Liquidity Dynamics in an Electronic Open Limit Order Book: an Event Study Approach

Published date01 January 2015
Date01 January 2015
Liquidity Dynamics in an Electronic
Open Limit Order Book: An Event
Study Approach
Peter Gomber
University of Frankfurt, Grüneburgplatz 1, 60323, Frankfurt, Germany
Uwe Schweickert
Deutsche Börse AG, 60487, Frankfurt, Germany
Erik Theissen
University of Mannheim, Center for Financial Studies (Frankfurt) and Centre for Financial Research
(Cologne), Finance Area, L5 2, 68161, Mannheim, Germany
We analyse the dynamics of liquidity in an electronic limit order book using the
Exchange Liquidity Measure (XLM), a measure of the cost of a roundtrip trade of
given size V. We use intraday event study methodology to analyse how liquidity
shocks large transactions and Bloomberg ticker news affect the XLM. We nd
that resiliency after large transactions is high, i.e., liquidity quickly reverts to
normallevels. Large trades are timed; they take place at times when liquidity is
unusually high. Bloomberg ticker news items do not have a discernible effect on
Keywords: liquidity, limit order book, resiliency
JEL classification: G10
Earlier versions of this paper were circulated under the title Zooming in on Liquidity.We
thank Deutsche Börse AG for providing the data. We thank an anonymous referee, Pierre
Giot, Joachim Grammig, Alexander Kempf, participants of the 31st annual meeting of the
European Finance Association, of the 11th annual meeting of the German Finance
Association, of the 9th Symposium on Finance, Banking and Insurance in Karlsruhe and
seminar participants at the University of St. Gallen and the University of Exeter for valuable
comments. Correspondence: Erik Theissen.
European Financial Management, Vol. 21, No. 1, 2015, 5278
doi: 10.1111/j.1468-036X.2013.12006.x
© 2013 John Wiley & Sons Ltd
1. Introduction
It is a commonplace that liquidity is the most important determinant of market quality. It
affects the transaction costs for investors, and it is a decisive factor in the competition for
order ow among exchanges, and between exchanges and proprietary trading systems.
Over the last decades researchers have gained a thorough understanding of liquidity.
There is a wide array of liquidity measures, and the crosssectional and timeseries
determinants of liquidity are fairly well understood. However, our understanding of the
intraday dynamics of liquidity, and of the motives that govern traderschoices between
market orders and limit orders is much less well understood.
Our paper contributes to the literature on liquidity by analysing the dynamics of
liquidity in an electronic open limit order book. The main building block of our analysis is
the Exchange Liquidity Measure XLM(V).
It measures the cost of a roundtrip trade of
size V. We analyse how this measure reacts to liquidity shocks. To do so we employ an
intraday event study approach. Using data at 1minute frequency we analyse how the
XLM(V) measure reacts to liquidity shocks. We consider two types of shocks, large
transactions and Bloomberg ticker news. The large transactions are endogenous events
because they originate in the market. The ticker news, on the other hand, are exogenous.
Our main ndings can be summarised as follows. Large transactions (by denition)
have an immediate negative impact on liquidity because limit orders in the book are
executed. We nd that liquidity partially recovers within one or two minutes after the
transaction, but does not reach its pretransaction level. There thus appears to be a
permanent effect. The explanation for this pattern is revealed once the XLM measure prior
to the transaction is included in the analysis. Liquidity increases prior to the transaction.
Thus, transactions take place when liquidity is unusually high. Immediately after the
transaction, liquidity reverts to its normal level. It does not, however, revert to the
unusually high level immediately prior to the transaction. The observed pattern suggests
that large transactions are timed. This is an important result because it implies that traders
initiating large trades, although being arguably less patient than limit order traders, do
have the patience to delay their transaction until liquidity is high enough. Our results are
also consistent with theoretical predictions that market orders are more attractive when
liquidity is high (e.g. Foucault, 1999; Foucault et al., 2005), and with the intuition that the
incentive to split large orders is lower when liquidity is high. The nding that large
transactions are timed also suggests that the results of studies treating the timing of large
trades as exogenous may be misleading.
We do not nd a clear pattern in the XLM measure around the publication of news items
on the Bloomberg ticker. This may be because the news items are anticipated,
they do not have information content per se, or because Bloomberg is not the rst channel
through which the information reaches the market. Additional analyses yield support for
the second and the third explanation.
Our paper is related to various strands of the microstructure literature. Several authors
have proposed theoretical models of dynamic limit order markets (e.g. Parlour, 1998:
See section 2 and Gomber and Schweickert (2002) for a description of the XLM measure.
Market participants may know that there will be an information event and withdraw liquidity
in anticipation of the release. In such a case there will obviously be an effect on liquidity, but it
will be observed prior to the event and not upon publication of the news item.
© 2013 John Wiley & Sons Ltd
Liquidity Dynamics in an Electronic Open Limit Order Book 53

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