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Predictive accuracy of competing Value-at Risk specifications during crisis : an application to CEE financial markets
Kroutil, Tomáš ; Baruník, Jozef (advisor) ; Seidler, Jakub (referee)
The recent worldwide Financial Crisis has increased the need for reliable financial risk measurement and management. In this thesis we evaluate and compare the accuracy of one-day-ahead out-of-sample forecasts of various Value-at-Risk models through a comprehensive assessment framework using crisis data of three CEE stock market indices (PX, WIG20 and BUX) and two benchmark stock indices (S&P 500, DAX). For building the VaR specifications we employ several GARCH extensions allowing either for asymmetry in volatility such as EGARCH, TGARCH and APARCH or long memory like FIGARCH and HYGARCH. Apart from conditional heteroscedasticity models, we also utilize realized volatility estimated by long memory ARFIMA and HAR. Individual volatility models are combined with full parametric approach, filtered historical simulation or filtered extreme value theory. This thesis shows that while VaR specifications based on logarithmic realized volatility, TGARCH and APARCH perform best overall, the benchmark - RiskMetrics model - is not significantly outperformed. The best performing model proves to be the TGARCH-t FHS, which is a combination of asymmetric and heavy-tailed GARCH filter with a historical simulation based approach.
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Value at Risk Calculation of the Czech Stock Portfolio Using Alternative Distributions
Hédl, Tomáš ; Gapko, Petr (advisor) ; Seidler, Jakub (referee)
The aim of this diploma thesis is to analyze ways of Value at Risk calculation. Its core is to get a suitable model that could most appropriately reflect the probability distribution of returns of the Czech stock portfolio that we have generated. In this thesis we find out that the returns follow unbounded distribution which was first described by Johnson (1949). Since we detect that returns are correlated we have to apply appropriate autoregressive process that removes this dependency. In the empirical part we discover an inability of models based on assumptions of normality, to correctly predict the Value at Risk. Historical simulation methods, which have promising backtesting results, are rejected because of the slow adaptation to the recent changes in the market. However, we find a way how to implement Johnson SU distribution into the GARCH model. This model, which passes all the tests, is thus able to predict Value at Risks of the portfolio most accurately. JEL Classification: C16, C22, G11 Keywords: Market risk, Value at Risk, Risk management, Johnson SU distribution
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Value-at-risk forecasting with the ARMA-GARCH family of models during the recent financial crisis
Jánský, Ivo ; Rippel, Milan (advisor) ; Seidler, Jakub (referee)
The thesis evaluates several hundred one-day-ahead VaR forecasting models in the time period between the years 2004 and 2009 on data from six world stock indices - DJI, GSPC, IXIC, FTSE, GDAXI and N225. The models model mean using the AR and MA processes with up to two lags and variance with one of GARCH, EGARCH or TARCH processes with up to two lags. The models are estimated on the data from the in-sample period and their forecasting ac- curacy is evaluated on the out-of-sample data, which are more volatile. The main aim of the thesis is to test whether a model estimated on data with lower volatility can be used in periods with higher volatility. The evaluation is based on the conditional coverage test and is performed on each stock index sepa- rately. Unlike other works in this eld of study, the thesis does not assume the log-returns to be normally distributed and does not explicitly select a partic- ular conditional volatility process. Moreover, the thesis takes advantage of a less known conditional coverage framework for the measurement of forecasting accuracy.
