies on credit risk modeling, as aim is not to price instruments based on estimated credit risk parameters, but to calculate these parameters based on the available market quotes. Furthermore, compared to other studies, the LGD parameter is assumed to be endogenous and we provide the method for its simultaneous calculation with the probability of default. Finally, using developed methods, we estimate implied PD and LGD for nine European banks assuming that the risk is priced correctly by other investors and the markets are efficient. JEL Classification: C02, C63, G13, G33 Keywords: credit risk, loss given default, probability of default,...
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Income Elasticity of Money Demand: A Meta-Analysis
Sedlaříková, Jana ; Havránek, Tomáš (advisor) ; Šopov, Boril (referee)
The income elasticity of money demand represents an important economic variable which affects money demand function. Precise evaluation of money demand is important for central banking and for determining the transmission mechanism. Nevertheless, there is no general agreement on the exact structure of the function of money demand and income elasticity values neither in theoretical nor practical context. Many different economic theories concerning this field were developed by various economists during the 20th century. There was also a large amount of empirical research whose goal was to estimate the value of income elasticity based on real economic data. However, these studies are characterized by strong heterogeneity of the respective results. The method of meta-analysis is considered to be an effective statistical instrument that allows systematic evaluation of these inconsistent estimates. This method was applied to the dataset consisting of 985 empirical estimates from more than 70 primary studies. The publication selection bias was detected only in the case of using broad monetary aggregates. The resulting estimates adjusted for publication bias range from 0.784 for narrow monetary aggregates to 0.93 for the broadly defined money. In addition, meta- regression analysis revealed correlation...
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Forecasting realized volatility: Do jumps in prices matter?
Lipták, Štefan ; Baruník, Jozef (advisor) ; Šopov, Boril (referee)
This thesis uses Heterogeneous Autoregressive models of Realized Volatility on five-minute data of three of the most liquid financial assets - S&P 500 Futures index, Euro FX and Light Crude NYMEX. The main contribution lies in the length of the datasets which span the time period of 25 years (13 years in case of Euro FX). Our aim is to show that decomposing realized variance into continuous and jump components improves the predicatability of RV also on extremely long high frequency datasets. The main goal is to investigate the dynamics of the HAR model parameters in time. Also, we examine if volatilities of various assets behave differently. The results reveal that decomposing RV into its components indeed im- proves the modeling and forecasting of volatility on all datasets. However, we found that forecasts are best when based on short, 1-2 years, pre-forecast periods due to high dynamics of HAR model's parameters in time. This dynamics is revealed also by a year-by-year estimation on all datasets. Con- sequently, we consider HAR models to be inapproppriate for modeling RV on such long datasets as they are not able to capture the dynamics of RV. This was indicated on all three datasets, thus, we conclude that volatility behaves similarly for different types of assets with similar liquidity. 1
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Analysis of stock market anomalies: US cross-sectoral comparison
Jílek, Lukáš ; Krištoufek, Ladislav (advisor) ; Šopov, Boril (referee)
The purpose of this thesis is to analyze anomalies in the US stock market. Special attention is put on Day of the week effect, January effect, and Part of the month effect. We focus on comparison of companies with low and high capitalization. We perform an analysis across 6 major industrial sectors. Then, we discuss the findings with results of past projects and finally, we try to find a speculative investment strategy. We found out that neither Day of the week effect nor January effect do not appear in US stock market nowadays. Part of the month effect was the only anomaly, which was observed in our data. Keywords Stock market anomalies, financial markets, cross-sectoral analysis, Jannuary effect, Day of the week effect, Part of the month effect Author's e-mail jileklukas@gmail.com Supervisor's e-mail kristoufek@gmail.com
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Analysis of gasoline and diesel prices in the Czech Republic
Badáňová, Martina ; Krištoufek, Ladislav (advisor) ; Šopov, Boril (referee)
This thesis investigates relationship between fuel (gasoline and diesel) prices in the Czech Republic and world crude oil prices over the period from 2004 to 2011. Using daily data we estimate an asymmetric error correction model and we find that in the short-run fuel prices are adjusted upwards to the long-run equilibrium faster than they are adjusted downwards to the equilibrium. However, the difference in responses is found to be not statistically significant.
