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MIDAS 2018 : MIDAS @ECML-PKDD 2018 - 3rd Workshop on MIning DAta for financial applicationS


When Sep 10, 2018 - Sep 14, 2018
Where Dublin, Ireland
Submission Deadline Jul 2, 2018
Notification Due Jul 23, 2018
Final Version Due Aug 6, 2018
Categories    data mining   machine learning   finance

Call For Papers

MIDAS 2018
The Third Workshop on MIning DAta for financial applicationS
September 10 or 14, 2018 - Dublin, Ireland

in conjunction with

The European Conference on Machine Learning and Practice of Knowledge Discovery
September 10-14, 2018 - Dublin, Ireland

We invite submissions to the 3rd MIDAS Workshop on MIning DAta for financial applicationS,
to be held in conjunction with ECML-PKDD 2018 - European Conference on Machine Learning and
Principles and Practice of Knowledge Discovery.

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.

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
- Discovering patterns and correlations in financial data
- Text mining and NLP for financial applications
- Financial network analysis
- Time series analysis
- Pitfalls identification

We invite submissions of either regular papers (long or short), and extended abstracts:
- Long regular papers: up to 12 pages long (in the Springer LNCS style,, reporting on novel,
unpublished work that might not be mature enough for a conference or journal submission.
- Short regular papers: up to 6 pages long, presenting work-in-progress.
- Extended abstracts: up to 2 pages long, referring to recently published work on
the workshop topics, position papers, late-breaking results, or emerging research problems.

Contributions should be submitted in PDF format, electronically, using the workshop
submission site at
Papers must be written in English and formatted according to the ECML-PKDD 2018
submission guidelines available at

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.

Accepted papers will be part of the workshop proceedings, which will be published online
as a volume of the CEUR Workshop Proceedings publication service (
The CEUR service ensures that the published papers are permanently available and citable.
CEUR Workshop Proceedings are indexed by major digital libraries
(e.g., DBLP, GoogleScholar, CiteSeerX).

Additionally, based on the success of the workshop, extended versions of selected papers
will be published either as a post-proceeding volume of the Springer LNAI series or as a
special issue of a premier journal in the fields of interest of the workshop.

Submission deadline: July 2, 2018
Acceptance notification: July 23, 2018
Camera-ready deadline: August 6, 2018
Workshop date: September 10, 2018 or September 14, 2018


Aris Anagnostopoulos, Sapienza University of Rome
Ioannis Arapakis, Telefonica Research
Argimiro Arratia, Universitat PolitÈcnica de Catalunya
Xiao Bai, Yahoo Research
Paolo Barucca, University of Zurich
Ali Caner Turkmen Bogazici University,
Olivier Caelen, Atos Wordline
Annalina Caputo, ADAPT - School of Computer Science and Statistics, Trinity College Dublin
Diego Ceccarelli, Bloomberg LP
Carlotta Domeniconi, George Mason University
Debora Donato, StumbleUpon Inc
Ana Maria Freire Veiga, UPF
Joao Gama, University of Porto
Ruth Garcia, Skyscanner
Sara Hajian, NTent
Roberto Interdonato, CIRAD - UMR TETIS
Andreas Kaltenbrunner, NTent
Dragi Kocev, Joûef Stefan Institute
Nicolas Kourtellis, Telefonica Research
Iordanis Koutsopoulos, UTH
Elisa Letizia, European Central Bank
Donato Malerba, University of Bari
Matteo Manca, Eurecat
Stefania Marrara, C2T
Yelena Mejova, Qatar Computing Research Institute
Iris Miliaraki, Schibsted
Davide Mottin, Hasso Plattner Institute
Jordi Nin, BBVA Data & Analytics
Alvin Pastore, The University of Sheffield
Mirjana Pejic Bach, Zagreb University
Giovanni Ponti, ENEA
Aleksandra Rashkovska, Josef Stefan Institute
Antti Ukkonen, Finnish Institute of Occupational Health
Edoardo Vacchi, RedHat
Tim Weninger, University of Notre Dame

Valerio Bitetta, UniCredit, R&D Dept., Italy
Ilaria Bordino, UniCredit, R&D Dept., Italy
Guido Caldarelli, IMT Institute for Advanced Studies Lucca, Italy
Andrea Ferretti, UniCredit, R&D Dept., Italy
Francesco Gullo, UniCredit, R&D Dept., Italy
Stefano Pascolutti, UniCredit, R&D Dept., Italy
Tiziano Squartini, IMT Institute for Advanced Studies Lucca, Italy

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