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Fools Rush In: Competitive Effects of Reaction Time in Automated Trading

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

Original languageEnglish
Title of host publication12th International Conference on Agents and Artificial Intelligence (ICAART-2020)
Publisher or commissioning bodySciTePress
Pages82-93
Number of pages12
Volume1
ISBN (Electronic)978-989-758-395-7
ISBN (Print)978-989-758-395-7
DOIs
DateAccepted/In press - 17 Dec 2019
DatePublished (current) - 18 Mar 2020
EventICAART-2020: 12th International Conference on Agents and Artificial Intelligence - Valletta, Malta
Duration: 22 Feb 202024 Feb 2020
http://www.icaart.org/

Conference

ConferenceICAART-2020: 12th International Conference on Agents and Artificial Intelligence
CountryMalta
CityValletta
Period22/02/2024/02/20
Internet address

Abstract

We explore the competitive effects of reaction time of automated trading strategies in simulated financial markets containing a single exchange with public limit order book and continuous double auction matching. A large body of research conducted over several decades has been devoted to trading agent design and simulation, but the majority of this work focuses on pricing strategy and does not consider the time taken for these strategies to compute. In real-world financial markets, speed is known to heavily influence the design of automated trading algorithms, with the generally accepted wisdom that faster is better. Here, we introduce increasingly realistic models of trading speed and profile the computation times of a suite of eminent trading algorithms from the literature. Results demonstrate that: (a) trading performance is impacted by speed, but faster is not always better; (b) the Adaptive-Aggressive (AA) algorithm, until recently considered the most dominant trading strategy in the literature, is outperformed by the simplistic Shaver (SHVR) strategy — shave one tick off the current best bid or ask — when relative computation times are accurately simulated.

    Research areas

  • Agent Based Modelling, Auctions, Automated Trading, Financial Markets, Simulation, Trading Agents

Event

ICAART-2020: 12th International Conference on Agents and Artificial Intelligence

Duration22 Feb 202024 Feb 2020
CityValletta
CountryMalta
Web address (URL)
Degree of recognitionInternational event

Event: Conference

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  • Full-text PDF (final published version)

    Rights statement: This is the final published version of the article (version of record). It first appeared online via SciTe Press at http://www.scitepress.org/DigitalLibrary/Link.aspx?doi=10.5220/0008973700820093. Please refer to any applicable terms of use of the publisher.

    Final published version, 1.12 MB, PDF document

    Licence: CC BY-NC-ND

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