  A point process model for order flows in limit order books is proposed, in
which the conditional intensity is the product of a Hawkes component and a
state-dependent factor. In the LOB context, state observations may include the
observed imbalance or the observed spread. Full technical details for the
computationally-efficient estimation of such a process are provided, using
either direct likelihood maximization or EM-type estimation. Applications
include models for bid and ask market orders, or for upwards and downwards
price movements. Empirical results on multiple stocks traded in Euronext Paris
underline the benefits of state-dependent formulations for LOB modeling, e.g.
in terms of goodness-of-fit to financial data.
