Publication Type
Conference Proceeding Article
Version
Publisher’s Version
Publication Date
9-2010
Abstract
In this paper, we introduce how one can validate an event-centric trading simulation platform that is built with multi-agent technology. The issue of validation is extremely important for agent-based simulations, but unfortunately, so far there is no one universal method that would work in all domains. The primary contribution of this paper is a novel combination of event-centric simulation design and event study approach for market dynamics generation and validation. In our event-centric design, the simulation is progressed by announcing news events that affect market prices. Upon receiving these events, event-aware software agents would adjust their views on the market and act accordingly. Their actions would be based on their roles and also their private information, and collectively the market dynamics will be shaped. The generated market dynamics can then be validated by a variant of the event study approach. We demonstrate how the methodology works with several numerical experiments and conclude by highlighting the practical significance of such simulation platform.
Keywords
analytical models, biological system modeling, computational modeling, economics, humans, numerical models, security
Discipline
Artificial Intelligence and Robotics | Business | Operations Research, Systems Engineering and Industrial Engineering
Publication
IEEE/WIC/ACM International Conference on Web Intelligence-Intelligent Agent Technology WI-IAT 2010: Toronto, August 31 - September 3
First Page
465
Last Page
469
ISBN
9781424484829
Identifier
10.1109/WI-IAT.2010.212
Publisher
IEEE Computer Society
City or Country
Los Alamitos, CA
Citation
CHENG, Shih-Fen.
Event study method for validating agent-based trading simulations. (2010). IEEE/WIC/ACM International Conference on Web Intelligence-Intelligent Agent Technology WI-IAT 2010: Toronto, August 31 - September 3. 465-469.
Available at: https://ink.library.smu.edu.sg/sis_research/1563
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
http://dx.doi.org/10.1109/WI-IAT.2010.212
Included in
Artificial Intelligence and Robotics Commons, Business Commons, Operations Research, Systems Engineering and Industrial Engineering Commons