IDEAS home Printed from https://ideas.repec.org/a/spr/operea/v24y2024i3d10.1007_s12351-024-00817-w.html
   My bibliography  Save this article

The novel hybrid multiple criteria decision method BWM-Moora-N applied for investment funds prioritization

Author

Listed:
  • Victor Rosemberg Reis Mota

    (Universidade Federal Fluminense)

  • Carlos Francisco Simões Gomes

    (Universidade Federal Fluminense)

  • Diogo Ferreira Lima Silva

    (Universidade Federal Fluminense)

  • Marcos Santos

    (Centro de Análises de Sistemas Navais (CASNAV)
    Military Institute of Engineering (IME))

Abstract

This study presents a novel approach for ranking problems, named BWM-MOORA-N, which consists of a hybrid MCDM/A method based on BWM and MOORA. The proposed method is utilized to analyze a set of investment funds, considering the preferences of a financial analyst. The BWM-MOORA-N method utilizes BWM to determine the criteria weights, MOORA to order the alternatives, and an additional normalization procedure to ensure that the results are evaluated on a 0–1 scale. The final normalization prevents the presence of negative global evaluations, which makes it easier to interpret and visualize the results. In the application, 42 investment funds are ordered based on a set of criteria derived from real data provided by an investment advisory company. The decision-makers preferences, according to a financial expert, were modeled using an unstructured process of interviews conducted by a decision analyst. The results of the study include comparisons to risk-return metrics and a ranking obtained using a reference point approach that incorporates the Tchebycheff distance concept. Additionally, experiments were conducted to vary possible BWM input comparisons, and statistics from over 1000 simulations are provided. The proposed method produces coherent results, including a ranking of funds that reflects the significant importance given by the decision-maker to profitability and risk criteria. Furthermore, the additional normalization proves to be suitable for practical purposes. Finally, the simulation results provide detailed information for each alternative, including the mean and standard deviations of the global evaluation and the mode of the ranking position.

