MIDAS
The Sixth Workshop on MIning DAta for financial applicationS
September 17, 2021 - Virtual
in
conjunction with
ECML-PKDD 2021
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases
September 13-17, 2021 - Virtual
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, for 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.
PAST EDITIONS
We encourage submission of papers on the area of data mining for financial applications. Topics of interest include, but are not limited to:
WORKSHOP FORMAT
The COVID-19 pandemic has made a traditional conference format
impossible for ECML-PKDD 2021. To allow all members of ECML-PKDD
and the wider research community at large to participate,
ECML-PKDD 2021, and all its satellite events, including the
MIDAS workshop, will thus be organized as a fully-fledged
virtual event.
Further details will be provided later.
INVITED SPEAKER
Dr.
Gianmarco De Francisci Morales, ISI Foundation
Title: "How I learned to stop worrying and love the risk"
Abstract: Risk is one of the fundamental concepts in finance,
and it appears in several forms such as market risk, credit
risk, liquidity risk, and many others. This talk will present
two examples of applied research projects which deal with risk
in the context of a real-world bank.
We will first illustrate how graph mining techniques improve
models for estimating credit risk, by allowing to take trade
credit into account via relational features from the trade
network and the supply chain of the firms considered. We will
then show how reinforcement learning techniques can be used to
tackle a complex, multi-period portfolio allocation problem in
a life insurance context, which includes liability management.
Finally, we will talk about another facet of risk: What are
the risks when running an applied science project? Such a
project requires managing the expectations and trust of the
stakeholders, and a careful balance between ambition, novelty,
disruption, and feasibility. We will discuss the main
obstacles to overcome, and the lessons learned while working
on risky projects.
ACCEPTED PAPERS
Luca
Barbaglia, Sergio Consoli and Susan Wang.
Financial forecasting with word embedding extracted from
news: a preliminary analysis
Eric
Benhamou, David Saltiel, Serge Tabachnik, Corentin Bourdeix
and Francois Chareyron.
Adaptive Supervised Learning for Financial Markets Volatility
Targeting Models
Hamish
Hall, Pedro Baiz and Philip Nadler.
Efficient Analysis of Transactional Data Using Graph
Convolutional Networks
Jorge
M. Bravo.
Forecasting longevity for financial applications: A first
experiment with deep learning methods
Sergio
Consoli, Matteo Negri, Amirhossein Tebbifakhr, Elisa Tosetti
and Marco Turchi.
On neural forecasting and news emotions: the case of the
Spanish stock market
Luigi
Bellomarini, Livia Blasi, Rosario Laurendi and Emanuel
Sallinger.
A Reasoning Approach to Financial Data Exchange with
Statistical Confidentiality
Edoardo
Vittori, Martino Bernasconi de Luca, Francesco Trovò and
Marcello Restelli.
Dealing with Transaction costs in Online Portfolio
Optimization
PROGRAM
Workshop
Day: September 17th, 2021
9:00 - 10:30 SESSION I
-----------------------------------
9:00 - 9:10 OPENING
9:10 - 10:00 [INVITED TALK] Gianmarco De Francisci
Morales, ISI Foundation, Turin.
How I learned to stop worrying and love the risk!
10:00 - 10:30 [SHORT PAPER] Luca Barbaglia, Sergio Consoli and
Susan Wang. Financial forecasting with word embedding extracted
from news: a preliminary analysis
-----------------------------------
10:30
- 11:00 Coffee break
-----------------------------------
11:00
- 12:30 SESSION II
-----------------------------------
11:00
- 11:30 [FULL PAPER] Eric Benhamou, David Saltiel, Serge
Tabachnik, Corentin Bourdeix and Francois Chareyron.
Adaptive Supervised Learning for Financial Markets Volatility
Targeting Models
11:30 - 12:00 [FULL PAPER] Hamish Hall, Pedro Baiz and Philip
Nadler.
Efficient Analysis of Transactional Data Using Graph
Convolutional Networks
12:00 - 12:30 [FULL PAPER] Jorge M. Bravo.
Forecasting longevity for financial applications: A first
experiment with deep learning methods
-----------------------------------
12:30
- 14:00 Lunch break
-----------------------------------
14:00
- 15:40 SESSION III
-----------------------------------
14:00
- 14:30 [SHORT PAPER] Sergio Consoli, Matteo Negri,
Amirhossein Tebbifakhr, Elisa Tosetti and Marco Turchi.
On neural forecasting and news emotions: the case of the Spanish
stock market
14:30 - 15:00 [SHORT PAPER] Luigi Bellomarini, Livia Blasi,
Rosario Laurendi and Emanuel Sallinger.
A Reasoning Approach to Financial Data Exchange with Statistical
Confidentiality
15:00 - 15:30 [SHORT PAPER] Edoardo Vittori, Martino
Bernasconi de Luca, Francesco Trovò and Marcello Restelli.
Dealing with Transaction costs in Online Portfolio Optimization
15.30 - 15.40 CONCLUDING REMARKS