We invite submissions to the 9th MIDAS Workshop on MIning DAta for financial applicationS, to be held in conjunction with ECML-PKDD 2024 - European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases.

Like the famous King Midas, popularly remembered in Greek mythology for his ability to turn everything he touched with his hand into gold, we believe that the wealth of data generated by modern technologies, with widespread presence of computers, users and media connected by Internet, is a goldmine for tackling a variety of problems in the financial domain.

The MIDAS workshop is aimed at discussing challenges, potentialities, and applications of leveraging data-mining tasks to tackle problems in the financial domain. The workshop provides a premier forum for sharing findings, knowledge, insights, experience and lessons learned from mining data generated in various application domains. The intrinsic interdisciplinary nature of the workshop constitutes an invaluable opportunity to promote interaction between computer scientists, physicists, mathematicians, economists and financial analysts, thus paving the way for an exciting and stimulating environment involving researchers and practitioners from different areas.

PAST EDITIONS

MIDAS 2023

TOPICS OF INTEREST

We encourage submission of papers on the area of data mining for financial applications. Topics of interest include, but are not limited to:

- trading models
- discovering market trends
- predictive analytics for financial services
- network analytics in finance
- planning investment strategies
- portfolio management
- understanding and managing financial risk
- customer/investor profiling
- identifying expert investors
- financial modeling
- anomaly detection in financial data
- fraud detection
- anti-money laundering
- discovering patterns and correlations in financial data
- text mining and NLP for financial applications
- sentiment and opinion analysis for finance
- financial network analysis
- financial time series analysis
- pitfalls identification
- financial knowledge graphs
- learning paradigms in the financial domain
- explainable AI in financial services
- fairness in financial data mining
- quantum computing for finance
- generative models for synthetic data
- large language models in finance

WORKSHOP FORMAT

The ECML-PKDD 2024 conference is full in presence as only in-person attendances are allowed. More in concrete, this means that at least one author of each paper accepted for presentation at MIDAS must have a full conference registration and present the paper in person. Papers without a full registration or in-presence presentation won't be included in the post-workshop Springer proceedings.

INVITED SPEAKERS

Aurelie BEAUGEARD, BNP Paribas - "How to ease adoption of AI with Explainable AI to help reduce risk exposure in the banking sector?"

ACCEPTED PAPERS

T. B. D.

PROGRAM

Every paper is assigned a slot of 15 minutes for presentation + 3-5 minutes of Q/A

9:00 - 9:10: OPENING

9:10 - 10:00: INVITED TALK
Aurelie BEAUGEARD, BNP Paribas - "How to ease adoption of AI with Explainable AI to help reduce risk exposure in the banking sector?"

10:00 - 11:00: PAPER PRESENTATION SESSION I (3 papers)
PAPER 1: Joao B. G. de Brito (Federal University of Rio Grande do Sul); Rodrigo Heldt (Federal University of Rio Grande do Sul ); Cleo Silveira (Federal University of Rio Grande do Sul ); Matthias Bogaert (Ghent University); Guilherme Bucco (Federal University of Rio Grande do Sul ); Fernando Luce (Federal University of Rio Grande do Sul ); Joao Becker (Federal University of Rio Grande do Sul); Filipe Zabala (Federal University of Rio Grande do Sul); Michel Anzanello (Federal University of Rio Grande do Sul) Snoeck - "Predicting and Explaining Customer Data Sharing in the Open Banking"
PAPER 2: Baptiste Lefort (CentraleSupélec, Paris-Saclay University, Ai For Alpha); Eric Benhamou (AI For Alpha); David Saltiel (A.I. For Alpha); Jean Jacques Ohana (Ai For Alpha); Beatrice Guez (Ai For Alpha) – "Optimizing Performance: How Compact Models Match or Exceed GPT’s Classification Capabilities through Fine-Tuning"

PAPER 3: Xinlin Wang (University of Luxembourg); Mats Brorsson (University of Luxembourg) - "Which company adjustment matter? Insights from Uplift Modeling on Financial Health"

11:00 - 11:20: COFFEE BREAK

11:20 - 12:20: PAPER PRESENTATION SESSION II (3 papers)
PAPER 4: Baptiste Lefort (CentraleSupélec, Paris-Saclay University, Ai For Alpha); Eric Benhamou (AI For Alpha); David Saltiel (A.I. For Alpha); Jean Jacques Ohana (Ai For Alpha); Beatrice Guez (Ai For Alpha); Thomas Jacquot ( Ai For Alpha) – "Stress index strategy enhanced with financial news sentiment analysis for the equity markets"
INVITED PAPER: Aivaras Bielskis – "Advanced Machine Learning Techniques for Investment Forecasting: An Integrated Approach"
INVITED PAPER: Malte Lehna - "A Reinforcement Learning approach for the continuous electricity market of Germany: Trading from the perspective of a wind park operator""

12:20 - 12:30: CONCLUDING REMARKS