Abstract
The paper presents the use of third order stochastic dominance in ranking Investment alternatives, using TSD algorithms (Levy, 2006)for testing third order stochastic dominance. The main goal of using TSD rule is minimization of efficient investment set for investor with risk aversion, who prefers more money and likes positive skew ness.
Highlights
Abstract:The paperpresents theuse ofthird orderstochastic dominance inranking investmentalternatives, using TSDalgorithms (Levy, 2006)for testingthird order stochastic dominance
Lako se dokazuje da iz prvostepene (FSD), odnosno drugostepene stohastičke dominacije (SSD), sledi trećestepena stohastička dominacija (TSD), tako da su FSD i SSD u stvari dovoljni uslovi za postojanje TSD, a u nastavku navodimo dve teoreme koje daju neke od potrebnih uslova za TSD: Teorema1. (Schmidt, 2005): ako X TSD Y, onda E X E Y
Posmatrali smo skup investicija sa tiker simbolima: AZO, COG, DUK, ED, FAST, GIS, GR, JNJ, MCD, MMI, ORLY, PG, PGN, SO, VFC (Lončar, 2011а:163), nakon primene TSD algoritma, dobijamo TSD relacije između 15 navedenih investicija (Slika 1), tada TSD-efikasni skup čine sve investicije iz SSD-efikasnog skupa isključujući FAST, budući da je on TSD dominiran od strane ORLY
Summary
Abstract:The paperpresents theuse ofthird orderstochastic dominance inranking investmentalternatives, using TSDalgorithms (Levy, 2006)for testingthird order stochastic dominance. Trećestepena stohastička dominacija, pored uslova za funkciju korisnosti U , koji su postavljeni u pristupu drugostepene stohastičke dominacije (U 0,U 0 ) postavlja i uslov nenegativnosti trećeg izvoda funkcije korisnosti U 0 . Odgovarajuća stroga relacija trećestepene stohastičke dominacije TSD definiše se na sledeći način: Definicija 2.
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