CFP

The Journal of Decision Support Systems Special Issue on Data Mining for Financial Decision Making

GUEST EDITORS Hui Wang, University of Ulster Andreas S. Weigend, Weigend Associates LLC

CALL FOR PAPERS

As information intensive organizations transform themselves from passive collectors to active explorers and exploiters of data, they face a serious challenge: How can they benefit from increased access to information to better understand their markets, customers, suppliers, operations and internal business processes?

Responding to this challenge, the field of data mining has emerged. It focuses on the process of discovering valid, comprehensible, and potentially useful knowledge from large data sets with the goal to apply this knowledge to decision making.

Data mining integrates concepts from modern statistics, intelligent information systems, machine learning, pattern recognition, decision theory, data engineering and database management, and provides powerful tools that can reveal complex and hidden relationships in large amounts of data. The approaches include neural networks, genetic programming, and tree-based methods. Data mining already has a major impact on business and finance.

Financial markets generate large volumes of data. Analysing these data to reveal valuable information and making use of the information in decision making present great opportunities but grand challenges for data mining. The rewards for finding valuable patterns are potentially enormous, but so are the difficulties. There is evidence that short-term trends do exist and some general patterns do occur frequently. Important problems are: how to find the trends at their early stages and how to time the beginning and ending of trends, how to take into account in decision making the found trends, the general patterns, and domain knowledge that describes the intricately inter-related world of global financial markets.

The focus of this special issue is on the use of data mining techniques for decision making in financial markets. Topics of interest include:

• Financial data selection and pre-processing for data mining
• Solutions to new problems in financial decision making
• New solutions for classical problems in financial decision making
• Data and solutions visualisation for financial decision making
• Successful case studies.

• Risk management including credit risk and market risk
• Asset allocation, dynamic trading and hedging
• Execution and liquidity models
• Behavioural finance, and other emerging areas.

SUBMISSION INSTRUCTIONS Electronic submissions are strongly encouraged. Postscript or PDF copies of manuscripts may be emailed to h.wang@ulst.ac.uk.

SUBMISSION DEADLINE: September 9, 2002

Details about the submission process and scope of the special issue are available at http://www.weigend.com/dss and http://www.elsevier.com/inca/homepage/sae/orms/dss/call1.htm