APPLICATION OF PORTFOLIO OPTIMIZATION: A STATISTICAL APPROACH

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dc.contributor.authorMAIGARI, Ahmadu Hamza
dc.date.accessioned2018-09-17T15:26:54Z
dc.date.available2018-09-17T15:26:54Z
dc.date.issued2018-03
dc.descriptionA THESIS SUBMITTED TO THE POSTGRADUATE SCHOOL, AHMADU BELLO UNIVERSITY, ZARIA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE AWARD OF THE DEGREE OF MASTER OF SCIENCE IN STATISTICS DEPARTMENT OF STATISTICS, FACULTY OF SCIENCE, AHMADU BELLO UNIVERSITY, ZARIA, NIGERIAen_US
dc.description.abstractThe main objective of this thesis is to look at how the Markowitz Mean-Variance assets selection model performs with distribution free model, Gini-Mean Difference model and highlight statistical approach to portfolio optimization in terms of risk reduction; interrelationships of diversified assets, assets rebalancing and stochastic dominance etc. In the study, the Mean-Variance model tends to slightly outperform the Gini-Mean Difference model in return/risk characteristics. More sophisticated investors can use the Gini-Mean Difference model if they posses the skills as it involves more complex computations in the procedure, and further captures the data than Mean-Variance approach since its distribution free model.en_US
dc.identifier.urihttp://hdl.handle.net/123456789/10458
dc.language.isoenen_US
dc.subjectAPPLICATION,en_US
dc.subjectPORTFOLIO OPTIMIZATION,en_US
dc.subjectSTATISTICAL APPROACHen_US
dc.titleAPPLICATION OF PORTFOLIO OPTIMIZATION: A STATISTICAL APPROACHen_US
dc.typeThesisen_US
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