{"id":{"repo_id":"cape-town","oai_identifier":"oai:open.uct.ac.za:11427/30891"},"canonical_url":"https://search.dev.ndltd.org/etd/cape-town/oai:open.uct.ac.za:11427/30891","repository":{"repo_id":"cape-town","name":"University of Cape Town","base_url":"https://open.uct.ac.za/oai/request"},"display":{"title":"Potential Future Exposure in the Presence of Initial Margin","abstract":"This dissertation considers the concept of potential future exposure, and how initial margin can be used to mitigate it. In addition to this, the cost of implementing initial margin is estimated, and some of the difficulties associated with it are addressed. The two primary techniques for calculating initial margin considered are nested Monte Carlo, and Gaussian Least Squares Monte Carlo. These two techniques are compared for effectiveness. 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In addition to this, the cost of implementing initial margin is estimated, and some of the difficulties associated with it are addressed. The two primary techniques for calculating initial margin considered are nested Monte Carlo, and Gaussian Least Squares Monte Carlo. These two techniques are compared for effectiveness. It is shown that the nested Monte Carlo technique performs well under numerous conditions, and that the Gaussian Least Squares Monte Carlo relies on particular model and instrument characteristics."]},{"key":"dc:title","label":"Title","values":["Potential Future Exposure in the Presence of Initial Margin"]}]}],"canonical_facts":{"dc:contributor.advisor":["McWalter, Thomas"],"dc:creator":["Nevin, James"],"dc:date.accessioned":["2020-02-06T12:25:57Z"],"dc:date.available":["2020-02-06T12:25:57Z"],"dc:date.issued":["2019"],"dc:description.abstract":["This dissertation considers the concept of potential future exposure, and how initial margin can be used to mitigate it. In addition to this, the cost of implementing initial margin is estimated, and some of the difficulties associated with it are addressed. The two primary techniques for calculating initial margin considered are nested Monte Carlo, and Gaussian Least Squares Monte Carlo. These two techniques are compared for effectiveness. It is shown that the nested Monte Carlo technique performs well under numerous conditions, and that the Gaussian Least Squares Monte Carlo relies on particular model and instrument characteristics."],"dc:identifier.uri":["http://hdl.handle.net/11427/30891"],"dc:publisher.department":["African Institute of Financial Markets and Risk Management"],"dc:subject":["Mathematical Finance"],"dc:title":["Potential Future Exposure in the Presence of Initial Margin"],"dc:type":["Master Thesis"],"dc:type.qualificationlevel":["Masters"],"dc:type.qualificationname":["MPhil"]},"updated_at":"2026-07-22T22:22:37Z"}