No-Arbitrage Interpolation of the Option Price Function and Its Reformulation
Y. Wang,
H. Yin and
L. Qi
Additional contact information
Y. Wang: Peking University
H. Yin: Chinese Academy of Sciences
L. Qi: Hong Kong Polytechnic University
Journal of Optimization Theory and Applications, 2004, vol. 120, issue 3, No 8, 627-649
Abstract:
Abstract Several risk management and exotic option pricing models have been proposed in the literature which may price European options correctly. A prerequisite of these models is the interpolation of the market implied volatilities or the European option price function. However, the no-arbitrage principle places shape restrictions on the option price function. In this paper, an interpolation method is developed to preserve the shape of the option price function. The interpolation is optimal in terms of minimizing the distance between the implied risk-neutral density and the prior approximation function in L 2-norm, which is important when only a few observations are available. We reformulate the problem into a system of semismooth equations so that it can be solved efficiently.
Keywords: Option price functions; no-arbitrage principle; interpolation; semismooth equations; superlinear convergence (search for similar items in EconPapers)
Date: 2004
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)
Downloads: (external link)
http://link.springer.com/10.1023/B:JOTA.0000025713.44548.71 Abstract (text/html)
Access to the full text of the articles in this series is restricted.
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:spr:joptap:v:120:y:2004:i:3:d:10.1023_b:jota.0000025713.44548.71
Ordering information: This journal article can be ordered from
http://www.springer. ... cs/journal/10957/PS2
DOI: 10.1023/B:JOTA.0000025713.44548.71
Access Statistics for this article
Journal of Optimization Theory and Applications is currently edited by Franco Giannessi and David G. Hull
More articles in Journal of Optimization Theory and Applications from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().