  We present a measurement of price impact in order-driven markets that does
not require averages across executions or scenarios. Given the order book data
associated with one single execution of a sell metaorder, we measure its
contribution to price decrease during the trade. We do so by modelling the
limit order book using state-dependent Hawkes processes, and by defining the
price impact profile of the execution as a function of the compensator of a
stochastic process in our model. We apply our measurement to a data set from
NASDAQ, and we conclude that the clustering of sell child orders has a bigger
impact on price than their sizes.
