Portfolio Selection with Swarm Intelligence

DSpace/Manakin Repository

Show simple item record

dc.contributor.advisor Billio, Monica it_IT
dc.contributor.author Ciani, Gabriele <1993> it_IT
dc.date.accessioned 2018-02-16 it_IT
dc.date.accessioned 2018-06-22T09:58:30Z
dc.date.issued 2018-03-20 it_IT
dc.identifier.uri http://hdl.handle.net/10579/12769
dc.description.abstract The introduction of budget, cardinality and composition constraints to the portfolio selection problem implies the utilization of modern techniques for the achievement of the solution. In particular, this thesis will analyse Particle Swarm Optimization, a bio-inspired metaheuristic algorithm that aims to explore the search space in order to find optimal solutions. The problem considered consists in the minimization of a coherent risk measure, the expected shortfall, subject to risk adjusted performance constraints, budget, cardinality and fractions constraints. In practice, a chosen number of particles are exploring the set of feasible solutions. To the position of each particle is assigned a value of the objective function which accounts for the risk measure and for penalties associated to the constraints. Particles move according to signals given by their neighbors, by the particle with the best result and by their own memory. The implementation of the PSO algorithm is used to find a feasible and well diversified portfolio composed by Exchange Traded Funds sold on the Italian market, Borsa Italiana. it_IT
dc.language.iso en it_IT
dc.publisher Università Ca' Foscari Venezia it_IT
dc.rights © Gabriele Ciani, 2018 it_IT
dc.title Portfolio Selection with Swarm Intelligence it_IT
dc.title.alternative Portfolio Optimization with Swarm Intelligence it_IT
dc.type Bachelor Thesis it_IT
dc.degree.name Economia e finanza - economics and finance it_IT
dc.degree.level Laurea magistrale it_IT
dc.degree.grantor Dipartimento di Economia it_IT
dc.description.academicyear 2016/2017, sessione straordinaria it_IT
dc.rights.accessrights closedAccess it_IT
dc.thesis.matricno 860998 it_IT
dc.subject.miur SECS-P/02 POLITICA ECONOMICA it_IT
dc.description.note it_IT
dc.degree.discipline it_IT
dc.contributor.co-advisor it_IT
dc.date.embargoend 10000-01-01
dc.provenance.upload Gabriele Ciani (860998@stud.unive.it), 2018-02-16 it_IT
dc.provenance.plagiarycheck Monica Billio (billio@unive.it), 2018-03-05 it_IT


Files in this item

This item appears in the following Collection(s)

Show simple item record