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Revisiting agent-based models of algorithmic trading strategies

Abstract:

Algorithmic trading (AT) strategies aim at executing large orders discretely, in order to minimize the order’s impact, whilst also hiding the traders’ intentions. The contribution of this paper is twofold. First we presented a method for identifying the most suitable market simulation type, based on the specific market model to be investigated. Then we proposed an extended model of the Bayesian execution strategy. We implemented and assessed this model using our tool AlTraSimBa (ALgorithmic T...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1007/978-3-662-44871-7_4

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Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Role:
Author

Contributors

Role:
Editor
Role:
Editor
Publisher:
Springer Verlag Publisher's website
Volume:
8780
Issue:
LNCS
Pages:
92-121
Series:
Lecture Notes in Computer Science
Host title:
Lecture Notes in Computer Science
Publication date:
2014-09-27
DOI:
ISSN:
0302-9743
Source identifiers:
507393
Keywords:
Pubs id:
pubs:507393
UUID:
uuid:b8293fc8-bacd-4b46-ad58-c7f13eba6fe8
Local pid:
pubs:507393
Deposit date:
2019-01-07

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