Economics at your fingertips  

A multidimensional Hilbert transform approach for barrier option pricing and survival probability calculation

Jie Chen (), Liaoyuan Fan (), Lingfei Li () and Gongqiu Zhang ()
Additional contact information
Jie Chen: The Chinese University of Hong Kong
Liaoyuan Fan: JP Morgan Quantitative Research China
Lingfei Li: The Chinese University of Hong Kong
Gongqiu Zhang: The Chinese University of Hong Kong

Review of Derivatives Research, 2022, vol. 25, issue 2, No 4, 189-232

Abstract: Abstract This paper proposes a multidimensional Hilbert transform approach for pricing discretely monitored multi-asset barrier options and computing joint survival probability in multivariate exponential Lévy asset price models. We generalize the univariate Hilbert transform method of Feng and Linetsky (Math Financ 18(3), 337–384, 2008) for single-asset barrier options and the well-known Sinc approximation theory of Stenger (Numerical methods based on sinc and analytic functions. Springer, New York, 1993) for computing the one-dimensional Hilbert transform to any dimension. We prove that, for Lévy processes with joint characteristic functions having an exponentially decaying tail, the error of our method decays exponentially in some power of the number of terms used in the expansion for each dimension. Numerical experiments demonstrate the efficiency of our method in the two-dimensional and three-dimensional problems for some popular multivariate Lévy models.

Keywords: Hilbert transform; Sinc approximation; Lévy processes; Barrier options; Survival probability; 44A15; 65R10; 60G51 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link) Abstract (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:

Ordering information: This journal article can be ordered from
http://www.springer. ... 29/journal/11147/PS2

DOI: 10.1007/s11147-022-09186-y

Access Statistics for this article

Review of Derivatives Research is currently edited by Gurdip Bakshi and Dilip Madan

More articles in Review of Derivatives Research from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

Page updated 2022-07-30
Handle: RePEc:kap:revdev:v:25:y:2022:i:2:d:10.1007_s11147-022-09186-y