Pricing American options under rough volatility using deep-signatures and signature-kernels

2025/01/12 by Bayer, Christian, Pelizzari, Luca, Zhu, Jia-Jie · 7 citations
#60G40 #60L10 #91G20 #91G60 #FOS: Economics and business #Mathematical Finance (q-fin.MF)

paper · doi:10.48550/arxiv.2501.06758

Abstract

We extend the signature-based primal and dual solutions to the optimal stopping problem recently introduced in [Bayer et al.: Primal and dual optimal stopping with signatures, to appear in Finance & Stochastics 2025], by integrating deep-signature and signature-kernel learning methodologies. These approaches are designed for non-Markovian frameworks, in particular enabling the pricing of American options under rough volatility. We demonstrate and compare the performance within the popular rough Heston and rough Bergomi models.

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