An intelligent portfolio management system

Pao Yue-kong Library Electronic Theses Database

An intelligent portfolio management system


Author: Tse, Wan-fung Willy
Title: An intelligent portfolio management system
Degree: M.Sc.
Year: 1998
Subject: Portfolio management -- Data processing
Investment analysis -- Data processing
Artificial intelligence
Hong Kong Polytechnic University -- Dissertations
Department: Multi-disciplinary Studies
Dept. of Computing
Pages: vii, 123 leaves : ill. ; 30 cm
Language: English
InnoPac Record:
Abstract: With the emergence of information technology, the finance industries have great improvement in their products and services - numerous financial instruments were introduced to the market as a result of increasing computation power. Global investments are available due to the improvement of data communication means. Up till now, the information technology is mainly applied by the investors to the operation area. However, in the future it is expected to do more, such as automating decisions, intelligently analysing large volume of data, and learning from their mistakes. In fact, such intelligent technologies are not new in the academic field. Some of them were even applied successfully to some application domains, for example fuzzy controller. The use of intelligent techniques in financial sector is not popular and they still have lots of room available for research and development. Portfolio management is one of the topics for which many investors are interested on. The modern portfolio management is applicable not only to minimise risk for an expected return, but also to make decisions on investment. Over the decades, financial analysts have developed a strong framework in portfolio management which based on numerous academic studies and practical experiences. The framework covers all stages in the portfolio management process - from portfolio construction, monitoring to revision. The aim of this dissertation is to apply the intelligence techniques to the portfolio management process. This techniques include fuzzy logic, genetic algorithms and fuzzy expert system.

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