Effect of Market Spread Over Reinforcement Learning Based Market Maker

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Market Making (also known as liquidity providing service) is a well-known trading problem studied in multiple disciplines including Finance, Economics and Artificial Intelligence. This paper examines the impact of Market Spread over the market maker’s (or liquidity provider’s) convergence ability through testing the hypothesis that “Knowledge of market spread while learning leads to faster convergence to an optimal and less volatile market making policy”. Reinforcement Learning was used to mimic the behaviour of a liquidity provider with Limit Order Book using historical Trade and Quote data of five equities, as the trading environment. An empirical study of results obtained from experiments (comparing our reward function with benchmark) shows significant improvement in the magnitude of returns obtained by a market maker with knowledge of market spread compared to a market maker without such knowledge, which proves our stated hypothesis.
Original languageEnglish
Title of host publicationMachine Learning, Optimization, and Data Science - 5th International Conference, LOD 2019, Proceedings
EditorsGiuseppe Nicosia, Panos Pardalos, Renato Umeton, Giovanni Giuffrida, Vincenzo Sciacca
Chapter13
Pages143-153
Number of pages11
Volume11943
ISBN (Electronic)978-3-030-37599-7
DOIs
Publication statusPublished - 3 Jan 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11943 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Keywords

  • Market making
  • Market spread
  • Reinforcement learning
  • Reward function

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  • Cite this

    Haider, A., Wang, H., Scotney, B., & Hawe, G. (2020). Effect of Market Spread Over Reinforcement Learning Based Market Maker. In G. Nicosia, P. Pardalos, R. Umeton, G. Giuffrida, & V. Sciacca (Eds.), Machine Learning, Optimization, and Data Science - 5th International Conference, LOD 2019, Proceedings (Vol. 11943, pp. 143-153). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11943 LNCS). https://doi.org/10.1007/978-3-030-37599-7_13