{"id":{"repo_id":"vu-aus","oai_identifier":"oai:eprints.vu.edu.au:18168"},"canonical_url":"https://search.dev.ndltd.org/etd/vu-aus/oai:eprints.vu.edu.au:18168","repository":{"repo_id":"vu-aus","name":"Victoria University (Australia)","base_url":"https://vuir.vu.edu.au/cgi/oai2"},"display":{"title":"Mean reversion in asset prices and asset allocation in investment management","abstract":"This thesis examines the predictability of asset prices for an Australian investor. Evidence supporting the mean reversion alternative to the random walk hypothesis is presented, with a discussion of potential models, both linear and nonlinear. The normality and homoscedasticity assumptions are investigated and their use in asset models is validated. A study of fund performance is carried out and value is found to be added by timing asset allocation but not by stock selection, though there is no correlation between past and present rankings of managers. The difficulty of proving mean reversion or reversion to trend, other than for large deviations or extremes, and the actual performance by managers, implies a strategy of allocation at these extremes. That is, managers should adhere to their policy portfolios and let markets run short term; making appropriate large strategic moves when markets have moved to extremes.","abstract_html":"This thesis examines the predictability of asset prices for an Australian investor. Evidence supporting the mean reversion alternative to the random walk hypothesis is presented, with a discussion of potential models, both linear and nonlinear. The normality and homoscedasticity assumptions are investigated and their use in asset models is validated. A study of fund performance is carried out and value is found to be added by timing asset allocation but not by stock selection, though there is no correlation between past and present rankings of managers. The difficulty of proving mean reversion or reversion to trend, other than for large deviations or extremes, and the actual performance by managers, implies a strategy of allocation at these extremes. That is, managers should adhere to their policy portfolios and let markets run short term; making appropriate large strategic moves when markets have moved to extremes.","abstract_has_math":false,"creators":["Hart, Keith Allen"],"institution":"Victoria University of Technology","degree_name":"other","degree_level":"cmaster","degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":1996,"date_issued":"1996","date_published":"1996","updated_at":"2026-07-24T06:33:25Z","subjects":["0102 Applied Mathematics","0802 Computation Theory and Mathematics","1502 Banking, Finance and Investment","School of Engineering and Science"],"languages":["en"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":null,"outbound_label":null,"outbound_source":null},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Hart, Keith Allen"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["1996"]},{"key":"dc:date.issued","label":"Date","values":["1996"]},{"key":"dc:publisher.department","label":"Dc Publisher Department","values":["Department of Computer and Mathematical Sciences"]},{"key":"dc:publisher.institution","label":"Dc Publisher Institution","values":["Victoria University of Technology"]},{"key":"dc:relation.isreferencedby","label":"Dc Relation Isreferencedby","values":["https://vuir.vu.edu.au/18168/"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"dc:type.qualificationlevel","label":"Dc Type Qualificationlevel","values":["cmaster"]},{"key":"dc:type.qualificationname","label":"Dc Type Qualificationname","values":["other"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["0102 Applied Mathematics","0802 Computation Theory and Mathematics","1502 Banking, Finance and Investment","School of Engineering and Science"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://vuir.vu.edu.au/18168/1/HART_1996compressed.pdf"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["This thesis examines the predictability of asset prices for an Australian investor. Evidence supporting the mean reversion alternative to the random walk hypothesis is presented, with a discussion of potential models, both linear and nonlinear. The normality and homoscedasticity assumptions are investigated and their use in asset models is validated. A study of fund performance is carried out and value is found to be added by timing asset allocation but not by stock selection, though there is no correlation between past and present rankings of managers. The difficulty of proving mean reversion or reversion to trend, other than for large deviations or extremes, and the actual performance by managers, implies a strategy of allocation at these extremes. 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A study of fund performance is carried out and value is found to be added by timing asset allocation but not by stock selection, though there is no correlation between past and present rankings of managers. The difficulty of proving mean reversion or reversion to trend, other than for large deviations or extremes, and the actual performance by managers, implies a strategy of allocation at these extremes. 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