Modern portfolio optimization using robust estimation techniques

Rather than following a normal distribution, share returns and market proxies have been shown to follow skewed distributions, with long tails in some cases. In this dissertation various robust estimation techniques are investigated in an attempt to minimise the influence that outliers may have on the estimation and to better estimate the input parameters for the Markowitz and Sharpe portfolio models. The main goal is to ascertain whether or not the input parameters determined, using the robust procedures, yield better results than the Ordinary Least Squares (OLS) procedure.

Grantor dc:publisher.institution

Department of Mathematics and Applied Mathematics

Year dc:date.issued

2005

Author dc:creator

• Van Straaten, Conrad

Advisor dc:contributor.advisor

• Troskie, Casper G

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/11427/4943

OAI identifier oai:identifier

oai:open.uct.ac.za:11427/4943