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Financial Risk Measures: Review and Empirical Applications
Říha, Jan ; Šopov, Boril (advisor) ; Krištoufek, Ladislav (referee)
This thesis focuses on several classes of risk measures, related axioms and properties. We have introduced and compared monetary, coherent, convex and deviation classes of risk measures and subsequently their properties have been discussed and in selected cases demonstrated on data. Furthermore the relatively promising and advanced class of risk measures, the spectral risk measures, has been introduced. In addition to that we have outlined selected topics from portfolio theory that are relevant for applications of selected risk measures and then derived theoretical solution of portfolio selection using chosen risk measures. In the end we have highlighted the potential consequences of improper employment of certain risk measures in portfolio optimization.
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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 have been rejected by empirical evidence. Therefore, the estimated conditional correlation may not explain the whole dependence structure, since under non-normality the linear correlation is only one of the dependency 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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Yield Curve Modeling and the Effect of Macroeconomic Drivers: Dynamic Nelson-Siegel Approach
Patáková, Magdalena ; Šopov, Boril (advisor) ; Vošvrda, Miloslav (referee)
The thesis focuses on the yield curve modeling using the dynamic Nelson-Siegel approach. We propose two models of the yield curve and apply them on four currency areas - USD, EUR, GBP and CZK. At first, we distill the entire yield curve into the time-varying level, slope and curvature factors and estimate the parameters for individual currencies. Subsequently, we build a novel model investigating to what extent unobservable factors of the dynamic Nelson-Siegel model are determined by macroeconomic drivers. The main contribution of this thesis resides in the innovative approach to yield curve modeling with the application of advanced technical tools. Our primary objective was to increase the accuracy and the estimation power of the model. Moreover, we applied both models across different currency areas, which enabled us to compare the dynamics of the yield curves as well as the influence of the macroeconomic drivers. Interestingly, the results proved that both models we developed not only demonstrate strong validity, but also produce powerful estimates across all examined currencies. In addition, the incorporated macroeconomic factors contributed to reach higher precision of the modeling. JEL Classification: C51, C53, G17 Keywords: Nelson-Siegel, Kalman filter, Kalman smoother, Stace space formulation...
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Alternative field curve modelling approach : regional models
Šopov, Boril ; Seidler, Jakub (advisor) ; Baruník, Jozef (referee)
In this thesis, we focus on thorough yield curve modelling. We build on extended classical Nelson-Siegel model, which we further develop to accommodate unobserved regional common factors and principal components. We centre our discussion on central European currencies' yield curves: CZK, HUF, PLN and SKK. We propose two novel models to capture regional dynamics; one based purely on state space formulation and the other relying also on principal components of the regional yield curves. Moreover, we supplement the models with two application examples in risk management and structural break detection. The main contribution of this thesis is a creation of a complete framework that enables us to analyse yield curves, to design risk scenarios and to detect structural breaks of various types.
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Alternative yield curve modelling approach : regional models
Šopov, Boril ; Seidler, Jakub (advisor) ; Baruník, Jozef (referee)
In this thesis, we focus on thorough yield curve modelling. We build on extended classical Nelson-Siegel model, which we further develop to accommodate unobserved regional common factors and principal components. We centre our discussion on central European currencies' yield curves: CZK, HUF, PLN and SKK. We propose two novel models to capture regional dynamics; one based purely on state space formulation and the other relying also on principal components of the regional yield curves. Moreover, we supplement the models with two application examples in risk management and structural break detection. The main contribution of this thesis is a creation of a complete framework that enables us to analyse yield curves, to design risk scenarios and to detect structural breaks of various types.
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