4 papers
Rough volatility, path-dependent PDEs and weak rates of convergence
Ofelia Bonesini, Antoine Jacquier, Alexandre Pannier
In the setting of stochastic Volterra equations, and in particular rough volatility models, we show that conditional expectations are the unique classical solutions to path-depende…
Random neural networks for rough volatility
Antoine Jacquier, Zan Zuric
We construct a deep learning-based numerical algorithm to solve path-dependent partial differential equations arising in the context of rough volatility. Our approach is based on i…
On the large-time behaviour of affine Volterra processes
Antoine Jacquier, Alexandre Pannier, Konstantinos Spiliopoulos
We show the existence of a stationary measure for a class of multidimensional stochastic Volterra systems of affine type. These processes are in general not Markovian, a shortcomin…
Universal Approximation Theorem and error bounds for quantum neural networks and quantum reservoirs
Lukas Gonon, Antoine Jacquier
Universal approximation theorems are the foundations of classical neural networks, providing theoretical guarantees that the latter are able to approximate maps of interest. Recent…