31 citations · 152 across the 38 of their papers we have counts for
5 papers · 1 filter
Arbitrage-Aware Probabilistic Multi-Step Forecasting of Implied Volatility Surfaces: Joint Generation of Surface-Return Trajectories Using Latent Diffusion
Dominik Manuel Buchegger, Lukas Gonon
Implied volatility surfaces summarise the option market and are central to many financial applications. Probabilistic forecasting of their future evolution requires modelling two-d…
Approximation Rates for Deep Calibration of (Rough) Stochastic Volatility Models
Francesca Biagini, Lukas Gonon, Niklas Walter
We derive quantitative error bounds for deep neural networks (DNNs) approximating option prices on a -dimensional risky asset as functions of the underlying model parameters, pa…
Detecting asset price bubbles using deep learning
Francesca Biagini, Lukas Gonon, Andrea Mazzon +1
In this paper we employ deep learning techniques to detect financial asset bubbles by using observed call option prices. The proposed algorithm is widely applicable and model-indep…
Neural network approximation for superhedging prices
Francesca Biagini, Lukas Gonon, Thomas Reitsam
This article examines neural network-based approximations for the superhedging price process of a contingent claim in a discrete time market model. First we prove that the -quan…
Asset Pricing with General Transaction Costs: Theory and Numerics
Lukas Gonon, Johannes Muhle-Karbe, Xiaofei Shi
We study risk-sharing equilibria with general convex costs on the agents' trading rates. For an infinite-horizon model with linear state dynamics and exogenous volatilities, we pro…