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Erschienen in:
2014 | OriginalPaper | Buchkapitel
Pattern Mining in Ultra-High Frequency Order Books with Self-Organizing Maps
verfasst von : Piotr Lipinski, Anthony Brabazon
Erschienen in: Applications of Evolutionary Computation
Verlag: Springer Berlin Heidelberg
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This paper addresses the issue of discovering frequent patterns in order book shapes, in the context of the stock market depth, for ultra-high frequency data. It proposes a computational intelligence approach to building frequent patterns by clustering order book shapes with Self-Organizing Maps. An experimental evaluation of the approach proposed on the London Stock Exchange Rebuild Order Book database succeeded with providing a number of characteristic shape patterns and also with estimating probabilities of some typical transitions between shape patterns in the order book.