Show simple item record

dc.contributor.authorAdıgüzel Mercangöz, Burcu
dc.date.accessioned2021-12-10T13:20:03Z
dc.date.available2021-12-10T13:20:03Z
dc.identifier.citationAdıgüzel Mercangöz B., Portfolio Optimization, "Applying Particle Swarm Optimization: New Solutions and Cases for Optimized Portfolios", Burcu Adıgüzel Mercangöz, Editör, Springer, London/Berlin , Basel, ss.15-27, 2021
dc.identifier.otherav_ff982f78-dc2c-42de-9c13-438a3d699b9a
dc.identifier.othervv_1032021
dc.identifier.urihttp://hdl.handle.net/20.500.12627/175951
dc.identifier.urihttps://www.springer.com/gp/book/9783030702809
dc.description.abstractIn portfolio management, it is aimed to create a portfolio that gives the best combination of risk and return among the assets in the market. There are different optimization techniques for creating an optimum portfolio depending on the risk and return variable. Particle swarm optimization (PSO) method is one of the important and useful techniques used in portfolio optimization in finance. In this chapter, Markowitz mean-variance model, which is the main model of modern portfolio theory, is explained, and mathematical representations are given. The subject is supported with mathematical notations by mentioning concepts such as portfolio risk and return, efficient frontier, utility theory, asset allocation, indifference curves, Sharpe ratio, and coefficient of variation.
dc.language.isoeng
dc.publisherSpringer, London/Berlin 
dc.subjectMühendislik ve Teknoloji
dc.subjectSosyal ve Beşeri Bilimler
dc.subjectSosyal Bilimler (SOC)
dc.subjectMühendislik, Bilişim ve Teknoloji (ENG)
dc.titleApplying Particle Swarm Optimization: New Solutions and Cases for Optimized Portfolios
dc.typeKitapta Bölüm
dc.contributor.departmentİstanbul Üniversitesi , Ulaştırma Ve Lojistik Fakültesi , Ulaştırma Ve Lojistik Bölümü
dc.contributor.firstauthorID2648566


Files in this item

FilesSizeFormatView

There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record