Full Text Available
Note: Clicking the button above will open the full text document at the original institutional repository in a new window.
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, Appro...
Saved in:
| Main Author: | |
|---|---|
| Other Authors: | |
| Format: | Thesis |
| Language: | English |
| Published: |
Department of Statistical Sciences
2023
|
| Subjects: | |
| Tags: |
No Tags, Be the first to tag this record!
|
| _version_ | 1867613285990268928 |
|---|---|
| access_status_str | Open Access |
| author | Gant, Michael |
| author2 | Gebbie, Timothy |
| author_browse | Gant, Michael Gebbie, Timothy |
| author_facet | Gebbie, Timothy Gant, Michael |
| author_sort | Gant, Michael |
| collection | Thesis |
| description | 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. |
| format | Thesis |
| id | oai:open.uct.ac.za:11427/37333 |
| institution | University of Cape Town (South Africa) |
| language | eng |
| last_indexed | 2026-06-10T12:33:43.673Z |
| license_str | Not specified — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository |
| publishDate | 2023 |
| publishDateRange | 2023 |
| publishDateSort | 2023 |
| publisher | Department of Statistical Sciences |
| publisherStr | Department of Statistical Sciences |
| record_format | dspace |
| source_str | UCTD — University of Cape Town Open Access Repository |
| spelling | oai:open.uct.ac.za:11427/37333 Calibrating a Latent Order Book Model to Market Data Gant, Michael Gebbie, Timothy Statistical Sciences, 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. 2023-03-07T12:46:00Z 2023-03-07T12:46:00Z 2022 2023-02-20T12:46:48Z Master Thesis Masters MSc http://hdl.handle.net/11427/37333 eng application/pdf Department of Statistical Sciences Faculty of Science |
| spellingShingle | Statistical Sciences, Gant, Michael Calibrating a Latent Order Book Model to Market Data |
| thesis_degree_str | Master's |
| title | Calibrating a Latent Order Book Model to Market Data |
| title_full | Calibrating a Latent Order Book Model to Market Data |
| title_fullStr | Calibrating a Latent Order Book Model to Market Data |
| title_full_unstemmed | Calibrating a Latent Order Book Model to Market Data |
| title_short | Calibrating a Latent Order Book Model to Market Data |
| title_sort | calibrating a latent order book model to market data |
| topic | Statistical Sciences, |
| url | http://hdl.handle.net/11427/37333 |
| work_keys_str_mv | AT gantmichael calibratingalatentorderbookmodeltomarketdata |