Machine learning methods for American-style path-dependent contracts

Speaker:  Andrea Pallavicini - Intesa San Paolo
  Thursday, October 17, 2024 at 12:00 PM

In the present work, we introduce and compare state-of-the-art algorithms, that are now classified under the name of machine learning, to price Asian and look-back products with early-termination features. These include randomized feed-forward neural networks, randomized recurrent neural networks, and a novel method based on signatures of the underlying price process. Additionally, we explore potential applications on callable certificates. Furthermore, we present an innovative approach for calculating sensitivities, specifically Delta and Gamma, leveraging Chebyshev interpolation techniques.


Programme Director
Alessandro Gnoatto

External reference
Publication date
July 26, 2024

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