Mon, 13 Nov 2023

We kick off QuantMinds International with our summit day. Today, the Quant Invest Summit, the Fundamentals of Machine Learning in Finance and the Latest in Volatility Modelling workshop return. Brand new for this year, we introduce the LLMs and Advanced ML Summit, plus the Hackathon focussing on LLM use cases in quant finance.

Interactions in asset pricing

We propose a linearization of rule-based algorithms that reveals the most important interactions between characteristics and macroeconomic variables when explaining future stock returns. Our results suggest that the two types of predictors are intertwined, which implies that the relationships between returns and standard asset pricing characteristics are not only non-linear but also strongly dependent on the state of the economy. From an investment standpoint, our interpretable machine learning approach produces portfolios that outperform out-of-sample.

Stream: Quant Invest Summit

Time: 14:00

Speaker in the spotlight

Thomas Raffinot

Head of Quant Investment Signals, AXA Investment Managers

Thomas Raffinot is the Head of Quant Investment Signals at AXA-IM. He has 19 years of experience in the industry, both as a strategist and a data scientist (CPR AM, BNPP).

Thomas oversees AXA-IM internal quant platform, which aims at illustrating and analyzing complex market dynamics to improve the investment decision process. In his role at AXA-IM, he applies data and quantitative techniques to automate business processes including research, modeling, simulation and visualization.

Ethical Considerations of NLP in Finance

What are the impacts of LLMs on data privacy, fairness in competition, security, accountability, and transparency?

Stream: LLMs & Advanced ML Summit

Time: 09:40

Speaker under the spotlight:

Nicole Königstein

Chief Data Scientist and Head of AI & Quantitative Research, Wyden Capital

Nicole Königstein is a distinguished Data Scientist and Quantitative Researcher, currently working as Chief Data Scientist and Head of AI & Quantitative Research at Wyden Capital and as Head of AI and Quantitative Research at quantmate. Alongside her role in this organizations, she serves as an AI consultant across diverse industries, leading workshops, and guiding companies from the conceptual stages of AI implementation through to final deployment.

Introduction and unsupervised learning

Machine learning vs statistics
Different learning approaches and their applications
The use of training, validation, and test data sets
The variance-bias trade-off
The k-means algorithm and case study
Other unsupervised learning tools

Stream: Fundamentals of Machine Learning in Finance Workshop

Time: 09:00

Speaker in the spotlight:

John Hull

Maple Financial Professor of Derivatives & Risk Management at Joseph L. Rotman School of Management, University Of Toronto

John Hull is an internationally recognized authority on derivatives and risk management and has many publications in this area. His work has an applied focus. In 1999 he was voted Financial Engineer of the Year by the International Association of Financial Engineers. He has acted as consultant to many North American, Japanese, and European financial institutions. He has won many teaching awards, including University of Toronto’s prestigious Northrop Frye award.

Calibration of volatility models

The particle method for smile calibration
Calibration of multi-asset volatility models: local volatility/correlation, cross-dependent volatility/correlation
Joint S&P 500/VIX smile calibration
The term-structure of the equity at-the-money skew

Stream: Latest in Volatility Modelling Workshop

Time: 15:50

Speaker under the spotlight:

Julien Guyon

Professor of Applied Mathematics, École des Ponts ParisTech

Julien Guyon is a professor of Applied Mathematics at Ecole des Ponts ParisTech, one of the oldest and one of the most prestigious French Grandes Ecoles, where he holds the BNP Paribas Chair Futures of Quantitative Finance. Before joining Ecole des Ponts, Julien worked in the financial industry for 16 years, first in the Global Markets Quantitative Research team at Societe Generale in Paris (2006-2012), then as a senior quantitative analyst in the Quantitative Research group at Bloomberg L.P., New York (2012-2022). Julien was also an adjunct professor in the Department of Mathematics at Columbia University and at the Courant Institute of Mathematical Sciences, NYU, from 2015 to 2022; and previously at Universite Paris Diderot and Ecole des Ponts ParisTech. Julien serves as an Associate Editor of Finance & Stochastics, Quantitative Finance, SIAM Journal on Financial Mathematics, and Journal of Dynamics and Games. He is also a Louis Bachelier Fellow.

QuantMinds Hackathon

in partnership with CompatibL

Stream: QuantMinds Hackathon

Time: 09:00

Speaker under the spotlight:

Alexander Sokol

Executive Chairman, CompatibL

Alexander Sokol is the founder, Executive Chairman, and Head of Quant Research at CompatibL, a trading and risk technology company. He is also the co-founder of Numerix, where he served as CTO from 1996 to 2003, and the co-founder of Duality Group, where he served as CTO from 2017 to 2020.