DocumentCode
1920223
Title
Maximizing portfolio diversification benefit via extended mean-variance model
Author
Zulkifli, Mohamed ; Daud, Mohamed ; Omar, Samat
Author_Institution
Fac. of Bus. Manage., Univ. Teknol. MARA, Shah Alam, Malaysia
fYear
2010
fDate
3-5 Oct. 2010
Firstpage
675
Lastpage
680
Abstract
Stock market fluctuation is very challenging to investors. They have to make important decision regarding dollar and cent in uncertain environment. Therefore the study has introduced a model to present the uncertainty in stock returns. The model was derived by incorporating the MV model and the VBS fuzzy model. Using fuzzy approach, the study introduced an extended MV model. To investigate the effectiveness of the extended MV model, the study has tested the model in 10 types of portfolios involving 300 listed companies in Bursa Malaysia from 1998 to 2009. Portfolio superiority then being examined by using the efficient frontier index (EFI). Empirical evidence revealed that the extended MV model is able to maximize portfolio´s diversification benefit in the Malaysian stock market compared to the conventional MV and the VBS fuzzy models. The result provides on how the Malaysian investors could improve on their investment strategy. This study is perhaps one of the first to address portfolio diversification benefit using the extended mean-variance model in the Malaysian stock market.
Keywords
fuzzy set theory; investment; stock markets; Malaysian investors; VBS fuzzy model; efficient frontier index; extended MV model; extended mean-variance model; investment strategy; portfolio diversification maximization; stock market fluctuation; Adaptation model; Biological system modeling; Indexes; Investments; Mathematical model; Portfolios; Stock markets; Malaysia; efficient frontier; fuzzy; mean-variance; portfolio;
fLanguage
English
Publisher
ieee
Conference_Titel
Industrial Electronics & Applications (ISIEA), 2010 IEEE Symposium on
Conference_Location
Penang
Print_ISBN
978-1-4244-7645-9
Type
conf
DOI
10.1109/ISIEA.2010.5679379
Filename
5679379
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