Importance sampling for jump processes and applications to finance
Laetitia Badouraly Kassim,
Jérôme Lelong () and
Imane Loumrhari
Additional contact information
Laetitia Badouraly Kassim: SAM - Statistique Apprentissage Machine - LJK - Laboratoire Jean Kuntzmann - UPMF - Université Pierre Mendès France - Grenoble 2 - UJF - Université Joseph Fourier - Grenoble 1 - Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology - CNRS - Centre National de la Recherche Scientifique
Jérôme Lelong: SAM - Statistique Apprentissage Machine - LJK - Laboratoire Jean Kuntzmann - UPMF - Université Pierre Mendès France - Grenoble 2 - UJF - Université Joseph Fourier - Grenoble 1 - Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology - CNRS - Centre National de la Recherche Scientifique
Imane Loumrhari: SAM - Statistique Apprentissage Machine - LJK - Laboratoire Jean Kuntzmann - UPMF - Université Pierre Mendès France - Grenoble 2 - UJF - Université Joseph Fourier - Grenoble 1 - Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology - CNRS - Centre National de la Recherche Scientifique
Post-Print from HAL
Abstract:
Adaptive importance sampling techniques are widely known for the Gaussian setting of Brownian driven diffusions. In this work, we want to extend them to jump processes. Our approach relies on a change of the jump intensity combined with the standard exponential tilting for the Brownian motion. The free parameters of our framework are optimized using sample average approximation techniques. We illustrate the efficiency of our method on the valuation of financial derivatives in several jump models.
Keywords: adaptive Monte Carlo methods.; sample average approximation; Importance sampling; adaptive Monte Carlo methods (search for similar items in EconPapers)
Date: 2015-12
Note: View the original document on HAL open archive server: https://hal.science/hal-00842362v1
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)
Published in The Journal of Computational Finance, 2015, 19 (2), pp.109-139. ⟨10.21314/JCF.2015.292⟩
Downloads: (external link)
https://hal.science/hal-00842362v1/document (application/pdf)
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:hal:journl:hal-00842362
DOI: 10.21314/JCF.2015.292
Access Statistics for this paper
More papers in Post-Print from HAL
Bibliographic data for series maintained by CCSD ().