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National Repository of Grey Literature 2 records found  Search took 0.00 seconds. 
Almost stochastic dominance
 Štefánik, Adam ; Kopa, Miloš (advisor) ; Branda, Martin (referee)
Title: Almost stochastic dominance Author: Adam Štefánik Department: Probability and Mathematical Statistics Supervisor: RNDr. Ing. Miloš Kopa, PhD. Department of Probability and Mathematical Statistics, MFF UK Abstract: In the presented work we study the almost stochastic dominance and it's properties. Almost stochastic dominance is a relaxation of stochastic dominance. Almost stochastic dominance also deals with paradox situations occurring in case of stochastic dominance. This is a situation when stochastic dominance determines indifferent relation- ship between two portfolios, but in fact almost all investors can choose the better one. The original almost stochastic dominance presented by Leshno and Levy (2002) is compu- tationally expensive. Lizyayev and Ruszczy'nski (2012) suggested an alternative approach. This work introduces both approaches. The most interesting part of this work is a search for efficient portfolio with respect to the almost stochastic dominance by the simple linear programming. Lizyayev and Ruszczy'nski (2012) approach is applied to Kopa and Chovanec (2008) quantile approach for portfolio efficiency testing with respect to second order stochastic dominance. Keywords: almost stochastic dominance, efficiency, CVaR
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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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