Refined group learning based on XCS and neural network in intelligent financial decision support system

Jung Bin Li*, An-Pin Chen

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

Cooperative learning is widely defined as a process through which a group of individuals interact to achieve a learning goal. In the fluctuating stock market, investors often have various decision-making approaches. This study attempts to exploit computer technology, financial mathematics, and econometrics to make reasonable investment decisions to reduce man-made errors or mistakes and increase profits. This work integrates the extended Classifier System (XCS) and neural network modules and incorporates features such as dynamic learning and group decision making. An empirical study is conducted by comparing the profitability of the proposed system with that of investment strategies based on simple rules with single technical indices, individual learning XCS, buy and hold, and six-year term deposit based on the Taiwan Index. The proposed system demonstrates superior performance in terms of accuracy, rate of cumulative return, and variance of return.

Original languageEnglish
Title of host publicationProceedings - ISDA 2006
Subtitle of host publicationSixth International Conference on Intelligent Systems Design and Applications
Pages925-930
Number of pages6
DOIs
StatePublished - 1 Dec 2006
EventISDA 2006: Sixth International Conference on Intelligent Systems Design and Applications - Jinan, China
Duration: 16 Oct 200618 Oct 2006

Publication series

NameProceedings - ISDA 2006: Sixth International Conference on Intelligent Systems Design and Applications
Volume2

Conference

ConferenceISDA 2006: Sixth International Conference on Intelligent Systems Design and Applications
CountryChina
CityJinan
Period16/10/0618/10/06

Keywords

  • Classifier system
  • Multi-agent
  • Neural network
  • XCS

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