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Implied market loss given default
Seidler, Jakub ; Jakubík, Petr (advisor) ; Dědek, Oldřich (referee)
This thesis focuses on the key credit risk parameter - Loss Given Default (LGD). We describe its general properties and determinants with respect to seniority of debt, characteristics of debtors or macroeconomic conditions, and discuss its role in Basel II framework. Further, we illustrate how the LGD can be extracted from market observable information with help of both the structural and reduced- form models. Finally, by using the adjusted Mertonian approach, we estimate the 5-year expected LGDs for companies listed on Prague Stock Exchange and find out, that the average LGD for this analyzed sample is around 20%. To the author's best knowledge, those are the first implied market estimates of LGD in the Czech Republic. Powered by TCPDF (www.tcpdf.org)
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Value-at-risk based extreme value theory method and copulas : empirical evidence from Central Europe
Avdulaj, Krenar ; Seidler, Jakub (referee) ; Baruník, Jozef (advisor)
Assessing the extreme events is crucial in financial risk management. All risk managers and and financial institutions want to know the risk of their portfolio under rare events scenarios. We illustrate a multivariate Monte Carlo and semi-parametric method to estimate Value-at-Risk (VaR) for a portfolio of stock exchange indexes in Central Europe. It is a method that uses the non-parametric empirical distribution to capture the small risks and the parametric Extreme Value theory to capture large risks. We compare this method with historical simulation and variance-covariance method under low and high volatility samples of data. In general historical simulation method over estimates the VaR for extreme events, while variance-covariance underestimates it. The method that we illustrate gives a result in between because it considers historical performance of the stocks and also corrects for the heavy tails of the distribution. We conclude that the estimate method that we illustrate here is useful in estimating VaR for extreme events, especially for high volatility times.
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Mean-variance & mean-VaR portfolio selection : a simulation based comparison in Czech crisis environment
Parrák, Radovan ; Hájek, Filip (referee) ; Seidler, Jakub (advisor)
This thesis focuses on two methods for optimum portfolio selection. We compare Mean-Variance method with Mean-VaR method by the means of investment simulation, based on Czech financial market data from turbulent market periods of the year 2007 and the year 2008. We theoretically describe various approaches of optimum portfolio selection within a frame of Mean-Variance as well as Mean-VaR method. Furthermore, we highlight the similarities and differences of both strategies. Finally, we compare both strategies, basing on measurements of relative and absolute profitability of both strategies in crisis periods.
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Development of bank loans for private sector in Czech Republic
Doutnáčová, Jana ; Teplý, Petr (referee) ; Seidler, Jakub (advisor)
This work focuses on the development of the loan market in the czech economy. In the first portion of this work, the problems of bank loans at the infancy of the Czech Republic transformation are described. Subsequently depicted is the loan emission evolution in the private sector during the 90's, the 1997 crisis impact on the loan market and the following "credit crunch" are examined in more detail. Additionally, the influence of the privatization of large czech banks on the loan administration after the year 2000 is studied as well as the entrance of the Czech Republic into the European Union, which affected primarily banking regulation. The second portion of this work analyzes the connection between bank loan growth rate and economic measures (GNP, loan rates, and classified loans). This analysis is executed for the household and the business sectors of the Czech Republic separately.
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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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The stock market volatility in the Czech Republic : rises and falls
Princ, Michael ; Netuka, Martin (advisor) ; Seidler, Jakub (referee)
The thesis concentrate on a volatility analysis os a stock market in the Czech Republic in years 1994-2009 including a comparison with a data available from world developed stock markets - namely European region, USA and Japan, econometric tools include GARCH model and its most popular derivates and generalisations I.E. IGARCH, EGARCH AND APARCH PROCESSES. The thesis is split into two main parts. The first part is devoted to a PSE volatility analysis based only on domestic data series involving GARCH class model estimations, forecasting abilities comparison and also a structural-break analysis based on the ICSS algorithm including the Inclan-Tiao test and its successors. Next part involves a dynamic analysis based on DCC MVGARCH model, which describes a change in a volatility spillover effect during the time. Data source used during the model estimation includes a development of stock indices and also net profits from point of view of Czech investor investing on global markets. It is furthermore supported by Granger causality estimation, which reveals a long-lasting unidirectional dependence of PSE on other developed markets. The complex results, which arise from a synergistic compound of particular econometric models, show that the stock market in the Czech Republic came through three main phases.
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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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