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An Artificial Intelligence Approach for Decision Making in Investment

by Hegazy Zaher, Naglaa Ragaa Saeid, Walaa Moshref
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 182 - Number 19
Year of Publication: 2018
Authors: Hegazy Zaher, Naglaa Ragaa Saeid, Walaa Moshref
10.5120/ijca2018917953

Hegazy Zaher, Naglaa Ragaa Saeid, Walaa Moshref . An Artificial Intelligence Approach for Decision Making in Investment. International Journal of Computer Applications. 182, 19 ( Oct 2018), 24-32. DOI=10.5120/ijca2018917953

@article{ 10.5120/ijca2018917953,
author = { Hegazy Zaher, Naglaa Ragaa Saeid, Walaa Moshref },
title = { An Artificial Intelligence Approach for Decision Making in Investment },
journal = { International Journal of Computer Applications },
issue_date = { Oct 2018 },
volume = { 182 },
number = { 19 },
month = { Oct },
year = { 2018 },
issn = { 0975-8887 },
pages = { 24-32 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume182/number19/30042-2018917953/ },
doi = { 10.5120/ijca2018917953 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:11:52.283510+05:30
%A Hegazy Zaher
%A Naglaa Ragaa Saeid
%A Walaa Moshref
%T An Artificial Intelligence Approach for Decision Making in Investment
%J International Journal of Computer Applications
%@ 0975-8887
%V 182
%N 19
%P 24-32
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper considers decision making for fuzzy investments. A proposed client asset allocation model based on Mamdani FIS. The major aim of building such model is to help advising clients how to allocate portions of their investments in three types of assets, saving account, investment certificate and investment fund. The investment advisory models are applied with the goal of maximizing the expected return under two constraints, client’s risk and age. The investment decisions can be undertaken when the aggregated if-then rules are applied in Mamdani FIS. A comparison between using different types and number of membership functions is outlined.The types of membership functions used are triangular MF ,Trapizodial MF and mixing between both triangular an trapizodial MF. It was found that using the MFs of the same kind triangular MF only or trapezoidal MF only give better expected returns than mixed MFs. The work is accompanied by an illustrative case study that show the validity of the approach, followed by some recommendations for future research area.

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Index Terms

Computer Science
Information Sciences

Keywords

Fuzzy investment Mamdani Fuzzy Inference system assets allocation & decision making in investment or finance.

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