Non-average price impact in order-driven markets
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.
PDF AbstractTasks
Datasets
Add Datasets
introduced or used in this paper
Results from the Paper
Submit
results from this paper
to get state-of-the-art GitHub badges and help the
community compare results to other papers.
Methods
No methods listed for this paper. Add
relevant methods here
