Economics at your fingertips  

A switching self-exciting jump diffusion process for stock prices

Donatien Hainaut () and Franck Moraux ()
Additional contact information
Donatien Hainaut: UCL - Université Catholique de Louvain

Post-Print from HAL

Abstract: This study proposes a new Markov switching process with clustering eects. In this approach, a hidden Markov chain with a nite number of states modulates the parameters of a self-excited jump process combined to a geometric Brownian motion. Each regime corresponds to a particular economic cycle determining the expected return, the diusion coecient and the long-run frequency of clustered jumps. We study rst the theoretical properties of this process and we propose a sequential Monte-Carlo method to lter the hidden state variables. We next develop a Markov Chain Monte-Carlo procedure to t the model to the S&P 500. Finally, we analyse the impact of such a jump clustering on implied volatilities of European options.

Keywords: self-excited jumps; Hawkes process; switching regime; Jump diffusion process (search for similar items in EconPapers)
Date: 2019-06
New Economics Papers: this item is included in nep-cmp and nep-ets
Note: View the original document on HAL open archive server:
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5) Track citations by RSS feed

Published in Annals of Finance, Springer Verlag, 2019, 15 (2), pp.267-306. ⟨10.1007/s10436-018-0340-5⟩

Downloads: (external link) (application/pdf)

Related works:
Journal Article: A switching self-exciting jump diffusion process for stock prices (2019) Downloads
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:

DOI: 10.1007/s10436-018-0340-5

Access Statistics for this paper

More papers in Post-Print from HAL
Bibliographic data for series maintained by CCSD ().

Page updated 2020-11-11
Handle: RePEc:hal:journl:halshs-01909772