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Transform Analysis for Hawkes Processes with Applications in Dark Pool Trading. (arXiv:1710.01452v1 [q-fin.TR])
来源于:arXiv
Hawkes processes are a class of simple point processes that are self-exciting
and have clustering effect, with wide applications in finance, social networks
and many other fields. This paper considers a self-exciting Hawkes process
where the baseline intensity is time-dependent, the exciting function is a
general function and the jump sizes of the intensity process are independent
and identically distributed non-negative random variables. This Hawkes model is
non-Markovian in general. We obtain closed-form formulas for the Laplace
transform, moments and the distribution of the Hawkes process. To illustrate
the applications of our results, we use the Hawkes process to model the
clustered arrival of trades in a dark pool and analyze various performance
metrics including time-to-first-fill, time-to-complete-fill and the expected
fill rate of a resting dark order. 查看全文>>