Proceedings of the 9th Joint International Conference on Information Sciences (JCIS-06)

An Evolutionary Weight Encoding Scheme and Crossover Methodology in Portfolio Assets Allocation

Authors
Ping-Chen Lin 0, Po-Chang Ko, Hsin-Chieh Wang
Corresponding Author
Ping-Chen Lin
0Department of Finance, KUAS
Available Online October 2006.
DOI
https://doi.org/10.2991/jcis.2006.133How to use a DOI?
Keywords
Portfolio, Asset allocation, Genetic Algorithms, Encoding, Crossover
Abstract
Most of GA-based portfolio assets allocation uses normalization method to allocate investment asset’s weight. However, the normalization process will cause unease converging and even diverging characteristics, because it changes the gene’s relativity of address in chromosome. In this paper, we propose a weighed encoding scheme and crossover algorithm to allocate suitable assets in portfolio. Each gene encoded as a real number in a chromosome is denoted as the weighted number of assets in our approach. Due to no specific relationship assumed in our encoding scheme, the crossover process would not influence overall converging speed. In addition, in order to avoid losing optimal asset allocations through quicker converging, we also introduce the expanding rate to allow enlarging the possible range of asset allocation weight during the evolutionary process. Our experiments also show that higher expanding rate produces higher excess profit of investment.
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Proceedings
9th Joint International Conference on Information Sciences (JCIS-06)
Part of series
Advances in Intelligent Systems Research
Publication Date
October 2006
ISBN
978-90-78677-01-7
ISSN
1951-6851
DOI
https://doi.org/10.2991/jcis.2006.133How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Ping-Chen Lin
AU  - Po-Chang Ko
AU  - Hsin-Chieh Wang
PY  - 2006/10
DA  - 2006/10
TI  - An Evolutionary Weight Encoding Scheme and Crossover Methodology in Portfolio Assets Allocation
BT  - 9th Joint International Conference on Information Sciences (JCIS-06)
PB  - Atlantis Press
SN  - 1951-6851
UR  - https://doi.org/10.2991/jcis.2006.133
DO  - https://doi.org/10.2991/jcis.2006.133
ID  - Lin2006/10
ER  -