Call for Papers Workshop: Application of Machine Learning and Data Mining in Finance 10th European Conference on Machine Learning (ECML-98) Chemnitz, Germany, April 24 1998 General Information In conjunction with the 10th European Conference on Machine Learning (ECML-98) the workshop "Application of Machine Learning and Data Mining in Finance" will be held in Chemnitz, Germany, on April, 24th 1998. The main conference takes place from April, 21st to 23rd 1998. Motivation Advanced data analysis and forecasting technologies such as neural networks, symbolic machine learning and genetic algorithms are being increasingly applied to support financial asset management and credit risk management. These methods are considered by many financial management institutions as innovative technologies to support conventional quantitative techniques. Their use in computational finance will have a major impact in the modelling of the currency markets, in tactical asset allocation, bond and stock valuation and portfolio optimisation. In addition the application of these tools for scoring tasks delivers valuable support for the management of client credit risk. Targets This workshop is designed to bring together researchers in the field of Machine Learning with those practicing financial consulting. The purpose is twofold: - Practitioners should become familiar with the state of the art in machine learning research for predictive modelling and scoring systems. - The research community should receive ideas and requirements from participants from the financial world with the aim to improve the acceptance of Machine Learning applications and to identify future areas of research. Research papers representing new and significant developments in methodology as well as applications of practical use will be presented. Topics include: Application aspects: - Scoring systems: Application and Behavioural Scoring - Trading- and forecasting models - Volatility models - Value at Risk - Financially motivated objective functions Methodological aspects: - Symbolic Learning in financial engineering - Neural Networks for financial applications - Aspects and dependencies of data transformation and model selection - Backtest procedures: Advantages and bottlenecks - Pre-testing as an alternative to backtest - Data Mining process model for financial applications Submission of papers Authors wishing to present a paper should send an electronic version (uuencoded compressed PostScript) not later than 28 February 98 to: Dr. Elmar Steurer DAIMLER-BENZ AG - Research and Technology Postfach 2360 89013 Ulm Tel.: 0049 - 731 / 505 -2868 Fax: 0049 - 731 / 505 4210 Email: elmar.steurer@dbag.ulm.DaimlerBenz.COM Accepted papers will be published in the workshop notes. Selected papers will be issued in a book. Contributors will be allocated 20 minutes for an oral presentation during the workshop. Further invited talks and a panel discussion are planned. Program committee: Ulrich Anders University of Otago, Dunedin, New Zealand Jeremy H. Armitage State Street Bank and Trust Company, London, UK Dirk Baestens Generale Bank, Brussels, Belgium Georg Bol University of Karlsruhe, Germany Guenter Grimm allfonds, Munich, Germany Tae H. Hann University of Karlsruhe, Germany Ashar Mahboob Fuji Capital Markets Corporation, New York, USA Andreas Weigend STERN Business School, New York University, USA Apostolos N. Refenes London Business School, UK Andrea Sczesny ZEW Mannheim, Germany Charles Taylor University of Leeds, UK Diethelm Wuertz ETH, Zurich, Switzerland Hans-Georg Zimmermann Siemens AG, Munich, Germany Important Dates: Submission deadline: 28 February 1998 Notification of acceptance: 15 March 1998 Camera ready copy: 28 March 1998 Workshop: 24 April 1998 Organization: Gholamreza Nakhaeizadeh and Elmar Steurer DAIMLER-BENZ AG - Research and Technology e-mail: nakhaeizadeh@dbag.ulm.DaimlerBenz.COM elmar.steurer@dbag.ulm.DaimlerBenz.COM Registration and further information: For further information about the main conference and registration please contact: ecml98@lri.fr ecml98@informatik.tu-chemnitz.de or visit the web site: http://www.tu-chemnitz.de/informatik/ecml98