An Improved Platform for Multi-Agent Based Stock Market Simulation in Distributed Environment Article Swipe
Ce Yu
,
Xiang Chen
,
Chunyu Wang
,
Hutong Wu
,
Jizhou Sun
,
Yuelei Li
,
Xiaotao Zhang
·
YOU?
·
· 2015
· Open Access
·
· DOI: https://doi.org/10.1587/transinf.2015edp7050
YOU?
·
· 2015
· Open Access
·
· DOI: https://doi.org/10.1587/transinf.2015edp7050
Multi-agent based simulation has been widely used in behavior finance, and several single-processed simulation platforms with Agent-Based Modeling (ABM) have been proposed. However, traditional simulations of stock markets on single processed computers are limited by the computing capability since financial researchers need larger and larger number of agents and more and more rounds to evolve agents' intelligence and get more efficient data. This paper introduces a distributed multi-agent simulation platform, named PSSPAM, for stock market simulation focusing on large scale of parallel agents, communication system and simulation scheduling. A logical architecture for distributed artificial stock market simulation is proposed, containing four loosely coupled modules: agent module, market module, communication system and user interface. With the customizable trading strategies inside, agents are deployed to multiple computing nodes. Agents exchange messages with each other and with the market based on a customizable network topology through a uniform communication system. With a large number of agent threads, the round scheduling strategy is used during the simulation, and a worker pool is applied in the market module. Financial researchers can design their own financial models and run the simulation through the user interface, without caring about the complexity of parallelization and related problems. Two groups of experiments are conducted, one with internal communication between agents and the other without communication between agents, to verify PSSPAM to be compatible with the data from Euronext-NYSE. And the platform shows fair scalability and performance under different parallelism configurations.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1587/transinf.2015edp7050
- https://www.jstage.jst.go.jp/article/transinf/E98.D/10/E98.D_2015EDP7050/_pdf
- OA Status
- diamond
- Cited By
- 3
- References
- 27
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2108663150
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W2108663150Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1587/transinf.2015edp7050Digital Object Identifier
- Title
-
An Improved Platform for Multi-Agent Based Stock Market Simulation in Distributed EnvironmentWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2015Year of publication
- Publication date
-
2015-01-01Full publication date if available
- Authors
-
Ce Yu, Xiang Chen, Chunyu Wang, Hutong Wu, Jizhou Sun, Yuelei Li, Xiaotao ZhangList of authors in order
- Landing page
-
https://doi.org/10.1587/transinf.2015edp7050Publisher landing page
- PDF URL
-
https://www.jstage.jst.go.jp/article/transinf/E98.D/10/E98.D_2015EDP7050/_pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
diamondOpen access status per OpenAlex
- OA URL
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https://www.jstage.jst.go.jp/article/transinf/E98.D/10/E98.D_2015EDP7050/_pdfDirect OA link when available
- Concepts
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Computer science, Scalability, Distributed computing, Scheduling (production processes), Multi-agent system, Stock exchange, Financial market, Stock market, Database, Artificial intelligence, Finance, Economics, Paleontology, Horse, Operations management, BiologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
3Total citation count in OpenAlex
- Citations by year (recent)
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2024: 1, 2021: 1, 2017: 1Per-year citation counts (last 5 years)
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27Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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