DocumentCode
3301070
Title
The YTM-based stock portfolio mining approach by genetic algorithm
Author
Chun-Hao Chen ; Ching-Yu Hsieh ; Yeong-Chyi Lee
Author_Institution
Dept. of Comput. Sci. & Inf. Eng., Tamkang Univ., Taipei, Taiwan
fYear
2013
fDate
13-15 Dec. 2013
Firstpage
38
Lastpage
42
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.
Keywords
cost-benefit analysis; genetic algorithms; investment; YTM-based stock portfolio mining; YTMGPSM; chromosome; genetic algorithm; investment capital penalty; portfolio penalty; return on investment; yield-to-maturity; Biological cells; Companies; Genetic algorithms; Investment; Portfolios; Sociology; Statistics; M-V model; genetic algorithm; portfolio selection; transaction lots; yield to maturity;
fLanguage
English
Publisher
ieee
Conference_Titel
Granular Computing (GrC), 2013 IEEE International Conference on
Conference_Location
Beijing
Type
conf
DOI
10.1109/GrC.2013.6740377
Filename
6740377
Link To Document