MIDAS 2016 : The First Workshop on MIning DAta for financial applicationS @ECML-PKDD 2016

Sep 19, 2016 - Sep 19, 2016

Riva del Garda (Italy)

Call For Papers

We invite submissions to the MIDAS Workshop on MIning DAta for financial applicationS, to be held in conjunction with ECML-PKDD 2016 - 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.

Topics of Interest

• 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

IMPORTANT DATES

Submission deadline: Jul 4, 2016.

Notification Due: Jul 25, 2016.

Final Version Due:Aug 8, 2016.

                       

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