DEVELOPING A MODULAR PORTFOLIO SELECTION MODEL FOR SHORT-TERM AND LONGTERM MARKET TRENDS AND MASS PSYCHOLOGY

M. Jasemi, A.M. Kimiagari

Abstract


ENGLISH ABSTRACT: In an effort to model stock markets, many researchers have developed portfolio selection models to maximise investor satisfaction. However, this field still needs more accurate and comprehensive models. Development of these models is difficult because of unpredictable economic, social, and political variables that affect stock market behaviour. In this paper, a new model with three modules for portfolio optimisation is presented. The first module derives the efficient frontier through a new approach; the second presents an intelligent mechanism for emitting trading signals; while the third module integrates the outputs of the first two modules. Some important features of the model in comparison with others are: 1) consideration of investors emotions the psychology of the market that arises from the three above-mentioned factors; 2) significant loosening of simplifying assumptions about markets and stocks; and 3) greater sensitivity to new data.

AFRIKAANSE OPSOMMING: In n poging om aandelemarkte te modelleer het verskeie navorsers portefeulje-seleksiemodelle ontwikkel om beleggers se tevredenheid te maksimiseer. Desnieteenstaande word meer akkurate en omvattende modelle benodig. Die ontwikkeling van hierdie modelle word bemoeilik deur die onvoorspelbare ekonomiese, sosiale en politiese veranderlikes wat aandelemarkte se gedrag raak. In hierdie artikel word n nuwe model voorgehou wat bestaan uit drie modules vir portefeulje-optimisering. Die eerste module bepaal die doelmatigheidsgrens op n nuwe metode; die tweede hou n intelligente meganisme voor om transaksieseine te lewer terwyl die derde module die uitsette van die eerste twee modules integreer. Sommige van die belangrike eienskappe van die model wat dit van ander onderskei is: 1) konsiderasie van die beleggers se emosies die sielkunde van die mark wat ontstaan vanwedie genoemde faktore; 2) betekenisvolle verslapping van die vereenvoudigende aannames oor market en aandele; en 3) verhoogde sensitiwiteit tot nuwe data.


Keywords



Full Text:

PDF


DOI: https://doi.org/10.7166/22-1-34

Refbacks

  • There are currently no refbacks.




Copyright (c) 2015 The South African Journal of Industrial Engineering


ISSN 2224-7890 (on-line) ; ISSN 1012-277X (print)


Powered by OJS and hosted by Stellenbosch University Library and Information Service since 2011.


Disclaimer:

This journal is hosted by the SU LIS on request of the journal owner/editor. The SU LIS takes no responsibility for the content published within this journal, and disclaim all liability arising out of the use of or inability to use the information contained herein. We assume no responsibility, and shall not be liable for any breaches of agreement with other publishers/hosts.

SUNJournals Help