Abstract
We have built an agent service-based enterprise infrastructure: F-TRADE. With its online connectivity to huge real stock data in global markets, it can be used for online evaluation of trading strategies and data mining algorithms. The main functions in the F-TRADE include soft plug-and-play, and back-testing, optimization, integration and evaluation of algorithms. In this paper, we’ll focus on introducing the intelligent plug-and-play, which is a key system function in the F-TRADE. The basic idea for the soft plug-and-play is to build agent services which can support the online plug-in of agents, algorithms and data sources. Agent UML-based modeling, role model and agent services for the plug-and-play are discussed. With this design, algorithm providers, data source providers, and system module developers of the F-TRADE can expand system functions and resources by online plugging them into the F-TRADE.
F-TRADE is a web-based automated enterprise infrastructure for evaluation of trading strategies and data mining algorithms with online connection to huge amount of stock data. It has been online running for more than one year. It gets fund support from CMCRC (Capital Market CRC, www.cmcrc.com) for the Data Mining Program at CMCRC.
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References
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© 2004 Springer-Verlag Berlin Heidelberg
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Cao, L., Ni, J., Wang, J., Zhang, C. (2004). Agent Services-Driven Plug-and-Play in F-TRADE. In: Webb, G.I., Yu, X. (eds) AI 2004: Advances in Artificial Intelligence. AI 2004. Lecture Notes in Computer Science(), vol 3339. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30549-1_79
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DOI: https://doi.org/10.1007/978-3-540-30549-1_79
Publisher Name: Springer, Berlin, Heidelberg
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