Calibrating a Latent Order Book Model to Market Data

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dc.contributor.advisorGebbie, Timothy
dc.contributor.authorGant, Michael
dc.date.accessioned2023-03-07T12:46:00Z
dc.date.available2023-03-07T12:46:00Z
dc.date.issued2022
dc.date.updated2023-02-20T12:46:48Z
dc.description.abstractWe investigate the formulation of the Latent Order Book (LOB) as a reaction diffusion Partial Differential Equation (PDE) and its subsequent numerical solution through an explicit method based on discrete stochastic processes. The numerical solution is calibrated using likelihood-free methods, Approximate Bayesian Computation (ABC) and an iterative extension, Population Monte-Carlo ABC (PMC-ABC) as well as a Black-box approach using the Nelder-Mead algorithm. We show that in the diffusion limit, the master equation becomes the LOB reaction-diffusion PDE and certain free-parameters are recoverable with the iterative calibration techniques.
dc.identifier.apacitationGant, M. (2022). <i>Calibrating a Latent Order Book Model to Market Data</i>. (). ,Faculty of Science ,Department of Statistical Sciences. Retrieved from http://hdl.handle.net/11427/37333en_ZA
dc.identifier.chicagocitationGant, Michael. <i>"Calibrating a Latent Order Book Model to Market Data."</i> ., ,Faculty of Science ,Department of Statistical Sciences, 2022. http://hdl.handle.net/11427/37333en_ZA
dc.identifier.citationGant, M. 2022. Calibrating a Latent Order Book Model to Market Data. . ,Faculty of Science ,Department of Statistical Sciences. http://hdl.handle.net/11427/37333en_ZA
dc.identifier.ris TY - Master Thesis AU - Gant, Michael AB - We investigate the formulation of the Latent Order Book (LOB) as a reaction diffusion Partial Differential Equation (PDE) and its subsequent numerical solution through an explicit method based on discrete stochastic processes. The numerical solution is calibrated using likelihood-free methods, Approximate Bayesian Computation (ABC) and an iterative extension, Population Monte-Carlo ABC (PMC-ABC) as well as a Black-box approach using the Nelder-Mead algorithm. We show that in the diffusion limit, the master equation becomes the LOB reaction-diffusion PDE and certain free-parameters are recoverable with the iterative calibration techniques. DA - 2022_ DB - OpenUCT DP - University of Cape Town KW - Statistical Sciences, LK - https://open.uct.ac.za PY - 2022 T1 - Calibrating a Latent Order Book Model to Market Data TI - Calibrating a Latent Order Book Model to Market Data UR - http://hdl.handle.net/11427/37333 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/37333
dc.identifier.vancouvercitationGant M. Calibrating a Latent Order Book Model to Market Data. []. ,Faculty of Science ,Department of Statistical Sciences, 2022 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/37333en_ZA
dc.language.rfc3066eng
dc.publisher.departmentDepartment of Statistical Sciences
dc.publisher.facultyFaculty of Science
dc.subjectStatistical Sciences,
dc.titleCalibrating a Latent Order Book Model to Market Data
dc.typeMaster Thesis
dc.type.qualificationlevelMasters
dc.type.qualificationlevelMSc
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