Bibliographic Details
| Title: |
NN de-Americanization: an efficient method to facilitate calibration of American-style options. |
| Authors: |
Pommergård Lind, Peter1 (AUTHOR) pplinvest1@gmail.com, Gatheral, Jim2 (AUTHOR) |
| Source: |
Quantitative Finance. Jan2025, Vol. 25 Issue 1, p1-16. 16p. |
| Subject Terms: |
*Options (Finance), *Derivative securities, *Artificial neural networks, Statistical models |
| 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. [ABSTRACT FROM AUTHOR] |
|
Copyright of Quantitative Finance is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) |
| Database: |
Business Source Complete |
