3 citations · 4 across the 4 of their papers we have counts for
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q-fin.MF2019★ 3 cited
From microscopic price dynamics to multidimensional rough volatility models
Mehdi Tomas, Mathieu Rosenbaum
Rough volatility is a well-established statistical stylised fact of financial assets. This property has lead to the design and analysis of various new rough stochastic volatility m…
q-fin.MF2019★ 1 cited
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…
q-fin.MF2019
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…