Machine Learning in Finance

Online Seminar Series
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Date
Friday 2 Feb 2024, 16:00 - 17:00
Type
Online event
Location

Online

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We are excited to announce the Call for Papers for our upcoming “Machine Learning in Finance” online seminar series, a virtual event dedicated to bringing together researchers at the intersection of Machine Learning and Finance. 

The ML in Finance seminar series is designed to create a collaborative platform for the exchange of insights and findings within the field. We aim to foster a friendly atmosphere that encourages constructive feedback, providing an opportunity for both junior and senior researchers to share their work.

Submit research paper

Submit original research papers in the following topics, but not limited to:

  • Asset Pricing
  • Big Data
  • Forecasting with Machine Learning
  • Macro Finance
  • Option Pricing

Submit your paper

One file only.
10 MB limit.
Allowed types: pdf.

 
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Registration

The seminar will start 16:00 - 17:00 CET. Monthly zoom webinars, please register via Zoom.

Organisers

See also

Unearthing Financial Statement Fraud: Insights from News Coverage Analysis

Jianqing Fan, Princeton University
Jianqing Fan smiling at the camera

Extending the Scope of Inference About Predictive Ability to Machine Learning Methods

Juan Carlos Escanciano (Universidad Carlos III de Madrid)
Polak Building and autumn trees

Beyond Arbitrage: Deviations from Risk-Return

Benjamin Holcblat, (University of Luxembourg)

On changepoint detection in functional data using empirical energy distance

Lorenzo Trapani, (University of Leicester)

Saddlepoint techniques for the statistical analysis of time series

Davide La Vecchia (University of Geneva)
Spring in Rotterdam

The Anatomy of Machine Learning-Based Portfolio Performance

Christian Montes Schutte, Aarhus University
Christian Montes Schutte smiling at the camera
More information

The seminar will start 16:00 - 17:00 CET.

Newsletter:
To receive updates about these events, join our mailing list by sending an email to fineml@ese.eur.nl

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