A slightly depressing jump model: intraday volatility pattern simulation
Khaldoun Khashanah,
Jing Chen and
Alan Hawkes
Quantitative Finance, 2018, vol. 18, issue 2, 213-224
Abstract:
Hawkes processes have been finding more applications in diverse areas of science, engineering and quantitative finance. In multi-frequency finance various phenomena have been observed, such as shocks, crashes, volatility clustering, turbulent flows and contagion. Hawkes processes have been proposed to model those challenging phenomena appearing across asset prices in various exchanges. The original Hawkes process is an intensity-based model for series of events with path dependence and self-exciting or mutual-exciting mechanisms. This paper introduces a slightly depressing process to model the reverse phenomenon of self-exciting mechanisms. Such a process models the decline in the intensity of jumps observed in market regimes. The proposed birth-immigration-death process captures the decline in jump intensity observed at the start of a daily trading regime while the classical immigration-birth process models an increase in jump intensity towards the close of daily trading. Each of these processes can be expressed as a special case of a simple bivariate Hawkes process.
Date: 2018
References: Add references at CitEc
Citations: View citations in EconPapers (2)
Downloads: (external link)
http://hdl.handle.net/10.1080/14697688.2017.1403139 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:quantf:v:18:y:2018:i:2:p:213-224
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RQUF20
DOI: 10.1080/14697688.2017.1403139
Access Statistics for this article
Quantitative Finance is currently edited by Michael Dempster and Jim Gatheral
More articles in Quantitative Finance from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().