  The extent to which a matching engine can cloud the modelling of underlying
order submission and management processes in a financial market remains an
unanswered concern with regards to market models. Here we consider a 10-variate
Hawkes process with simple rules to simulate common order types which are
submitted to a matching engine. Hawkes processes can be used to model the time
and order of events, and how these events relate to each other. However, they
provide a freedom with regards to implementation mechanics relating to the
prices and volumes of injected orders. This allows us to consider a reference
Hawkes model and two additional models which have rules that change the
behaviour of limit orders. The resulting trade and quote data from the
simulations are then calibrated and compared with the original order generating
process to determine the extent with which implementation rules can distort
model parameters. Evidence from validation and hypothesis tests suggest that
the true model specification can be significantly distorted by market
mechanics, and that practical considerations not directly due to model
specification can be important with regards to model identification within an
inherently asynchronous trading environment.
