Adjoint Venture: Fast Greeks with Adjoint Algorithmic Differentiation

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dc.contributor.advisorMcWalter, Thomasen_ZA
dc.contributor.authorMcPetrie, Christopher Lindsayen_ZA
dc.date.accessioned2017-09-26T14:57:45Z
dc.date.available2017-09-26T14:57:45Z
dc.date.issued2017en_ZA
dc.description.abstractThis dissertation seeks to discuss the adjoint approach to solving affine recursion problems (ARPs) in the context of computing sensitivities of financial instruments. It is shown how, by moving from an intuitive 'forward' approach to solving a recursion to an 'adjoint' approach, one might dramatically increase the computational efficiency of algorithms employed to compute sensitivities via the pathwise derivatives approach in a Monte Carlo setting. Examples are illustrated within the context of the Libor Market Model. Furthermore, these ideas are extended to the paradigm of Adjoint Algorithmic Differentiation, and it is illustrated how the use of sophisticated techniques within this space can further improve the ease of use and efficiency of sensitivity calculations.en_ZA
dc.identifier.apacitationMcPetrie, C. L. (2017). <i>Adjoint Venture: Fast Greeks with Adjoint Algorithmic Differentiation</i>. (Thesis). University of Cape Town ,Faculty of Commerce ,Division of Actuarial Science. Retrieved from http://hdl.handle.net/11427/25412en_ZA
dc.identifier.chicagocitationMcPetrie, Christopher Lindsay. <i>"Adjoint Venture: Fast Greeks with Adjoint Algorithmic Differentiation."</i> Thesis., University of Cape Town ,Faculty of Commerce ,Division of Actuarial Science, 2017. http://hdl.handle.net/11427/25412en_ZA
dc.identifier.citationMcPetrie, C. 2017. Adjoint Venture: Fast Greeks with Adjoint Algorithmic Differentiation. University of Cape Town.en_ZA
dc.identifier.ris TY - Thesis / Dissertation AU - McPetrie, Christopher Lindsay AB - This dissertation seeks to discuss the adjoint approach to solving affine recursion problems (ARPs) in the context of computing sensitivities of financial instruments. It is shown how, by moving from an intuitive 'forward' approach to solving a recursion to an 'adjoint' approach, one might dramatically increase the computational efficiency of algorithms employed to compute sensitivities via the pathwise derivatives approach in a Monte Carlo setting. Examples are illustrated within the context of the Libor Market Model. Furthermore, these ideas are extended to the paradigm of Adjoint Algorithmic Differentiation, and it is illustrated how the use of sophisticated techniques within this space can further improve the ease of use and efficiency of sensitivity calculations. DA - 2017 DB - OpenUCT DP - University of Cape Town LK - https://open.uct.ac.za PB - University of Cape Town PY - 2017 T1 - Adjoint Venture: Fast Greeks with Adjoint Algorithmic Differentiation TI - Adjoint Venture: Fast Greeks with Adjoint Algorithmic Differentiation UR - http://hdl.handle.net/11427/25412 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/25412
dc.identifier.vancouvercitationMcPetrie CL. Adjoint Venture: Fast Greeks with Adjoint Algorithmic Differentiation. [Thesis]. University of Cape Town ,Faculty of Commerce ,Division of Actuarial Science, 2017 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/25412en_ZA
dc.language.isoengen_ZA
dc.publisher.departmentDivision of Actuarial Scienceen_ZA
dc.publisher.facultyFaculty of Commerceen_ZA
dc.publisher.institutionUniversity of Cape Town
dc.subject.otherMathematical Financeen_ZA
dc.titleAdjoint Venture: Fast Greeks with Adjoint Algorithmic Differentiationen_ZA
dc.typeMaster Thesis
dc.type.qualificationlevelMasters
dc.type.qualificationnameMPhilen_ZA
uct.type.filetypeText
uct.type.filetypeImage
uct.type.publicationResearchen_ZA
uct.type.resourceThesisen_ZA
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