Deep Learning Volatility - Blanka Horvath, Kings College London

Explore deep learning volatility in this 26-minute talk by Blanka Horvath from King's College London at the Alan Turing Institute. Delve into neural network approaches for option pricing and calibration, examining challenges, advantages, and perspectives. Learn about rough volatility, Monte Carlo pricing methods, and model recognition. Gain insights from Horvath's research in stochastic analysis and mathematical finance, drawing from her paper "Deep Learning Volatility" and her expertise in asymptotic and numerical methods for option pricing.

Intro
Deep Learning Option Pricing and Calibration
Challenges for Neural Network Pricing
A NN Perspective on Pricing and (€) Calibration
Advantages of Neural Network Pricing
Questions
Digression: Rough Volatility
Pricing rough volatility by Monte Carlo
Model recognition