6th Workshop on MIning DAta for financial applicationS

Event Dates

Sep 13, 2021 - Sep 17, 2021

Location

Bilbao

Submission Deadline

Jun 25, 2021

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MIDAS 2021 – The Sixth Workshop on MIning DAta for financial applicationS

September 13 or 17, 2021 – VIRTUAL

http://midas.portici.enea.it

in conjunction with

ECML-PKDD 2021 – The European Conference on

Machine Learning and Principles and Practice of Knowledge Discovery in Databases

September 13-17, 2021 – VIRTUAL

https://2021.ecmlpkdd.org/

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COVID-19 PLAN

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Originally planned to take place in Bilbao, Spain, the COVID-19 pandemic made

the ECML-PKDD 2021 conference and all its satellite events — including MIDAS 2021 —

switch to an ONLINE format.

OVERVIEW

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We invite submissions to the 6th MIDAS Workshop on MIning DAta for financial applicationS,

to be held in conjunction with ECML-PKDD 2021 – 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.

Nowadays, people’s interactions with technological systems provide us with gargantuan amounts

of data documenting collective behaviour in a previously unimaginable fashion.

Recent research has shown that by properly modeling and analyzing these massive datasets, or

instance representing them as network structures it is possible to gain useful insights into

the evolution of the systems considered (i.e., trading, disease spreading, political elections).

Investigating the impact of data arising from today’s application domains on financial decisions

may be of paramount importance. Knowledge extracted from data can help gather critical information

for trading decisions, reveal early signs of impactful events (such as stock market moves), or

anticipate catastrophic events (e.g., financial crises) that result from a combination of actions,

and affect humans worldwide.

The importance of data-mining tasks in the financial domain has been long recognized.

Core application scenarios include correlating Web-search data with financial decisions,

forecasting stock market, predicting bank bankruptcies, understanding and managing financial risk,

trading futures, credit rating, loan management, bank customer profiling.

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.

TOPICS OF INTEREST

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We encourage submission of papers on the area of data mining for financial applications.

Topics of interest include, but are not limited to:

– Forecasting the stock market

– 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

– Measures of success in forecasting

– Anomaly detection in financial data

– Fraud detection

– Data-driven anti money laundering

– Discovering patterns and correlations in financial data

– Text mining and NLP for financial applications

– Financial network analysis

– Time series analysis

– Pitfalls identification

– Financial knowledge graphs

– Reinforcement learning in the financial domain

– Explainable AI in financial services

SUBMISSION GUIDELINES

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We invite submissions of either regular papers (long or short), and extended abstracts:

– Long regular papers: up to 15 pages long (in the Springer LNCS style,

https://www.springer.com/computer/lncs?SGWID=0-164-6-793341-0), reporting on novel,

unpublished work that might not be mature enough for a conference or journal submission.

– Short regular papers: up to 8 pages long, presenting work-in-progress.

– Extended abstracts: up to 4 pages long, referring to recently published work on

the workshop topics, position papers, late-breaking results, or emerging research problems.

All page limits are intended *excluding references*, whuch may take as many additional pages as preferred.

Contributions should be submitted in PDF format, electronically, using the workshop

submission site at https://easychair.org/conferences/?conf=midas2021.

Papers must be written in English and formatted according to the ECML-PKDD 2021

submission guidelines available at https://2021.ecmlpkdd.org/?page_id=1599.

Submitted papers will be peer-reviewed and selected on the basis of these reviews.

*If accepted, at least one of the authors must attend the workshop to present the work*.

PROCEEDINGS

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Accepted papers will be part of the ECML-PKDD 2021 workshop post-proceedings,

which will be published as a Springer LNCS volume.

The proceedings of the past three editions of the workshop are available here:

– 2020: https://www.springer.com/978-3-030-66980-5

– 2019: https://link.springer.com/book/10.1007/978-3-030-37720-5

– 2018: https://link.springer.com/book/10.1007%2F978-3-030-13463-1

IMPORTANT DATES (tentative)

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Submission deadline: June 25, 2021

Acceptance notification (tentative): July 19, 2021

Early registration: second half of July, 2021

Camera-ready deadline (tentative): July 26, 2020

Workshop date: September 13 or 17, 2021

INVITED SPEAKERS

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TBA

PROGRAM COMMITTEE

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Aris Anagnostopoulos, Sapienza University

Annalisa Appice, University of Bari

Argimiro Arratia, Universitat Politècnica de Catalunya

Davide Azzalini, Politecnico of Milan

Fabio Azzalini, Politecnico of Milan

Antonia Azzini, C2T

Xiao Bai, Yahoo Research

Andre Baier, Fraunhofer IEE

Luca Barbaglia, JRC – European Commission

Luigi Bellomarini, Banca d’Italia

Ludovico Boratto, Eurecat

Cristian Bravo, Western University

Douglas Burdick, IBM Research

Matteo Catena, SpazioDati

Jeremy Charlier, National Bank of Canada

Sergio Consoli, JRC – European Commission

Carlotta Domeniconi, George Mason University

Wouter Duivesteijn, Eindhoven University of Technology

Edoardo Galimberti, Inpendent Researcher

Cuneyt Gurcan Akcora, University of Manitoba

Roberto Interdonato, CIRAD

Anna Krause, University of Wurzburg

Rajasekar Krishnamurthy, IBM Almaden

Malte Lehna, Fraunhofer IEE

Domenico Mandaglio, University of Calabria

Yelena Mejova, ISI Foundation

Sandra Mitrovic, KU Leuven

Davide Mottin, Aarhus University

Giulia Preti, ISI Foundation

Daniel Schloer, University of Wurzburg

Christoph Scholz, Fraunhofer IEE

Edoardo Vacchi, Red Hat

Yongluan Zhou, University of Copenaghen

ORGANIZERS

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Valerio Bitetta, UniCredit, Italy

Ilaria Bordino, UniCredit, Italy

Andrea Ferretti, UniCredit, Italy

Francesco Gullo, UniCredit, Italy

Giovanni Ponti, ENEA, Italy

Lorenzo Severini, UniCredit, Italy

(midas2021@easychair.org)