Bandit Market Makers
| dc.contributor.author | Della Penna, Nicolas | |
| dc.contributor.author | Reid, Mark | |
| dc.date.accessioned | 2019-11-25T23:35:10Z | |
| dc.date.available | 2019-11-25T23:35:10Z | |
| dc.date.issued | 2011 | |
| dc.date.updated | 2019-05-19T08:23:15Z | |
| dc.description.abstract | We propose a flexible framework for profit-seeking market making by combining cost function based automated market makers with bandit learning algorithms. The key idea is to consider each parametrisation of the cost function as a bandit arm, and the minimum expected profits from trades executed during a period as the rewards. This allows for the creation of market makers that can adjust liquidity and bid-asks spreads dynamically to maximise profits. | en_AU |
| dc.format.mimetype | application/pdf | en_AU |
| dc.identifier.uri | http://hdl.handle.net/1885/186624 | |
| dc.language.iso | en_AU | en_AU |
| dc.provenance | Attribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0) | en_AU |
| dc.rights | © 2011 The Author(s) | en_AU |
| dc.rights.license | Attribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0) | en_AU |
| dc.rights.uri | https://creativecommons.org/licenses/by-nc-sa/3.0/ | en_AU |
| dc.source | Computing Research Repository (CoRR) | en_AU |
| dc.source.uri | https://arxiv.org/abs/1112.0076 | en_AU |
| dc.title | Bandit Market Makers | en_AU |
| dc.type | Conference paper | en_AU |
| dcterms.accessRights | Open Access | en_AU |
| local.bibliographicCitation.lastpage | 7 | en_AU |
| local.bibliographicCitation.startpage | 1 | en_AU |
| local.contributor.affiliation | Della Penna, Nicolas, College of Engineering and Computer Science, ANU | en_AU |
| local.contributor.affiliation | Reid, Mark, College of Engineering and Computer Science, ANU | en_AU |
| local.contributor.authoremail | u4466898@anu.edu.au | en_AU |
| local.contributor.authoruid | Della Penna, Nicolas, u4941783 | en_AU |
| local.contributor.authoruid | Reid, Mark, u4466898 | en_AU |
| local.description.notes | Imported from ARIES | en_AU |
| local.identifier.absfor | 080109 - Pattern Recognition and Data Mining | en_AU |
| local.identifier.absseo | 970108 - Expanding Knowledge in the Information and Computing Sciences | en_AU |
| local.identifier.ariespublication | u4963866xPUB167 | en_AU |
| local.identifier.uidSubmittedBy | u4963866 | en_AU |
| local.type.status | Published Version | en_AU |
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