Suggested Citation

  • Victor Rosemberg Reis Mota & Carlos Francisco Simões Gomes & Diogo Ferreira Lima Silva & Marcos Santos, 2024. "The novel hybrid multiple criteria decision method BWM-Moora-N applied for investment funds prioritization," Operational Research, Springer, vol. 24(3), pages 1-43, September.
    • Handle: RePEc:spr:operea:v:24:y:2024:i:3:d:10.1007_s12351-024-00817-w
    DOI: 10.1007/s12351-024-00817-w
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s12351-024-00817-w
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s12351-024-00817-w?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Adiel Teixeira de Almeida-Filho & Diogo Ferreira de Lima Silva & Luciano Ferreira, 2021. "Financial modelling with multiple criteria decision making: A systematic literature review," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 72(10), pages 2161-2179, October.
    2. Pranith Kumar Roy & Krishnendu Shaw, 2021. "A multicriteria credit scoring model for SMEs using hybrid BWM and TOPSIS," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-27, December.
    3. Stewart, TJ, 1992. "A critical survey on the status of multiple criteria decision making theory and practice," Omega, Elsevier, vol. 20(5-6), pages 569-586.
    4. Stanley Zionts, 1979. "MCDM---If Not a Roman Numeral, Then What?," Interfaces, INFORMS, vol. 9(4), pages 94-101, August.
    5. repec:eme:mfppss:03074350210768077 is not listed on IDEAS
    6. Haoran Zhao & Sen Guo & Huiru Zhao, 2018. "Comprehensive Performance Assessment on Various Battery Energy Storage Systems," Energies, MDPI, vol. 11(10), pages 1-26, October.
    7. Constantin Zopounidis & Emilios C. C Galariotis & Michael Doumpos & Stavroula Sarri & Kostas Andriosopoulos, 2015. "Multiple criteria decision aiding for finance: An updated bibliographic survey," Post-Print hal-02879842, HAL.
    8. Saaty, Thomas L., 1990. "How to make a decision: The analytic hierarchy process," European Journal of Operational Research, Elsevier, vol. 48(1), pages 9-26, September.
    9. Diogo F. de Lima Silva & Julio Cezar Soares Silva & Lucimário G. O. Silva & Luciano Ferreira & Adiel T. de Almeida-Filho, 2018. "Sovereign Credit Risk Assessment with Multiple Criteria Using an Outranking Method," Mathematical Problems in Engineering, Hindawi, vol. 2018, pages 1-11, September.
    10. Salvatore Greco & Benedetto Matarazzo & Roman Slowinski & Stelios Zanakis, 2011. "Global investing risk: a case study of knowledge assessment via rough sets," Annals of Operations Research, Springer, vol. 185(1), pages 105-138, May.
    11. Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, March.
    12. Siyavash Mohseni & Komeyl Baghizadeh & Julia Pahl & Stefania Tomasiello, 2022. "Evaluating Barriers and Drivers to Sustainable Food Supply Chains," Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-24, February.
    13. Mališa Žižović & Dragan Pamučar & Miloljub Albijanić & Prasenjit Chatterjee & Ivan Pribićević, 2020. "Eliminating Rank Reversal Problem Using a New Multi-Attribute Model—The RAFSI Method," Mathematics, MDPI, vol. 8(6), pages 1-16, June.
    14. Rezaei, Jafar, 2015. "Best-worst multi-criteria decision-making method," Omega, Elsevier, vol. 53(C), pages 49-57.
    15. Julio Cezar Soares Silva & Diogo Ferreira de Lima Silva & Luciano Ferreira & Adiel Teixeira de Almeida-Filho, 2022. "A dominance-based rough set approach applied to evaluate the credit risk of sovereign bonds," 4OR, Springer, vol. 20(1), pages 139-164, March.
    16. Mehdi KESHAVARZ GHORABAEE & Edmundas Kazimieras ZAVADSKAS & Zenonas TURSKIS & Jurgita ANTUCHEVICIENE, 2016. "A New Combinative Distance-Based Assessment(Codas) Method For Multi-Criteria Decision-Making," ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, Faculty of Economic Cybernetics, Statistics and Informatics, vol. 50(3), pages 25-44.
    17. Steuer, Ralph E. & Na, Paul, 2003. "Multiple criteria decision making combined with finance: A categorized bibliographic study," European Journal of Operational Research, Elsevier, vol. 150(3), pages 496-515, November.
    18. Cinelli, Marco & Kadziński, Miłosz & Gonzalez, Michael & Słowiński, Roman, 2020. "How to support the application of multiple criteria decision analysis? Let us start with a comprehensive taxonomy," Omega, Elsevier, vol. 96(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sarah Ben Amor & Fateh Belaid & Ramzi Benkraiem & Boumediene Ramdani & Khaled Guesmi, 2023. "Multi-criteria classification, sorting, and clustering: a bibliometric review and research agenda," Annals of Operations Research, Springer, vol. 325(2), pages 771-793, June.
    2. Qi, Yue & Liao, Kezhi & Liu, Tongyang & Zhang, Yu, 2022. "Originating multiple-objective portfolio selection by counter-COVID measures and analytically instigating robust optimization by mean-parameterized nondominated paths," Operations Research Perspectives, Elsevier, vol. 9(C).
