{"id":{"repo_id":"cape-town","oai_identifier":"oai:open.uct.ac.za:11427/8528"},"canonical_url":"https://search.dev.ndltd.org/etd/cape-town/oai:open.uct.ac.za:11427/8528","repository":{"repo_id":"cape-town","name":"University of Cape Town","base_url":"https://open.uct.ac.za/oai/request"},"display":{"title":"Hedge fund of funds investment process : a South African perspective","abstract":"The objective of this dissertation is to develop and test an investment process for hedge fund of funds (HFoFs) in South Africa. The dissertation proposes a three tiered process, adapted from the works of Lo (2008). Step one of the proccess involves the categorisation of hedge funds into broadly defined groups based on predefined factors. Two classification methodologies are examined herein to determine optimal category definitions. These are 1) an adaption of the classification developed by Schneeweis and Spurgin (2000), based on the correlation of hedge funds to an appropriate benchmark and the returns offered by these hedge funds, and 2) classification by cluster analysis. Once a finite set of classification is defined, step two of the process uses a minimum variance optimisation, based on forward-looking parameter estimates of return and co-variance to compute the optimal capital allocation to these categories. The final stage of the process employs a mixture of quantitative and qualitative analysis to allocate capital within categories to individual hedge funds.","abstract_html":"The objective of this dissertation is to develop and test an investment process for hedge fund of funds (HFoFs) in South Africa. The dissertation proposes a three tiered process, adapted from the works of Lo (2008). Step one of the proccess involves the categorisation of hedge funds into broadly defined groups based on predefined factors. Two classification methodologies are examined herein to determine optimal category definitions. These are 1) an adaption of the classification developed by Schneeweis and Spurgin (2000), based on the correlation of hedge funds to an appropriate benchmark and the returns offered by these hedge funds, and 2) classification by cluster analysis. Once a finite set of classification is defined, step two of the process uses a minimum variance optimisation, based on forward-looking parameter estimates of return and co-variance to compute the optimal capital allocation to these categories. The final stage of the process employs a mixture of quantitative and qualitative analysis to allocate capital within categories to individual hedge funds.","abstract_has_math":false,"creators":["Hossain, Mahzabeen Natasha"],"institution":"Division of Actuarial Science","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Lubbe, Sugnet"],"committee_chairs":[],"committee_members":[],"year":2014,"date_issued":"2014","date_published":"2014","updated_at":"2026-07-22T22:22:41Z","subjects":[],"languages":["eng"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/11427/8528","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Lubbe, Sugnet"]},{"key":"dc:creator","label":"Author","values":["Hossain, Mahzabeen Natasha"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2014-10-17T10:09:56Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2014-10-17T10:09:56Z"]},{"key":"dc:date.issued","label":"Date","values":["2014"]},{"key":"dc:publisher.department","label":"Dc Publisher Department","values":["Division of Actuarial Science"]},{"key":"dc:publisher.institution","label":"Dc Publisher Institution","values":["University of Cape Town"]},{"key":"dc:type","label":"Dc Type","values":["Master Thesis"]},{"key":"dc:type.qualificationlevel","label":"Dc Type Qualificationlevel","values":["Masters"]},{"key":"dc:type.qualificationname","label":"Dc Type Qualificationname","values":["MPhil"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["eng"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/11427/8528"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Includes bibliographical references."]},{"key":"dc:description.abstract","label":"Abstract","values":["The objective of this dissertation is to develop and test an investment process for hedge fund of funds (HFoFs) in South Africa. The dissertation proposes a three tiered process, adapted from the works of Lo (2008). Step one of the proccess involves the categorisation of hedge funds into broadly defined groups based on predefined factors. Two classification methodologies are examined herein to determine optimal category definitions. These are 1) an adaption of the classification developed by Schneeweis and Spurgin (2000), based on the correlation of hedge funds to an appropriate benchmark and the returns offered by these hedge funds, and 2) classification by cluster analysis. Once a finite set of classification is defined, step two of the process uses a minimum variance optimisation, based on forward-looking parameter estimates of return and co-variance to compute the optimal capital allocation to these categories. 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Two classification methodologies are examined herein to determine optimal category definitions. These are 1) an adaption of the classification developed by Schneeweis and Spurgin (2000), based on the correlation of hedge funds to an appropriate benchmark and the returns offered by these hedge funds, and 2) classification by cluster analysis. Once a finite set of classification is defined, step two of the process uses a minimum variance optimisation, based on forward-looking parameter estimates of return and co-variance to compute the optimal capital allocation to these categories. 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