Deep hedging in incomplete markets

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dc.contributor.advisorMavuso, Melusi
dc.contributor.authorStangroom, Jake
dc.date.accessioned2024-10-29T10:13:21Z
dc.date.available2024-10-29T10:13:21Z
dc.date.issued2024
dc.date.updated2024-07-09T13:01:21Z
dc.description.abstractThis dissertation presents an extensive analysis of the neural network approximation of mean-variance hedging with a comparison between the current neural network approaches and the theoretical solutions. These theoretical solutions provide a simulation-based performance benchmark for this comparison. Furthermore, this dissertation implements a financial market generator which allows for a realistic performance analysis based on both real and pseudo-real data; whereby, deep hedging is shown to offer highly competitive industry performance. Finally, the dissertation shows that deep hedging is effective for other quadratic criterion such as those similar to local risk-minimisation techniques.
dc.identifier.apacitationStangroom, J. (2024). <i>Deep hedging in incomplete markets</i>. (). ,Faculty of Science ,Department of Statistical Sciences. Retrieved from http://hdl.handle.net/11427/40641en_ZA
dc.identifier.chicagocitationStangroom, Jake. <i>"Deep hedging in incomplete markets."</i> ., ,Faculty of Science ,Department of Statistical Sciences, 2024. http://hdl.handle.net/11427/40641en_ZA
dc.identifier.citationStangroom, J. 2024. Deep hedging in incomplete markets. . ,Faculty of Science ,Department of Statistical Sciences. http://hdl.handle.net/11427/40641en_ZA
dc.identifier.ris TY - Thesis / Dissertation AU - Stangroom, Jake AB - This dissertation presents an extensive analysis of the neural network approximation of mean-variance hedging with a comparison between the current neural network approaches and the theoretical solutions. These theoretical solutions provide a simulation-based performance benchmark for this comparison. Furthermore, this dissertation implements a financial market generator which allows for a realistic performance analysis based on both real and pseudo-real data; whereby, deep hedging is shown to offer highly competitive industry performance. Finally, the dissertation shows that deep hedging is effective for other quadratic criterion such as those similar to local risk-minimisation techniques DA - 2024 DB - OpenUCT DP - University of Cape Town KW - Statistical Sciences LK - https://open.uct.ac.za PY - 2024 T1 - Deep hedging in incomplete markets TI - Deep hedging in incomplete markets UR - http://hdl.handle.net/11427/40641 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/40641
dc.identifier.vancouvercitationStangroom J. Deep hedging in incomplete markets. []. ,Faculty of Science ,Department of Statistical Sciences, 2024 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/40641en_ZA
dc.language.rfc3066Eng
dc.publisher.departmentDepartment of Statistical Sciences
dc.publisher.facultyFaculty of Science
dc.subjectStatistical Sciences
dc.titleDeep hedging in incomplete markets
dc.typeThesis / Dissertation
dc.type.qualificationlevelMasters
dc.type.qualificationlevelMSc
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