5 citations · 8 across the 5 of their papers we have counts for
4 papers · 1 filter
Not so Particular about Calibration: Smile Problem Resolved
Aitor Muguruza
We present a novel Monte Carlo based LSV calibration algorithm that applies to all stochastic volatility models, including the non-Markovian rough volatility family. Our framework…
On deep calibration of (rough) stochastic volatility models
Christian Bayer, Blanka Horvath, Aitor Muguruza +2
Techniques from deep learning play a more and more important role for the important task of calibration of financial models. The pioneering paper by Hernandez [Risk, 2017] was a ca…
Asymptotics for volatility derivatives in multi-factor rough volatility models
Chloe Lacombe, Aitor Muguruza, Henry Stone
We present small-time implied volatility asymptotics for Realised Variance (RV) and VIX options for a number of (rough) stochastic volatility models via large deviations principle.…
Deep Learning Volatility
Blanka Horvath, Aitor Muguruza, Mehdi Tomas
We present a neural network based calibration method that performs the calibration task within a few milliseconds for the full implied volatility surface. The framework is consiste…