Seminar on Computational Learning and Adaptation
Data Mining and Machine Learning in Finance:
the Application of Exchange Rate Forecasting
Folke A. Rauscher
Daimler-Benz Research & Technology
Ulm, Germany
Within the research fields of Machine Learning and Data Mining the
development of intelligent and adaptive methods have, among others,
led to most exciting applications in finance. These methods for the
intelligent analysis of large data sets have emerged from several
historically disjoint fields, such as applied statistics, information
systems, machine learning, data engineering, artificial intelligence
and knowledge discovery in databases. Within the quantitative financial
research these emerging technologies become amenable to data-driven
modeling as large sets of financial data become available, and
therefore "mine-able". In this talk, I first briefly describe the
Data Mining and Machine Learning activities at Daimler-Benz Research &
Technology in Germany in general. Then I describe the more specific
application of intelligent and adaptive methods for exchange rate
forecasting in an corporate business environment. Here I discuss
neural networks, multi-task learning aspects, decision and regressions
trees in the context of, and as applied to, quantitative financial
research. Finally, I raise some future research aspects which I would
be happy to collaboratively address during my visit at Stanford
through March.
Date: Thurs., January 15; Time: 4:15-5:30PM; Place: Gates 100
The goal of this seminar is to increase
communication among local researchers with interests in computational
approaches to learning and adaptation. If you would like to be added
to (or removed from) the mailing list, or if you are interested in
giving a talk in the seminar, please send email to
iba@isle.org.
Return to seminar schedule.