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This paper concerns knowledge discovery from ultra-high frequency financial time series of order book data from the London Stock Exchange Rebuild Order Book database. It focuses on extracting frequent patterns from order book shapes, which characterize particular stock market states. Because order book shapes vary considerably in time, it is necessary to convert the original price-volume representation...
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