5 citations · 9 across the 10 of their papers we have counts for
5 papers · 1 filter
Hedging under rough volatility
Masaaki Fukasawa, Blanka Horvath, Peter Tankov
In this chapter we first briefly review the existing approaches to hedging in rough volatility models. Next, we present a simple but general result which shows that in a one-factor…
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…
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…
Dirichlet Forms and Finite Element Methods for the SABR Model
Blanka Horvath, Oleg Reichmann
We propose a deterministic numerical method for pricing vanilla options under the SABR stochastic volatility model, based on a finite element discretization of the Kolmogorov prici…
Functional Analytic (Ir-)Regularity Properties of SABR-type Processes
Leif Doering, Blanka Horvath, Josef Teichmann
The SABR model is a benchmark stochastic volatility model in interest rate markets, which has received much attention in the past decade. Its popularity arose from a tractable asym…