Calibrating a Latent Order Book Model to Market Data

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.

Grantor

Department of Statistical Sciences

Year dc:date.issued

2022

Author dc:creator

• Gant, Michael

Advisor dc:contributor.advisor

• Gebbie, Timothy

• Statistical Sciences,

Handle dc:identifier.uri

http://hdl.handle.net/11427/37333

OAI identifier oai:identifier

oai:open.uct.ac.za:11427/37333