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Order aggressiveness and order book dynamics 135
addresses the question of where and when it is likely that an order will be placed
given the current state of the market.
In order to reduce the impact of noise in the data and to allow for a better
identification of systematic relationships, we explicitly focus on most aggressive
market orders, limit orders and cancellations. On top of the common classification
scheme proposed by Biais et al. (1995), we select only those orders whose volumes
are substantially larger than the average order volume. 3 According to previous
studies in this field, these are the most aggressive and interesting orders. Note that
this classification scheme also applies to cancellations, and we define a
cancellation as aggressive whenever a large volume is cancelled. In this sense,
our approach can be seen as an extension of the study by Coppejans and Domowitz
(2002) who also focus on the arrival rate of trades, limit orders and cancellations.
However, they do not explicitly study high volume orders but consider all
incoming orders. Moreover, as they analyze the individual processes separately
using a generalized version of Engle and Russell’s (1998) (univariate) autoregressive
conditional duration (ACD) model, their framework does not allow for
any multivariate interdependencies between the individual processes.
In this setting, we state the following research questions: (1) Can we confirm
previous results regarding the determinants of order aggressiveness and traders’
order submission strategies when the multivariate dynamics of limit order books
are fully taken into account? (2) How strong are the (dynamic) interdependencies
between the individual processes and how important is it to account for the order
book dynamics? (3) After modelling the multivariate dynamics, what is the
additional explanatory power of order book variables? (4) Can we confirm
theoretical predictions regarding the impact of order book variables on traders’
order submission strategies?
Our analysis is based on order book data from the five most liquid stocks traded
on the Australian Stock Exchange (ASX) during the period July–August 2002. By
replicating the electronic trading at the ASX, we reconstruct the complete order
book at each instant of time. The order arrival intensities are modelled using a sixdimensional
version of the autoregressive conditional intensity (ACI) model
introduced by Russell (1999), where we include explanatory variables that capture
the current state of the order book as well as recent changes in the book.
It turns out that market depth, the queued volume, the bid-ask spread, recent
volatility, as well as recent changes in both the order flow and the price play an
important role in explaining the determinants of order aggressiveness. We show
that the impact of these variables is quite stable over a cross-section of stocks.
Moreover, these results hold irrespective of the specification of the model
dynamics. Confirming the results of Coppejans and Domowitz (2002) we also
observe that the arrival rates of market orders and limit orders can behave quite
differently in their dependence of the state of the order book. Therefore, a limit
order should not necessarily be considered simply as a less aggressive version of a
market order. This finding motivates modelling the individual processes in a
multivariate setting. Moreover, we find clear evidence for multivariate dynamics
and interdependencies between the individual processes.
It is also shown that the inclusion of order book variables clearly improves the
goodness-of-fit of the model. In addition, we demonstrate that a model that
3 For more details, see Sect. 4.3.