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Contemporary measures of financial risk
Leder, Ondřej ; Hurt, Jan (advisor) ; Zichová, Jitka (referee)
The main goal of this work is to talk about some financial risks and to introduce some methods of measuring them. The most important part of this work is the value at risk, its extension in form of conditional value at risk and introduction of some of its possible alternatives, which are expectile and spectral risk measures. For this it is needed to give a theoretical framework from the theory of probability. Its goal is to show the similarity of expectile and quantile, because value at risk is practicaly a quantile. Another goal of this fork is to show some weak properties of VaR and to practically illustrate the possibility of using expectile as an alternative to VaR. Powered by TCPDF (www.tcpdf.org)
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Diversification in Data Envelopment Analysis in finance
Macková, Simona ; Branda, Martin (advisor) ; Hurt, Jan (referee)
Title: Diversification in Data Envelopment Analysis in Finance Author: Simona Macková Department: Department of Probability and Mathematical Statistics Supervisor: RNDr. Martin Branda, Ph.D., Department of Probability and Ma- thematical Statistics Abstract: This thesis deals with an extension of data envelopment analysis and its application in finance. This method enables to evaluate the efficiency of cho- sen production units based on several inputs and outputs. Administrative fees or risk measures can be used as inputs and expected incomes of observed assets as outputs in financial application. We show basic traditional models in a form of a primary problem of linear programming and a dual problem as well and later compare with diversification models. It is suitable to deal with diversification which enables to consider dependencies between assets in case of finance and in- vestments. Than we get to nonlinear programming problem hence we introduce appropriate risk and return measures to make the problem solvable. Especially, we focus on the conditional value at risk. Next we introduce the model which deals with diversification. We use this on real data of chosen mutual funds. Keywords: Data envelopment analysis, Efficiency, Diversification, Conditional value at risk
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Optimal investment problems solvable using linear programming
Jančařík, Joel ; Branda, Martin (advisor) ; Kopa, Miloš (referee)
Portfolio optimization problem is a classical optimization problem, where the expected return of the portfolio is maximized and the risk is minimized. In this bachelor thesis some LP solvable portfolio optimization models are studied. Application on real life financial data is also included. Model with Conditional Value at Risk, MAD-model and Minimax model are described. In numerical analysis data from Frankfurt Stock Exchange are used and optimization has been made by Wolfram Mathematica 9.0 function LinearProgramming. As a result we got optimal portfolios for eleven different models for each of six minimal expected return constraints. The portfolios have been then evaluated according to the data from next year period. Powered by TCPDF (www.tcpdf.org)
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Insurance pricing methods based on risk measures
Malá, Kateřina ; Branda, Martin (advisor) ; Mazurová, Lucie (referee)
In this thesis we study various risk measures and one of their characteristics - the coherence. We talk especially about value-at-risk (VaR in short), respectively about conditional value-at- risk (CVaR). We also mention the advantage of CVaR against VaR. After that we discuss the most common forms of compound distribution that are used in practice. The final part of this bachelor thesis is dedicated to a numerical study where we calculate mean, variance, VaR a CVaR for specific values of parameters.
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Cyber risk modelling using copulas
Spišiak, Michal ; Teplý, Petr (advisor) ; Baruník, Jozef (referee)
Cyber risk or data breach risk can be estimated similarly as other types of operational risk. First we identify problems of cyber risk models in existing literature. A large dataset consisting of 5,713 loss events enables us to apply extreme value theory. We adopt goodness of fit tests adjusted for distribution functions with estimated parameters. These tests are often overlooked in the literature even though they are essential for correct results. We model aggregate losses in three different industries separately and then we combine them using a copula. A t-test reveals that potential one-year global losses due to data breach risk are larger than the GDP of the Czech Republic. Moreover, one-year global cyber risk measured with a 99% CVaR amounts to 2.5% of the global GDP. Unlike others we compare risk measures with other quantities which allows wider audience to understand the magnitude of the cyber risk. An estimate of global data breach risk is a useful indicator not only for insurers, but also for any organization processing sensitive data.
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Optimization of reinsurace parameters in insurance
Dlouhá, Veronika ; Branda, Martin (advisor) ; Cipra, Tomáš (referee)
This thesis is dedicated to searching optimal parameters of reinsurance with a focus of quota-share and stop-loss reinsurance. The optimization is based on minimization of value at risk and conditional value at risk of total costs of the insurer for the recieved risk. It also presents a compound random variable and shows various methods of obtaining its probability distribution, for example ap- proximation by lognormal or gamma mixtures distributions or by Panjer recurive method for continuous severity and numerical method of its solution. At the end of the thesis we can find the calculation of the optimal parameters of reinsurance for a compound random variable based on real data. We use various methods to determine probability distribution and premiums. 1
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Basic approaches to robust conditional value at risk
Nožička, Michal ; Branda, Martin (advisor) ; Petrová, Barbora (referee)
The work describes conditional value at risk, its robustification with respect to the probability distribution of yields of assets and its applications to optimal portfolio selection. In chapter one there are definitions of conditional value at risk and its generalization throught robustification and also motivation to these definitions. The basic properties of conditional value at risk, mainly coherence and continuity with respect to the parametr of confidence level, are discussed in chapter two. There is also shown that some of these properties are preserved after robustification. The third chapter is dedicated to the derivation of optimization problems of optimal portfolio selection on the basis of conditional value at risk and its robustification. This thesis describes only special cases so that the final problems are solveble by the means of linear programming. The fourth chapter describes particular utilization of these methods with usage of real data from financial markets. Powered by TCPDF (www.tcpdf.org)
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Statistical tests for VaR and CVaR
Mirtes, Lukáš ; Pešta, Michal (advisor) ; Večeř, Jan (referee)
The thesis presents test statistics of Value-at-Risk and Conditional Value-at-Risk. The reader is familiar with basic nonparametric estimators and their asymptotic distributions. Tests of accuracy of Value-at- Risk are explained and asymptotic test of Conditional Value-at-Risk is derived. The thesis is concluded by process of backtesting of Value-at-Risk model using real data and computing statistical power and probability of Type I error for selected tests. Powered by TCPDF (www.tcpdf.org)
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Insurance pricing methods based on risk measures
Malá, Kateřina ; Branda, Martin (advisor) ; Mazurová, Lucie (referee)
In this thesis we study various risk measures and one of their characteristics - the coherence. We talk especially about value-at-risk (VaR in short), respectively about conditional value-at- risk (CVaR). We also mention the advantage of CVaR against VaR. After that we discuss the most common forms of compound distribution that are used in practice. The final part of this bachelor thesis is dedicated to a numerical study where we calculate mean, variance, VaR a CVaR for specific values of parameters.
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Measuring systemic risk in time-frequency domain
Muzikářová, Ivana ; Baruník, Jozef (advisor) ; Bauer, Michal (referee)
This thesis provides an analysis of systemic risk in the US banking sector. We use conditional value at risk (∆CoVaR), marginal expected shortfall (MES) and cross-quantilogram (CQ) to statistically measure tail-dependence in return series of individual institutions and the system as a whole. Wavelet multireso- lution analysis is used to study systemic risk in the time-frequency domain. De- composition of returns on different scales allows us to isolate cycles of 2-8 days, 8-32 days and 32-64 days and analyze co-movement patterns which would oth- erwise stay hidden. Empirical results demonstrate that filtering out short-term noise from the return series improves the forecast power of ∆CoVaR. Eventu- ally, we investigate the connection between statistical measures of systemic risk and fundamental characteristics of institutions (size, leverage, market to book ratio) and conclude that size is the most robust determinant of systemic risk.
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