Applying Interactive Artificial Bee Colony to Construct the Stock Portfolio

Author

Jui-Fang Chang ; Tsai-Wei Yang ; Pei-Wei Tsai

Author_Institution

Dept. of Int. Bus., Nat. Kaohsiung Univ. of Appl. Sci., Kaohsiung, Taiwan

fYear

2013

fDate

10-12 Dec. 2013

Firstpage

129

Lastpage

132

Abstract

In recent years, lots of portfolio analysis methods been proposed one after another. The investors care about how much money they can earn, and the companies need to know how much performance they gain. In this paper, a new stock portfolio construction strategy using Investment Satisfied Capability Index (ISCI) and Interactive Artificial Bee Colony (IABC) is proposed. Two-year daily Return on Investment (ROI) data is used in the experiment to test the performance of our proposed method. The experimental results are compared with the investment result from Taiwan broader market and Taiwan Top 50 Tracker Fund of Taiwan Yuanta Securities. The results are positive.

Keywords

genetic algorithms; investment; particle swarm optimisation; stock markets; time series; GA; IABC; ISCI; PSO; ROI data; Taiwan Yuanta Securities; genetic algorithms; interactive artificial bee colony; investment satisfied capability index; particle swarm optimization; return on investment; stock portfolio construction strategy; time series models; Companies; Genetic algorithms; Indexes; Investment; Portfolios; Sociology; Statistics; IABC; ISCI; portfolio; stock investment;

fLanguage

English

Publisher

ieee

Conference_Titel

Robot, Vision and Signal Processing (RVSP), 2013 Second International Conference on

Conference_Location

Kitakyushu

Print_ISBN

978-1-4799-3183-5

Type

conf

DOI

10.1109/RVSP.2013.36

Filename

6829996