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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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Suitable utility function identification
Majerová, Michaela ; Kopa, Miloš (advisor) ; Lachout, Petr (referee)
At the beginning of this work we study basic properties of utility functions and connection between their shape and investor's relation to risk. Then we define risk premium and we recall measure of risk aversion. In the second chapter we study classification of utility functions according to the absolute risk aversion measure and we list some basic types of utility functions. In the third chapter we construct investor's utility function. We use values of insurance premium which we get from questionnaire filled by MFF UK students. We use these utility functions in the last chapter. First we define portfolio selection problem and then we find optimal portfolio for different investors.
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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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Suitable utility function identification
Majerová, Michaela ; Kopa, Miloš (advisor) ; Lachout, Petr (referee)
At the beginning of this work we study basic properties of utility functions and connection between their shape and investor's relation to risk. Then we define risk premium and we recall measure of risk aversion. In the second chapter we study classification of utility functions according to the absolute risk aversion measure and we list some basic types of utility functions. In the third chapter we construct investor's utility function. We use values of insurance premium which we get from questionnaire filled by MFF UK students. We use these utility functions in the last chapter. First we define portfolio selection problem and then we find optimal portfolio for different investors.
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