Intelligent systems for finance and business

著者

書誌事項

Intelligent systems for finance and business

edited by Suran Goonatilake and Philip Treleaven

Wiley, c1995

  • : cloth

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注記

Includes bibliographical references and index

内容説明・目次

内容説明

A new generation of computing techniques, commonly known as "intelligent systems", are now being applied to a variety of financial and business modelling tasks. These techniques include genetic algorithms, neural networks, dynamical systems models (chaos theory), expert systems, rule induction, fuzzy systems and hybrids of these techniques. They are also being applied to stock market prediction, portfolio management, credit evaluation, fraud detection, insurance risk assessment, macro-economic modelling, and in many cases are outperforming traditional statistical techniques. This study analyzes the relative merits of the different techniques for financial and economic modelling, and examines current applications.

目次

  • Partial table of contents:
  • Intelligent Systems for Finance and Business: An Overview (S. Goonatilake)
  • CREDIT SERVICES
  • Intelligent Systems at American Express (R. Didner)
  • Neural Networks for Credit Scoring (D. Leigh)
  • DIRECT MARKETING
  • Neural Networks for Data-driven Marketing (P. Furness)
  • FRAUD DETECTION AND INSURANCE
  • Insider Dealing Detection at the Toronto Stock Exchange (S. Mott)
  • Expert Systems at Lloyd's of London (C. Talbot)
  • SECURITIES TRADING AND PORTFOLIO MANAGEMENT
  • Fuzzy Logic for Financial Trading (S. Tano)
  • Syntactic Pattern-based Inductive Learning for Chart Analysis (J. Lee & H. Kim)
  • ECONOMIC MODELLING
  • Genetic Programming for Economic Modeling (J. Koza)
  • Intelligent, Self-organizing Models in Economics and Finance (P. Allen)
  • IMPLEMENTING INTELLIGENT SYSTEMS
  • Software for Intelligent Systems (P. Treleaven)
  • Index.

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