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Stock Investment of Agriculture Companies in the Vietnam Stock Exchange Market: An AHP Integrated with GRA-TOPSIS-MOORA Approaches

The Journal of Asian Finance, 2020, Economics and Business , 7(7), 31, pp.113-121 [Peer Reviewed Journal]

ISSN: 2288-4637 ;EISSN: 2288-4645 ;DOI: 10.13106/jafeb.2020.vol7.no7.113

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  • Title:
    Stock Investment of Agriculture Companies in the Vietnam Stock Exchange Market: An AHP Integrated with GRA-TOPSIS-MOORA Approaches
  • Author: NGUYEN, Phi-Hung ; TSAI, Jung-Fa ; G, Venkata Ajay KUMAR ; HU, Yi-Chung
  • Subjects: 경제학
  • Is Part Of: The Journal of Asian Finance, 2020, Economics and Business , 7(7), 31, pp.113-121
  • Description: Multi-criteria stock selection is a critical issue for effective investment since the improper stock investment might cause many problems affecting investors negatively. Investors need a range of financial indicators while they are choosing the optimal set of stocks to invest. This study aims to rank the stock of agriculture companies indexed on the Vietnam Stock Exchange Market. The data of 13 agriculture companies during the 2016-2019 periods was analyzed by analytical hierarchy process (AHP) integrated with grey relational analysis (GRA), multiobjective optimization ratio analysis (MOORA), and technique for order performance by similarity to ideal solution (TOPSIS). The AHP method is employed to determine the weights of the proposed financial ratios, and GRA, TOPSIS, and MOORA approaches are used to obtain final ranking. The results indicated that HSL is the top stock with the highest rank and GRA, MOORA, and TOPSIS rankings have strong correlation values between 0.78-1. The findings suggest that the integrated model could be implemented effectively to specific analysis of industries such as oil and gas, textiles, food, and electronics in future research. Further, other techniques like COPRAS, KEMIRA, and EDAS could be employed to evaluate the financial performance of other companies to solve investment problems.
  • Publisher: 한국유통과학회
  • Language: English
  • Identifier: ISSN: 2288-4637
    EISSN: 2288-4645
    DOI: 10.13106/jafeb.2020.vol7.no7.113
  • Source: Alma/SFX Local Collection

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