NN de-Americanization: an efficient method to facilitate calibration of American-style options

Peter Pommergård Lind and Jim Gatheral

Quantitative Finance, 2025, vol. 25, issue 1, 1-16

Abstract: Neural network (NN) de-Americanization produces fast and accurate pseudo-European option prices from listed American option prices, facilitating the calibration of derivative models. The industry approach binomial de-Americanization takes a flat volatility surface as input for each strike and expiration. In contrast, the NN de-Americanization method takes the detailed shape of the volatility surface as an input; this is critical for accurately evaluating the early exercise premium (EEP) when interest rates are not close to zero.

Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/14697688.2024.2432511 (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:25:y:2025:i:1:p:1-16

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RQUF20

DOI: 10.1080/14697688.2024.2432511

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 ().