3 citations · 3 across the 4 of their papers we have counts for
7 papers
Risk Measures under Paired-Ambiguity: A Deep Learning Reflected BSDE Framework
Nacira Agram, Jan Rems, Emanuela Rosazza Gianin
We study optimal stopping under dynamic risk measures with simultaneous ambiguity in the probability model and the discount rate. We introduce a paired ambiguity framework combinin…
NeSTR: Neural S-Transform Reconstruction for Gaussian SPDEs
Nacira Agram, Fred Espen Benth, Jan Rems
We introduce Neural -Transform Reconstruction (NeSTR) for Gaussian stochastic partial differential equations (SPDEs). The learned object is not the random solution itself, but i…
A cylindrical neural approximation theorem for conditional laws of McKean-Vlasov equations with common noise
Nacira Agram, Reda Hmioui, Jan Rems
We introduce conditional cylindrical neural networks for approximating functionals of conditional laws in McKean-Vlasov equations with common noise. Fourier moments of the initial…
A Deep Learning Approach to Renewable Capacity Installation under Jump Uncertainty
Nacira Agram, Fred Espen Benth, Giulia Pucci +1
We study a stochastic model for the installation of renewable energy capacity under demand uncertainty and jump driven dynamics. The system is governed by a multidimensional Ornste…
Deep Learning for Energy Market Contracts: Dynkin Game with Doubly RBSDEs
Nacira Agram, Ihsan Arharas, Giulia Pucci +1
We formulate a Contract for Difference (CfD) with early exit options as a two-player zero-sum Dynkin game, reflecting the strategic interaction between an electricity producer and…
SIG-BSDE for Dynamic Risk Measures
Nacira Agram, Jan Rems, Emanuela Rosazza Gianin
In this paper, we consider dynamic risk measures induced by backward stochastic differential equations (BSDEs). We discuss different examples that come up in the literature, includ…
Deep learning for quadratic hedging in incomplete jump market
Nacira Agram, Bernt Øksendal, Jan Rems
We propose a deep learning approach to study the minimal variance pricing and hedging problem in an incomplete jump diffusion market. It is based upon a rigorous stochastic calculu…