research-article

An Agent-Based Model of Competition Between Financial Exchanges: Can Frequent Call Mechanisms Drive Trade Away from CDAs?

Authors:

Sanmay DasAuthors Info & Claims

AAMAS '16: Proceedings of the 2016 International Conference on Autonomous Agents & Multiagent Systems

Pages 50 - 58

Published: 09 May 2016 Publication History

Abstract

In the debate over high frequency trading, the frequent call (Call) mechanism has recently received considerable attention as a proposal for replacing the continuous double auction (CDA) mechanisms that currently run most financial markets. One natural question, which has begun to spur the development of new models, is the effect of competition between platforms that use these two different mechanisms when agents can strategize over platform choice. In this paper we contribute to this nascent literature by developing an agent-based model of competition between a Call market and a CDA market. Our model incorporates patient informed traders (both high-frequency and not) who are willing to wait for order execution at their preferred price and impatient background traders who demand immediate execution. We show that there is a strong tendency for the Call market to absorb a significant fraction of trade under most equilibrium and approximate-equilibrium conditions. These equilibria typically lead to significantly higher welfare for the background traders, an important measure of social value, than the operation of an isolated CDA market.

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Cited By

Cao L(2022)AI in Finance: Challenges, Techniques, and OpportunitiesACM Computing Surveys10.1145/350228955:3(1-38)Online publication date: 3-Feb-2022
https://dl.acm.org/doi/10.1145/3502289
Cheng FEngel YWellman M(2019)Cap-and-trade emissions regulationProceedings of the 28th International Joint Conference on Artificial Intelligence10.5555/3367032.3367060(187-193)Online publication date: 10-Aug-2019
https://dl.acm.org/doi/10.5555/3367032.3367060
Vaidya TMurguia CPiliouras GAndre EKoenig SDastani MSukthankar G(2018)Learning Agents in Financial MarketsProceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems10.5555/3237383.3238087(2106-2108)Online publication date: 9-Jul-2018
https://dl.acm.org/doi/10.5555/3237383.3238087
Show More Cited By

Index Terms

An Agent-Based Model of Competition Between Financial Exchanges: Can Frequent Call Mechanisms Drive Trade Away from CDAs?
1. Applied computing
  1. Law, social and behavioral sciences
    1. Economics
2. Computing methodologies
  1. Modeling and simulation
    1. Simulation types and techniques
      1. Agent / discrete models

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Information

Published In

cover image ACM Other conferences

AAMAS '16: Proceedings of the 2016 International Conference on Autonomous Agents & Multiagent Systems

May 2016

1580 pages

ISBN:9781450342391

General Chairs:
Catholijn M. Jonker
TU Delft, Netherlands
,
Stacy Marsella
University of Southern California, USA
,
Program Chairs:
John Thangarajah
RMIT University. Australia
,
Karl Tuyls
University of Liverpool, UK

Sponsors

IFAAMAS

In-Cooperation

SIGAI: ACM Special Interest Group on Artificial Intelligence

Publisher

International Foundation for Autonomous Agents and Multiagent Systems

Richland, SC

Publication History

Published: 09 May 2016

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US National Science Foundation

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AAMAS '16

Sponsor:

AAMAS '16: International Conference on Agents and Multiagent Systems

May 9 - 13, 2016

Singapore, Singapore

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AAMAS '16 Paper Acceptance Rate 137 of 550 submissions, 25%;

Overall Acceptance Rate 1,155 of 5,036 submissions, 23%

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Cited By

Cao L(2022)AI in Finance: Challenges, Techniques, and OpportunitiesACM Computing Surveys10.1145/350228955:3(1-38)Online publication date: 3-Feb-2022
https://dl.acm.org/doi/10.1145/3502289
Cheng FEngel YWellman M(2019)Cap-and-trade emissions regulationProceedings of the 28th International Joint Conference on Artificial Intelligence10.5555/3367032.3367060(187-193)Online publication date: 10-Aug-2019
https://dl.acm.org/doi/10.5555/3367032.3367060
Vaidya TMurguia CPiliouras GAndre EKoenig SDastani MSukthankar G(2018)Learning Agents in Financial MarketsProceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems10.5555/3237383.3238087(2106-2108)Online publication date: 9-Jul-2018
https://dl.acm.org/doi/10.5555/3237383.3238087
Wright MWellman MAndre EKoenig SDastani MSukthankar G(2018)Evaluating the Stability of Non-Adaptive Trading in Continuous Double AuctionsProceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems10.5555/3237383.3237475(614-622)Online publication date: 9-Jul-2018
https://dl.acm.org/doi/10.5555/3237383.3237475
Wang XWellman MLarson KWinikoff MDas SDurfee E(2017)Spoofing the Limit Order BookProceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems10.5555/3091125.3091219(651-659)Online publication date: 8-May-2017
https://dl.acm.org/doi/10.5555/3091125.3091219
Brinkman EWellman MDaskalakis CBabaioff MMoulin H(2017)Empirical Mechanism Design for Optimizing Clearing Interval in Frequent Call MarketsProceedings of the 2017 ACM Conference on Economics and Computation10.1145/3033274.3085153(205-221)Online publication date: 20-Jun-2017
https://dl.acm.org/doi/10.1145/3033274.3085153

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