    3. Julio Cezar Soares Silva & Diogo Ferreira de Lima Silva & Luciano Ferreira & Adiel Teixeira de Almeida-Filho, 2022. "A dominance-based rough set approach applied to evaluate the credit risk of sovereign bonds," 4OR, Springer, vol. 20(1), pages 139-164, March.
    4. Panos Xidonas & Ilias Lekkos & Charis Giannakidis & Christos Staikouras, 2023. "Multicriteria security evaluation: does it cost to be traditional?," Annals of Operations Research, Springer, vol. 323(1), pages 301-330, April.
    5. Ecer, Fatih & Pamucar, Dragan, 2022. "A novel LOPCOW‐DOBI multi‐criteria sustainability performance assessment methodology: An application in developing country banking sector," Omega, Elsevier, vol. 112(C).
    6. Gupta, Pankaj & Mittal, Garima & Mehlawat, Mukesh Kumar, 2013. "Expected value multiobjective portfolio rebalancing model with fuzzy parameters," Insurance: Mathematics and Economics, Elsevier, vol. 52(2), pages 190-203.
    7. Kavitha, S. & Satheeshkumar, J. & Amudha, T., 2024. "Multi-label feature selection using q-rung orthopair hesitant fuzzy MCDM approach extended to CODAS," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 222(C), pages 148-173.
    8. Seyed Morteza Hatefi & Hamideh Asadi & Gholamreza Shams & Jolanta Tamošaitienė & Zenonas Turskis, 2021. "Model for the Sustainable Material Selection by Applying Integrated Dempster-Shafer Evidence Theory and Additive Ratio Assessment (ARAS) Method," Sustainability, MDPI, vol. 13(18), pages 1-23, September.
    9. Righi, Marcelo Brutti & Borenstein, Denis, 2018. "A simulation comparison of risk measures for portfolio optimization," Finance Research Letters, Elsevier, vol. 24(C), pages 105-112.
    10. Chun-Chieh Tseng & Jun-Yi Zeng & Min-Liang Hsieh & Chih-Hung Hsu, 2022. "Analysis of Innovation Drivers of New and Old Kinetic Energy Conversion Using a Hybrid Multiple-Criteria Decision-Making Model in the Post-COVID-19 Era: A Chinese Case," Mathematics, MDPI, vol. 10(20), pages 1-25, October.
    11. Amelia Bilbao-Terol & Mar Arenas-Parra & Raquel Quiroga-García & Celia Bilbao-Terol, 2022. "An extended best–worst multiple reference point method: application in the assessment of non-life insurance companies," Operational Research, Springer, vol. 22(5), pages 5323-5362, November.
    12. Dragan Pamučar & Ibrahim Badi & Korica Sanja & Radojko Obradović, 2018. "A Novel Approach for the Selection of Power-Generation Technology Using a Linguistic Neutrosophic CODAS Method: A Case Study in Libya," Energies, MDPI, vol. 11(9), pages 1-25, September.
    13. Željko Stević & Dragan Pamučar & Marko Subotić & Jurgita Antuchevičiene & Edmundas Kazimieras Zavadskas, 2018. "The Location Selection for Roundabout Construction Using Rough BWM-Rough WASPAS Approach Based on a New Rough Hamy Aggregator," Sustainability, MDPI, vol. 10(8), pages 1-27, August.
    14. Engau, Alexander, 2009. "Tradeoff-based decomposition and decision-making in multiobjective programming," European Journal of Operational Research, Elsevier, vol. 199(3), pages 883-891, December.
    15. Zhang, Jingshun & Hu, Jiayi & Wang, Xitong & Fang, Lien & Jin, Yi & Li, Muyang & Liu, Yangqing & Wu, Anna & Wang, Libin & Liu, Ruining & Zhang, Yi & Chen, Faan, 2023. "Quantifying transport safety success at the regional level: A guide to policy and practice on investment for G20," Socio-Economic Planning Sciences, Elsevier, vol. 89(C).
    16. Susmaga, Robert & Szczȩch, Izabela & Zielniewicz, Piotr & Brzezinski, Dariusz, 2023. "MSD-space: Visualizing the inner-workings of TOPSIS aggregations," European Journal of Operational Research, Elsevier, vol. 308(1), pages 229-242.
    17. Iakovou, E. & Moussiopoulos, N. & Xanthopoulos, A. & Achillas, Ch. & Michailidis, N. & Chatzipanagioti, M. & Koroneos, C. & Bouzakis, K.-D. & Kikis, V., 2009. "A methodological framework for end-of-life management of electronic products," Resources, Conservation & Recycling, Elsevier, vol. 53(6), pages 329-339.
    18. Fernando A. F. Ferreira & Sérgio P. Santos, 2021. "Two decades on the MACBETH approach: a bibliometric analysis," Annals of Operations Research, Springer, vol. 296(1), pages 901-925, January.
    19. Abastante, Francesca & Corrente, Salvatore & Greco, Salvatore & Ishizaka, Alessio & Lami, Isabella M., 2018. "Choice architecture for architecture choices: Evaluating social housing initiatives putting together a parsimonious AHP methodology and the Choquet integral," Land Use Policy, Elsevier, vol. 78(C), pages 748-762.
    20. Sen Guo & Wenyue Zhang & Xiao Gao, 2020. "Business Risk Evaluation of Electricity Retail Company in China Using a Hybrid MCDM Method," Sustainability, MDPI, vol. 12(5), pages 1-21, March.

    More about this item

    Keywords

    BWM; MOORA; MCDM; MCDA; Investment funds;
    All these keywords.

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:operea:v:24:y:2024:i:3:d:10.1007_s12351-024-00817-w. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.