Modeling the Dynamics of the Entire Implied Volatility Surface with Deep Learning

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Modeling the Dynamics of the Entire Implied Volatility Surface with Deep Learning

Arthur Böök discusses deep learning advances in modeling implied volatility surfaces.

Wednesday 21 September 2022

0:00 / 0:00

Podcast Description

QuantSpeak podcast, Dan Tudball is joined by Derivatives Structurer, Arthur Böök. Arthur will be discussing his early career beginnings, his recent paper with Daniel Bloch, ‘Smiling in Action’, and the exciting advancements happening in machine learning.

Topics & Timestamps

[00:00 - 01:01] Guest Intro: Arthur Book & Research Overview

[01:01 - 01:49] Arthur’s Academic Path & Interest in Probability

[01:49 - 03:21] University Experience & Early Research

[03:21 - 05:08] Industry Entry & Machine Learning Emergence

[05:08 - 09:19] Early ML Projects, Adoption, and Model Challenges

[09:19 - 12:17] Options Data: Value, Noise, and Use in Trading

[12:17 - 16:06] Data Cleaning, Market Making, & Rough Volatility

[16:06 - 18:23] Collaboration with Daniel Bloch

[18:23 - 24:34] Reinforcement Learning & Surface Modeling Methods

[24:34 - 26:12] Crypto Volatility & ML Applications

[26:12 - 30:31] Key Takeaways, Opportunities, and Volatility Insights

[30:31 - 34:43] ML for Sentiment, News, and Final Thoughts.

Disclaimer

Podcasts are for informational purposes only and provided “as is” without any representation or warranty from Fitch Learning of any kind. Comments or statements expressed by speakers may not be those of the Fitch Learning. Fitch Learning is not providing advice or recommendations. Fitch Learning, its directors, officers, or employees do not accept any liability for any loss arising from the use of information.