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A hybrid grey MCDM approach for asset allocation: evidence from China’s Shanghai Stock Exchange

    Ebenezer Fiifi Emire Atta Mills   Affiliation
    ; Mavis Agyapomah Baafi   Affiliation
    ; Nelson Amowine   Affiliation
    ; Kailin Zeng   Affiliation

Abstract

Asset allocation is a critical concern for any investor in the financial market. This paper aims to prioritize five randomly selected firms from the top ten stocks by market capitalization of the Shanghai Stock Exchange (SSE) by opting for adequate financial procedures and practical criteria under uncertain conditions. Decision makers want not only the ranking order of stocks but also capital proportions to be allocated. Therefore, this study uses a hybrid multi-criteria decision-making (MCDM) approach comprising of an integrated analytic network process (ANP) and decision making trial and evaluation laboratory (DEMATEL) in a grey environment for optimal portfolio selection to provide both ranking and weighting information for decision makers. Results indicate that return, financial ratios, dividends, and risk are causal criteria group, which are the most influential determinants for obtaining high benefits with regards to stock portfolio selection in SSE. The free float of stocks is the least influencing criterion among all identified criteria of stock portfolio selection of SSE. The Industrial and Commercial Bank of China Ltd. stocks have the highest allocated proportion with the highest priority shown by investors and can be described as a suitable alternative. The practical implications of this research are that the approach, when applied, highlights how the grey system theory minimizes the uncertainties in all stages of decision-making of portfolio selection.

Keyword : asset allocation, grey MCDM, grey-ANP, grey-DEMATEL, Shanghai Stock Exchange, China

How to Cite
Atta Mills, E. F. E. ., Baafi, M. A. ., Amowine, N. ., & Zeng, K. . (2020). A hybrid grey MCDM approach for asset allocation: evidence from China’s Shanghai Stock Exchange. Journal of Business Economics and Management, 21(2), 446-472. https://doi.org/10.3846/jbem.2020.11967
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Mar 3, 2020
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This work is licensed under a Creative Commons Attribution 4.0 International License.

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