Price jump prediction in a limit order book

Ban Zheng, Eric Moulines () and Frédéric Abergel ()
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Ban Zheng: LTCI - Laboratoire Traitement et Communication de l'Information - Télécom ParisTech - IMT - Institut Mines-Télécom [Paris] - CNRS - Centre National de la Recherche Scientifique, FiQuant - Chaire de finance quantitative - MICS - Mathématiques et Informatique pour la Complexité et les Systèmes - CentraleSupélec
Eric Moulines: LTCI - Laboratoire Traitement et Communication de l'Information - Télécom ParisTech - IMT - Institut Mines-Télécom [Paris] - CNRS - Centre National de la Recherche Scientifique
Frédéric Abergel: FiQuant - Chaire de finance quantitative - MICS - Mathématiques et Informatique pour la Complexité et les Systèmes - CentraleSupélec, MAS - Mathématiques Appliquées aux Systèmes - EA 4037 - Ecole Centrale Paris

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Abstract: A limit order book provides information on available limit order prices and their volumes. Based on these quantities, we give an empirical result on the relationship between the bid-ask liquidity balance and trade sign and we show that liquidity balance on best bid/best ask is quite informative for predicting the future market order's direction. Moreover, we de ne price jump as a sell (buy) market order arrival which is executed at a price which is smaller (larger) than the best bid (best ask) price at the moment just after the precedent market order arrival. Features are then extracted related to limit order volumes, limit order price gaps, market order information and limit order event information. Logistic regression is applied to predict the price jump from the limit order book's feature. LASSO logistic regression is introduced to help us make variable selection from which we are capable to highlight the importance of di erent features in predicting the future price jump. In order to get rid of the intraday data seasonality, the analysis is based on two separated datasets: morning dataset and afternoon dataset. Based on an analysis on forty largest French stocks of CAC40, we nd that trade sign and market order size as well as the liquidity on the best bid (best ask) are consistently informative for predicting the incoming price jump.

Keywords: limit order book; price jumps; predictibility; LASSO (search for similar items in EconPapers)
Date: 2013-05
New Economics Papers: this item is included in nep-fmk, nep-for and nep-mst
Note: View the original document on HAL open archive server: https://hal.science/hal-00684716v2
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Citations: View citations in EconPapers (7)

Published in journal of mathematical finance, 2013, 3 (2), pp.242-255. ⟨10.4236/jmf.2013.3202⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-00684716

DOI: 10.4236/jmf.2013.3202

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