{"id":{"repo_id":"cape-town","oai_identifier":"oai:open.uct.ac.za:11427/31319"},"canonical_url":"https://search.dev.ndltd.org/etd/cape-town/oai:open.uct.ac.za:11427/31319","repository":{"repo_id":"cape-town","name":"University of Cape Town","base_url":"https://open.uct.ac.za/oai/request"},"display":{"title":"Application of Volatility Targeting Strategies within a Black-Scholes Framework","abstract":"The traditional Black-Scholes (BS) model relies heavily on the assumption that underlying returns are normally distributed. In reality however there is a large amount of evidence to suggest that this assumption is weak and that actual return distributions are non-Gaussian. This dissertation looks at algorithmically generating a Volatility Targeting Strategy (VTS) which can be used as an underlying asset. 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In reality however there is a large amount of evidence to suggest that this assumption is weak and that actual return distributions are non-Gaussian. This dissertation looks at algorithmically generating a Volatility Targeting Strategy (VTS) which can be used as an underlying asset. The rationale here is that since the VTS has a constant prespecified level of volatility, its returns should be normally distributed, thus tending closer to an underlying that adheres to the assumptions of BS."]},{"key":"dc:title","label":"Title","values":["Application of Volatility Targeting Strategies within a Black-Scholes Framework"]}]}],"canonical_facts":{"dc:contributor.advisor":["Mahomed, Obeid"],"dc:creator":["Vakaloudis, Dmitri"],"dc:date.accessioned":["2020-02-25T11:38:35Z"],"dc:date.available":["2020-02-25T11:38:35Z"],"dc:date.issued":["2019"],"dc:description.abstract":["The traditional Black-Scholes (BS) model relies heavily on the assumption that underlying returns are normally distributed. 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