High-frequency financial data modeling using Hawkes processes

By V. Chavez‐Demoulin, J. A. McGill. 2012

168 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Pricing Vulnerable Options with Jump Clustering (2017, methodology): “Owing to the clustering of jumps, self-exciting Hawkes processes can be used to model the phenomenon of volatility clustering (Chavez-Demoulin & McGill, 2012).”
Hawkes processes and their applications to finance: a review (2018, methodology): “(2014) considered self-exciting Hawkes process role in a process exceeding above some threshold using POT, in the fashion of Chavez-Demoulin et al. (2005), Chavez-Demoulin and McGill (2012) and McNeil et al.”
Hawkes Processes in Finance (2015, methodology): “[18], ChavezDemoulin and Mc Gill constructed a model for the excessses of an asset price above a given threshold.”
Statistics and Quantitative Risk Management for Banking and Insurance (2014, methodology): “Estimation based on self-exciting (or Hawkes) processes is exemplified in Chavez-Demoulin and McGill (2012). For an early use on Hawkes processes in finance, see ChavezDemoulin et al. (2005). McNeil et al. (2005, Section 7.4.3) contains an early text-book reference to QRM. Extreme Value Theory (EVT)”