Swissquote Conference 2018 on Machine Learning in Finance

REGISTRATION Participation is free but places at the conference are limited.

Friday, November 9, 2018

Machine learning has come to play a prominent role in modern finance. Current applications range from text-based analysis of business reports to deep learning for credit risk and portfolio management. But the noise and behavioral elements inherent in financial data often require nonstandard machine learning solutions, possibly yet to be developed. The full potential of machine learning in finance is still to be explored.

The 9th annual Swissquote Conference will feature current research and insights on machine learning in finance provided by leading experts and scholars in the field. The event addresses academics and practitioners alike, and shall foster the interaction among individuals and across institutions

Speakers and program :

08:30 – 09:10 Registration and welcome coffee
09:10 – 09:25 Welcome address
09:25 – 10:00 Rama Cont, University of Oxford
10:00 – 10:35 Artur Sepp, Julius Baer
Applications of machine learning for volatility estimation and quantitative strategies
10:35 – 11:05 Coffee Break
11:05 – 11:40 Hans Buehler, JP Morgan
Deep Hedging
11:40 – 12:15 Kay Giesecke, Stanford University
Toward Explainable AI: Significance Tests for Neural Network
12:15 – 13:45 Lunch break
13:45 – 14:20 Gerard Hoberg, USC Marshall
Text-Based Representation of Industry Structure and Firm Innovation
14:20 – 14:50 Coffee Break
14:50 – 15:25 Isabelle Flückiger, Accenture
How Natural Language Processing (NLP) is Transforming Finance
15:25 – 16:00 David L. Shrier, University of Oxford
The Ethics of AI

Venue: SwissTech Convention Center, Ecole Polytechnique Fédérale de Lausanne (EPFL), Switzerland


The conference is organized by the Swissquote Chair in Quantitative FinanceAlexander Lipton, and the Swiss Finance Institute@EPFL and is sponsored by:

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