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Capital allocation principles
Dvořák, Daniel ; Mazurová, Lucie (advisor) ; Hurt, Jan (referee)
Insurance companies or other financial institutions face financial risks during their various activites. Risk capital is allocated in order to cover these risks. The goal of capital allocation is to redistribute this capital to various constituents of the firm with respect to their riskiness. The thesis deals with risk measures and allocation methods. Special emphasis is put on the notions of coherent risk measures and coherent allocation methods. Conditions of coherence are checked for certain allocation methods. The thesis also deals with practical calculation of allocations to individual risks using allocation methods. 1
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Financial risks with copulas
Prelecová, Natália ; Hurt, Jan (advisor) ; Zichová, Jitka (referee)
The aim of this thesis is the thorough description of the copula theory. It deals with the theory's basic definitions, classes and characteristics. In addition, relations between copulas and dependence measures are explained. Furthermore, we evaluate the possibilities of copula's parametres estimation and selecting the right copula for real data. Then, the copula theory is interconnected with the basic risk measures in finance. We describe the elementary categorization of financial risks and standard risk measurement approaches. We also define basic risk measures with the emphasis on value at risk. Lastly, we present a real data case study of a selected portfolio.
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Generalized Linear Models in Reserving Risk
Zboňáková, Lenka ; Pešta, Michal (advisor) ; Branda, Martin (referee)
In the presented thesis we deal with the generalized linear models framework in a claims reserving problem. Claims reserving in non-life insurance is firstly described and the considered class of models is introduced. Consequently, this branch of stochastic modelling is implemented in the reserving setup. For computation of the risk associated with claims reserving, we need a predictive distribution of future liabilities in order to evaluate risk measures such as Va- lue at Risk and Conditional Value at Risk. Since datasets in non-life insurance commonly consist of a small number of observations and estimation of predictive distributions can be complicated, we adopt a bootstrap method for this purpose. Model fitting, simulations and consequent measuring of the reserving risk are performed within the use of real-life data. Based on this, an analysis of fitted models and their comparison together with graphical outputs is included. 1
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Portfolio efficiency with continuous probability distribution of returns
Kozmík, Václav
Present work deals with the portfolio selection problem using mean-risk models. The main goal of this work is to investigate the convergence of approximate solutions using generated scenarios to the analytic solution and its sensitivity to chosen risk measure and probability distribution. The considered risk measures are: variance, VaR, cVaR, absolute deviation and semivariance. We present analytical solutions for all risk measures under the assumption of normal or Student distribution. For log-normal distribution, we use the approximate assumption that the sum of log-normal random variables has log-normal distribution. Optimization models for discrete scenarios are derived for all risk measures and compared with analytical solution. In case of approximate solution with scenarios, we repeat the procedure multiple times and present our own approach to finding the optimal solution using the cluster analysis. All optimization models are written in GAMS language. Testing and estimating are realized using an application developed in C++ language.
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Data Envelopment Analysis with financial application
Marcinek, Daniel ; Branda, Martin (advisor) ; Zichová, Jitka (referee)
This thesis deals with various methods of Data Envelopment Analysis and their use in finance. Efficiency is measured by a ratio of weighted outputs to weighted inputs. From this model, a fractional programming problem is formed, which is then transformed into a linear programming problem. We derive a dual problem for that one. We also introduce another methods of Data Envelopment Analysis. We explain difference between a constant return to scale and a variable return to scale. We deal with a risk measures, which are considered as the inputs together with the management fees. We use gross returns as the single input. We apply these models to 15 mutual funds, determine efficiency of these mutual funds and compare these methods with another one. At the end we determine how the efficiency changes if we use only the risk measures as the inputs.
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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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Mean-Variance and Mean-CVaR Models in Portfolio Optimization
Spousta, Tomáš ; Borovička, Adam (advisor) ; Odintsov, Kirill (referee)
The thesis mainly deals with a comparison of two methods that could be used in portfolio optimization (efficient portfolio frontier searching). The first chapter consists of brief introduction to portfolio theory, it also reveals motivation for usage of more sophisticated risk statistics. Following chapter contains definition of both models that have been used in the analysis. First of them is famous Markowitz's model that has become a legend during 60 years of its existence. The most significant advantage is its simplicity, on the other hand it cannot deal with non-normality of asset returns. Normality assumption can be omitted using Maen-CVaR model -- the second model used in the analysis. Final part of this thesis is an application of both models on four different real datasets. Obtained results are analysed with attention on the constitution of efficient portfolio sets and their VaR.
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