This work focuses on measuring the quality of stochastic dominance approx- imation. A measure of non-dominance is developed to quantify the error caused by assuming that a stochastic dominance relationship holds even when it does not. It is computed exactly for uniform, normal, and exponential distribution, and a numerical study is performed to estimate its values for log-normal and gamma distribution. Portfolio optimization problems involving stochastic dom- inance constraints are also presented. They are applied to real-life data using monthly returns of twelve assets captured by the German stock index DAX. The end of this work focuses on the computation of the measure of non-dominance for the optimal portfolio with respect to the second-order stochastic dominance. 1
Identifer | oai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:456081 |
Date | January 2022 |
Creators | Junová, Jana |
Contributors | Kopa, Miloš, Lachout, Petr |
Source Sets | Czech ETDs |
Language | Czech |
Detected Language | English |
Type | info:eu-repo/semantics/masterThesis |
Rights | info:eu-repo/semantics/restrictedAccess |
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