Book
 Data Mining in Finance: Advances in Relational and
Hybrid Methods
by Boris Kovalerchuk and Evgenii Vityaev,
Kluwer Acad. Publ, 2000
The Kluwer International Series in Engineering and Computer Science ,
Vol. 547
ISBN: 0-7923-7804-0
Kluwer's prepublication flyer, 2000 (pdf)
Foreword by Gregory Piatetsky-Shapiro
CONTENTS
1. The Scope and Methods
of the Study
2. Numerical Data Mining
Models with Financial Applications
3. Rule-Based and Hybrid
Financial Data Mining
4. Relational Data Mining
(RDM)
5. Financial Applications
of Relational Data Mining
6. Comparison of
Performance of RDM and other methods in financial applications
7. Fuzzy logic approach
and its financial applications
Getting
the book:
Amazon.com
Barnes&Noble
Springer/Kluwer
|
5. Financial Applications of Relational Data Mining
Contents
- Introduction
- Transforming numeric data into relations
- Hypotheses and probabilistic “laws”
- Markov chains as probabilistic “laws” in finance
- Learning
- Method of forecasting
- Experiment 1
- Experiment 2
- Interval stock forecast for portfolio selection
- Predicate invention for financial applications: calendar effects
- Conclusion
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