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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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