Robust portfolio construction using sorting signatures

 

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dc.contributor.advisor Bradfield, Dave en_ZA
dc.contributor.advisor Bailey, Geraldine en_ZA
dc.contributor.author Kasenene, Lillian en_ZA
dc.date.accessioned 2014-10-17T10:09:56Z
dc.date.available 2014-10-17T10:09:56Z
dc.date.issued 2014 en_ZA
dc.identifier.citation Kasenene, L. 2014. Robust portfolio construction using sorting signatures. University of Cape Town. en_ZA
dc.identifier.uri http://hdl.handle.net/11427/8527
dc.description Includes bibliographical references. en_ZA
dc.description.abstract Mean-variance analysis introduced by Harry Markowitz has been criticised in the past mainly due to the counter-intuitive and unstable nature of the resultant portfolios from the optimisation. These disappointing results have been linked to the presence of estimation error in the estimates of the expected returns and covariances which serve as input to the optimisation. Several attempts have been made to produce more reliable estimates, with a significant amount of effort and resources placed in estimation of expected returns, which is generally a more difficult task than estimation of covariances. Almgren and Chriss (2006) provide a methodology for portfolio selection in which the order of expected returns replaces the numerical values of the returns. This framework allows full use of the covariance matrix, in a method analogous to mean-variance optimisation. We adopt this framework in our analysis together with the robust optimisation technique introduced by Golts and Jones (2009) which improves the estimate of the covariance matrix by direct modification in the optimisation process. Golts and Jones (2009) argue that a reduction of the angle between the input return forecasts and the output portfolio positions results in more investment relevant portfolios, inline with the investment manager's insights. They relate this angle to the condition number of the covariance matrix and use robust optimisation to improve the conditioning of this matrix. Assuming perfect alpha foresight of an investment manager, we apply a combination of the techniques of Almgren and Chriss (2006) and Golts and Jones (2009) to South African equity data and show that the resultant robust portfolios, though conservative in their risk-adjusted return statistics, are more diversified and exhibit lower leverage than mean-variance portfolios. We further show that independent of the optimisation method, there is a marginal difference in the performance of portfolios created using ordering information and actual returns. en_ZA
dc.language.iso eng en_ZA
dc.title Robust portfolio construction using sorting signatures en_ZA
dc.type Master Thesis
uct.type.publication Research en_ZA
uct.type.resource Thesis en_ZA
dc.publisher.institution University of Cape Town
dc.publisher.faculty Faculty of Commerce en_ZA
dc.publisher.department Division of Actuarial Science en_ZA
dc.type.qualificationlevel Masters
dc.type.qualificationname MPhil en_ZA
uct.type.filetype Text
uct.type.filetype Image
dc.identifier.apacitation Kasenene, L. (2014). <i>Robust portfolio construction using sorting signatures</i>. (Thesis). University of Cape Town ,Faculty of Commerce ,Division of Actuarial Science. Retrieved from http://hdl.handle.net/11427/8527 en_ZA
dc.identifier.chicagocitation Kasenene, Lillian. <i>"Robust portfolio construction using sorting signatures."</i> Thesis., University of Cape Town ,Faculty of Commerce ,Division of Actuarial Science, 2014. http://hdl.handle.net/11427/8527 en_ZA
dc.identifier.vancouvercitation Kasenene L. Robust portfolio construction using sorting signatures. [Thesis]. University of Cape Town ,Faculty of Commerce ,Division of Actuarial Science, 2014 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/8527 en_ZA
dc.identifier.ris TY - Thesis / Dissertation AU - Kasenene, Lillian AB - Mean-variance analysis introduced by Harry Markowitz has been criticised in the past mainly due to the counter-intuitive and unstable nature of the resultant portfolios from the optimisation. These disappointing results have been linked to the presence of estimation error in the estimates of the expected returns and covariances which serve as input to the optimisation. Several attempts have been made to produce more reliable estimates, with a significant amount of effort and resources placed in estimation of expected returns, which is generally a more difficult task than estimation of covariances. Almgren and Chriss (2006) provide a methodology for portfolio selection in which the order of expected returns replaces the numerical values of the returns. This framework allows full use of the covariance matrix, in a method analogous to mean-variance optimisation. We adopt this framework in our analysis together with the robust optimisation technique introduced by Golts and Jones (2009) which improves the estimate of the covariance matrix by direct modification in the optimisation process. Golts and Jones (2009) argue that a reduction of the angle between the input return forecasts and the output portfolio positions results in more investment relevant portfolios, inline with the investment manager's insights. They relate this angle to the condition number of the covariance matrix and use robust optimisation to improve the conditioning of this matrix. Assuming perfect alpha foresight of an investment manager, we apply a combination of the techniques of Almgren and Chriss (2006) and Golts and Jones (2009) to South African equity data and show that the resultant robust portfolios, though conservative in their risk-adjusted return statistics, are more diversified and exhibit lower leverage than mean-variance portfolios. We further show that independent of the optimisation method, there is a marginal difference in the performance of portfolios created using ordering information and actual returns. DA - 2014 DB - OpenUCT DP - University of Cape Town LK - https://open.uct.ac.za PB - University of Cape Town PY - 2014 T1 - Robust portfolio construction using sorting signatures TI - Robust portfolio construction using sorting signatures UR - http://hdl.handle.net/11427/8527 ER - en_ZA


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