Transform Analysis for Hawkes Processes with Applications in Dark Pool Trading
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AbstractHawkes processes are a class of simple point processes that are self-exciting and have a 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 nonnegative 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 analyse various performance metrics including time-to-first-fill, time-to-complete-fill and the expected fill rate of a resting dark order.
Acceptance Date01/11/2017
All Author(s) ListGao XF, Zhou X, Zhu LJ
Journal nameQuantitative Finance
Year2018
Volume Number18
Issue Number2
PublisherROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD
Pages265 - 282
ISSN1469-7688
eISSN1469-7696
LanguagesEnglish-United Kingdom
KeywordsHawkes processes,Transform analysis,Dark pool trading
Web of Science Subject CategoriesBusiness, Finance;Economics;Mathematics, Interdisciplinary Applications;Social Sciences, Mathematical Methods;Business & Economics;Mathematics;Mathematical Methods In Social Sciences