collaborators

7 papers

math.PR2026

Expected signatures via partial integration, coordinate change and symmetrization

Paul P. Hager, Luca Pelizzari

We study signature transformations of heterogeneous paths whose components may differ in regularity and probabilistic structure. We introduce an invertible change of coor…

stat.ML2026

The Volterra signature

Paul P. Hager, Fabian N. Harang, Luca Pelizzari +1

Modern approaches for learning from non-Markovian time series, such as recurrent neural networks, neural controlled differential equations or transformers, typically rely on implic…

math.NA2026

Computational aspects of the Volterra Signature

Paul P. Hager, Fabian N. Harang, Luca Pelizzari +1

The Volterra signature extends the classical path signature by incorporating general matrix-valued kernel into its iterated integral structure, yielding a flexible notion of memory…

stat.ML2025

Local regression on path spaces with signature metrics

Christian Bayer, Davit Gogolashvili, Luca Pelizzari

We study nonparametric regression and classification for path-valued data. We introduce a functional Nadaraya-Watson estimator that combines the signature transform from rough path…

q-fin.MF2025

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

Christian Bayer, Luca Pelizzari, Jia-Jie Zhu

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 a…

q-fin.MF2025

Rough PDEs for local stochastic volatility models

Peter Bank, Christian Bayer, Peter K. Friz +1

In this work, we introduce a novel pricing methodology in general, possibly non-Markovian local stochastic volatility (LSV) models. We observe that by conditioning the LSV dynamics…