A market making quotation strategy based on dual deep learning agents for option pricing and bid-Ask spread estimation

Pei Ying Hsu, Chin Chou, Szu-Hao Huang, An-Pin Chen

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

Traditional professional traders and institutional investors utilized complex statistical models to price various derivative contracts and make trading decisions in the option and future markets. In recent years, with the rapid growth of algorithmic trading and program trading, the advanced information and communication technology has become an indispensable element for high-frequency traders, especially for the market makers. In addition, artificial intelligence and deep learning also plays an important role in novel financial technology (FinTech) research field. In this paper, we proposed a market making quotation strategy based on deep learning structure and practical finance domain knowledge. The proposed dual agents will simultaneously model the option prices and bid-Ask spreads. The experiments demonstrate that our system can precisely estimate the value of options than famous financial engineering models. It also can be extended to develop proper market making quotation strategies to trade the options of Taiwan Stock Exchange Capitalization Weighted Stock Index(TAIEX).

Original languageEnglish
Title of host publicationProceedings - 2018 IEEE International Conference on Agents, ICA 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages99-104
Number of pages6
ISBN (Print)9781538681800
DOIs
StatePublished - 10 Sep 2018
Event2018 IEEE International Conference on Agents, ICA 2018 - Singapore, Singapore
Duration: 28 Jul 201831 Jul 2018

Publication series

NameProceedings - 2018 IEEE International Conference on Agents, ICA 2018

Conference

Conference2018 IEEE International Conference on Agents, ICA 2018
CountrySingapore
CitySingapore
Period28/07/1831/07/18

Keywords

  • Bid-Ask spread
  • Deep learning
  • Market makers
  • Option pricing

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