Trading on major financial markets is typically conducted via electronic order books whose state is visible to market participants in real-time. A significant research literature has emerged concerning order book evolution, focussing on characteristics of the order book such as the time series of trade prices, movements in the bid-ask spread and changes in the depth of the order book at each price point. The latter two items can be characterised as order book shape where the book is viewed as a histogram with the size of the bar at each price point corresponding to the volume of shares demanded or offered for sale at that price. Order book shape is of interest to market participants as it provides insight as to current, and potentially future, market liquidity. Questions such as what shapes are commonly observed in order books and whether order books transition between certain shape patterns over time are of evident interest from both a theoretical and practical standpoint. In this study, using high-frequency equity data from the London Stock Exchange, we apply an unsupervised clustering methodology to determine clusters of common order book shapes, and also attempt to assess the transition probabilities between these clusters. Findings indicate that order books for individual stocks display intraday seasonality, exhibit some common patterns, and that transitions between order book patterns over sequential time periods is not random.
Order book patterns Ultra high-frequency financial data Self-organising map Unsupervised clustering
This is a preview of subscription content, log in to check access.
This publication has emanated from research conducted with the financial support of Science Foundation Ireland under Grant No. 08/SRC/FM1389. Calculations have been carried out using resources provided by Wroclaw Centre for Networking and Supercomputing (http://wcss.pl), Grant No. 405. The authors would also like to acknowledge the contribution of the anonymous reviewers to the improvement of this paper and the work of Dr Wei Cui on the analysis of the descriptives in Sect. 3.
Al-Suhaibani M, Kryzanowski L (2000) An exploratory analysis of the order book, and order flow and execution on the Saudi stock market. J Bank Finance 24(5):1323–1357CrossRefGoogle Scholar
Ben Omrane W, de Bodt E (2007) Using self-organizing maps to adjust for intra-day seasonality. J Bank Finance 31(6):1817–1838CrossRefGoogle Scholar
Biais B, Hillion P, Spatt C (1995) An empirical analysis of the limit order book and the order flow in the Paris Bourse. J Finance 50(3):1655–1689CrossRefGoogle Scholar
Brabazon A, O’Neill M (2006) Biologically inspired algorithms for financial modeling. Springer, BerlinMATHGoogle Scholar
Brabazon A, O’Neill M, Dempsey I (2008) An introduction to evolutionary computation in finance. IEEE Comput Intell Mag 3(4):42–55CrossRefGoogle Scholar
Cai C, Hudson R, Keasey K (2004) Intraday bid-ask spreads, trading volume and volatility: recent empirical evidence from the London stock exchange. J Bus Finance Account 31(5):647–676CrossRefGoogle Scholar
Cao C, Hansch O, Wang X (2008) Order placement strategies in a pure limit order book market. J Financ Res 26(2):113–140CrossRefGoogle Scholar
Cao C, Hansch O, Wang X (2009) The information content of an open limit order book. J Futur Mark 29(1):16–41CrossRefGoogle Scholar
Chen T, Li J, Cai J (2008) Information content of inter-trade time on the Chinese market. Emerg Mark Rev 9(2):174–193CrossRefGoogle Scholar
Cho J, Nelling E (2000) The probability of limit-order execution. Financ Anal J 56(5):28–33CrossRefGoogle Scholar
Chung K, Van Ness B, Van Ness R (1999) Limit orders and the bid-ask spread. J Financ Econ 53(3):255–287CrossRefGoogle Scholar
Omura K, Tanigawa Y, Uno J (2000) Execution probability of limit orders on the Tokyo stock exchange. http://ssrn.com/abstract=252588. Accessed 25 April 2016
Pascual R, Verdas D (2009) What pieces of limit order book information matter in explaining order choice by patient and impatient traders? Quant Finance 9(1):527–545MathSciNetCrossRefGoogle Scholar
Pöllä M, Honkela T, Kohonen T (2009) Bibliography of self-organizing map (SOM) papers: 2002–2005 addendum. TKKReports in Information and Computer Science, Helsinki University of Technology, Report TKK-ICS-R24Google Scholar
Ranaldo A (2004) Order aggressiveness in limit order book markets. J Financ Mark 7(1):53–74CrossRefGoogle Scholar
Sarlin P, Peltonen T (2013) Mapping the state of financial stability. J Int Financ Mark Inst Money 26:46–76CrossRefGoogle Scholar
Verhoeven P, Ching S, Ng H (2004) Determinants of the decision to submit market or limit orders on the ASX. Pac Basin Finance J 12(3):1–18CrossRefGoogle Scholar
Wilinski M, Cui W, Brabazon A, Hamill P (2015) An analysis of price impact functions of individual trades on the London Stock Exchange. Quant Finance 15(10):1727–1735MathSciNetCrossRefGoogle Scholar