NDLI: The YTM-based stock portfolio mining approach by genetic algorithm

Content Provider	IEEE Xplore Digital Library
Author	Chun-Hao Chen Ching-Yu Hsieh Yeong-Chyi Lee
Copyright Year	2013
Description	Author affiliation: Dept. of Inf. Manage., Cheng Shiu Univ., Kaohsiung, Taiwan (Yeong-Chyi Lee) \|\| Dept. of Comput. Sci. & Inf. Eng., Tamkang Univ., Taipei, Taiwan (Chun-Hao Chen; Ching-Yu Hsieh)
Abstract	This study proposes a yield-to-maturity (YTM)-based genetic portfolio selection model with user defined constraints, namely YTMGPSM. A set of real numbers are encoded into a chromosome to form a possible portfolio, which presents whether buy or not buy and purchased units of assets. The fitness value of a chromosome is evaluated by return on investment, value at risk and suitability of the respective portfolio. The suitability of a chromosome consists of portfolio penalty and investment capital penalty that are used to reflect the satisfactions of user predefined maximum investment and maximum number of companies, respectively. Experiments on real dataset are made to show the merits of the proposed approach.
Sponsorship	IEEE Comput. Soc.
Starting Page	38
Ending Page	42
File Size	1253637
Page Count	5
File Format	PDF
ISBN	9781479912827
DOI	10.1109/GrC.2013.6740377
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-12-13
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	genetic algorithm Sociology Companies portfolio selection Statistics yield to maturity Portfolios Biological cells M-V model Investment Genetic algorithms transaction lots
Content Type	Text
Resource Type	Article

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