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Abstract: Large trades in a financial market are usually split into smaller parts andtraded incrementally over extended periods of time. We address these largetrades as hidden orders. In order to identify and characterize hidden orders wefit hidden Markov models to the time series of the sign of the tick by tickinventory variation of market members of the Spanish Stock Exchange. Ourmethodology probabilistically detects trading sequences, which arecharacterized by a net majority of buy or sell transactions. We interpret thesepatches of sequential buying or selling transactions as proxies of the tradedhidden orders. We find that the time, volume and number of transactions sizedistributions of these patches are fat tailed. Long patches are characterizedby a high fraction of market orders and a low participation rate, while shortpatches have a large fraction of limit orders and a high participation rate. Weobserve the existence of a buy-sell asymmetry in the number, average length,average fraction of market orders and average participation rate of thedetected patches. The detected asymmetry is clearly depending on the localmarket trend. We also compare the hidden Markov models patches with thoseobtained with the segmentation method used in Vaglica {\it et al.} 2008 andwe conclude that the former ones can be interpreted as a partition of thelatter ones.



Author: Gabriella Vaglica, Fabrizio Lillo, Rosario N. Mantegna

Source: https://arxiv.org/







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