26 citations · 157 across the 57 of their papers we have counts for
73 papers
Uncertainty and Explainability in Deep Rough Volatility: A Neural Information-Theoretic Posterior Approach
Damiano Brigo, Raphaël Huser, Dan Leonte
Deep learning has substantially accelerated the calibration of complex stochastic-volatility models, but neural point calibration alone does not capture the uncertainty remaining a…
Exact calibration of structural models via time-change
Frédéric Vrins, Damiano Brigo
In this note, we propose a general structural approach to model a default time as the first-passage time (FPT) of a (``firm-value'') process below a (``debt'') barrier …
Local Stochastic Rough Volatility: Pathwise Filtering and the Conditional Density Equation
Damiano Brigo, Vladimir Lucic
This article studies the conditional-density equation and its pathwise transformation in local stochastic rough volatility models, with rough Heston (rHeston) as the main explicit…
On the boundaries, asymptotic law and Bernoulli-Doob representation of homogeneous bounded martingales
Damiano Brigo, Frédéric Vrins
We study homogeneous diffusion martingales evolving in a bounded state space , where and are zeros of the diffusion coefficient. We call a process of the form $Z_t…
Deep learning interpretability for rough volatility
Bo Yuan, Damiano Brigo, Antoine Jacquier +1
Deep learning methods have become a widespread toolbox for pricing and calibration of financial models. While they often provide new directions and research results, their `black b…
Optimal Projection Filters
Damiano Brigo
We present the two new notions of projection of a stochastic differential equation (SDE) onto a submanifold, as developed in Armstrong, Brigo e Rossi Ferrucci (2019, 2018): the Ito…