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Investment problems with stochastic dominance constraints
Dorová, Bianka ; Kopa, Miloš (advisor) ; Kozmík, Václav (referee)
This thesis focuses on stochastic dominance in portfolio selection problems. The thesis recalls basic knowledge from the area of portfolio optimization with utility functions and first, second, $N$-th and infinite order of stochastic dominance. It sumarizes Post's, Kuosmanen's and Kopa's criteria for portfolio efficiency and necessary and sufficient conditions of stochastic dominance for discrete and continuous probability distributions. The thesis also contains formulations of optimization problems with second order stochastic dominance constraints derived for discrete and continuous probability distributions. A practical application is also a part of the thesis, where the optimization problems for monthly returns of Czech stocks are solved using optimization software GAMS.
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Kelly criterion in portfolio selection problems
Dorová, Bianka ; Kopa, Miloš (advisor) ; Omelka, Marek (referee)
In the present work we study portfolio optimization problems. Introduction is followed by chapter 2, where we introduce the concept of utility function and its relationship to the investor's risk attitude. To solve the optimization problem we consider the Markowitz portfolio optimization model and the Kelly criterion, which are recalled in the fourth and fifth chapter. The work also contains an extensive numerical study. Using the optimization software GAMS we solve portfolio optimization problems. We consider a portfolio problem with (and without) allowed short sales. We compare the obtained portfolios and we discuss whether Kelly optimal portfolio is a special case of the Markowitz optimal portfolio for the special value of the minimum expected return.
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Stochastic DEA and dominance
Majerová, Michaela ; Kopa, Miloš (advisor) ; Dupačová, Jitka (referee)
At the beginning of this thesis we discuss DEA methods, which measure efficiency of Decision Making Units by comparing weighted inputs and outputs. First we describe basic DEA models without random inputs and outputs then stochastic DEA models which are derived from the deterministic ones. We describe more approaches to stochastic DEA models, for example using scenario approach or chance constrained programming problems. Another approach for measuring efficiency employs stochastic dominance. Stochastic dominance is a relation that allows to compare two random variables. We describe the first and second order stochastic dominance. First we consider pairwise stochastic efficiency, then we discuss the first and second order stochastic dominance portfolio efficiency. We describe different tests to measure this type of efficiency. At the end of this thesis we study efficiency of US stock portfolios using real historical data and we compare results obtained when using stochastic DEA models and stochastic dominance. Powered by TCPDF (www.tcpdf.org)
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The transportation problem, its generalizations and applications in probability and statistics
Doležel, Pavel ; Dupačová, Jitka (advisor) ; Kopa, Miloš (referee)
Author describes a specific optimization problem-the transportation problem and analyzes relevant solution methods. Several methods of solving the transportation problem are listed, applied or introduced and applications of the transportation poblem in the theory of probability and mathematical statistics are presented, namely the statistical sorting in L1 norm and re-construction of contingency tables. Special interest is devoted to several modifications of ordinary transportation problem, mainly the multiindex transportation problem. The crucial part of the work are selected applications of the transportation problem to particular problems and showing some algorithms used for finding solutions.
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Multiobjective portfolio optimization
Malá, Alena ; Kopa, Miloš (advisor) ; Dupačová, Jitka (referee)
The goal of this thesis is to summarize three basic principles of solving multi-objective programming problems. We focus on three approaches: a linear combination of objective functions, ε-constrained approach and a goal programming. All these methods are subsequently applied to US data. We consider monthly excess returns of ten US representative portfolios based on individual stock market capitalization of equity that serve as basic assets. Our aim is to find the efficient portfolios. Next we investigate a structure of these portfolios and their mutual relationships. Graphic representation of efficient frontiers is also included in the thesis. All calculations were performed using Mathematica software version 8.
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Spatial econometrics
Nývltová, Veronika ; Pawlas, Zbyněk (advisor) ; Kopa, Miloš (referee)
This thesis is devoted to the models that are suitable for modelling spatial data. For this purpose, random fields with finite index set are used. Based on the neighbourhood relationship a spatial weight matrix is introduced which describes spatial dependencies. A recognition and testing of spatial dependence is mentioned and it is applied for macroeconomic indicators in the Czech Republic. Spatial models originated from generalization of usual time series models are subsequently combined with linear regression models. The parameter estimators are derived for selected models by three different methods. These methods are ordinary least squares, maximum likelihood and method of moments. Theoretical asymptotic results are supplemented by a simulation study that examines the performance of estimators for finite sample size. Finally, a short illustration on real data is demonstrated. Powered by TCPDF (www.tcpdf.org)
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Searching for optimal path in graphs
Znamenáčková, Gabriela ; Lachout, Petr (advisor) ; Kopa, Miloš (referee)
It's possible to simulate a lot of real decision-making situations by a weighted graph. Consequently it's important to find the optimal solution of a given situation based on this model. The subject of this Bachelor Thesis is to present the typical problems of combinatorial optimization, that deal with finding the optimal path in a graph considering the given conditions, and algorithms to find their optimal solution. It's focused on following problems: the shortest path problem, the minimum cost spanning-tree problem, the minimum cost Steiner tree problem, the travelling salesman problem and the optimal network flow. Working of some algorithms is shown on illustrative examples.
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