IDEAS home Printed from https://ideas.repec.org/a/eee/jomega/v35y2007i1p75-88.html
   My bibliography  Save this article

An interactive three-stage model for mutual funds portfolio selection

Author

Listed:
  • Perez Gladish, B.
  • Jones, D.F.
  • Tamiz, M.
  • Bilbao Terol, A.

Abstract

The aim of this work is to be a useful instrument for helping finance practitioners on the selection of suitable mutual fund portfolios. The portfolio selection problem is characterized by imprecision and/or vagueness inherent in the required data and more generally, in the context where investors have to make decisions. In order to mitigate these problems, a three stage model has been proposed based on a multi-index model and considering several market scenarios described in an imprecise way by an expert. The proposed fuzzy model allows the Decision Maker to select, by means of an outranking method, a suitable portfolio taking into account the uncertainty related to the market scenarios and the imprecision and/or vagueness associated with the model data.

Suggested Citation

  • Perez Gladish, B. & Jones, D.F. & Tamiz, M. & Bilbao Terol, A., 2007. "An interactive three-stage model for mutual funds portfolio selection," Omega, Elsevier, vol. 35(1), pages 75-88, February.
    • Handle: RePEc:eee:jomega:v:35:y:2007:i:1:p:75-88
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0305-0483(05)00062-9
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    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. Elton, Edwin J & Gruber, Martin J & Urich, Thomas J, 1978. "Are Betas Best?," Journal of Finance, American Finance Association, vol. 33(5), pages 1375-1384, December.
    2. Markowitz, Harry M & Perold, Andre F, 1981. "Portfolio Analysis with Factors and Scenarios," Journal of Finance, American Finance Association, vol. 36(4), pages 871-877, September.
    3. P. L. Yu, 1973. "A Class of Solutions for Group Decision Problems," Management Science, INFORMS, vol. 19(8), pages 936-946, April.
    4. Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, March.
    5. Kane, Stephen, 2004. "Scientific methods in finance," International Review of Financial Analysis, Elsevier, vol. 13(1), pages 105-118.
    6. Tanaka, Hideo & Guo, Peijun, 1999. "Portfolio selection based on upper and lower exponential possibility distributions," European Journal of Operational Research, Elsevier, vol. 114(1), pages 115-126, April.
    7. Arenas Parra, M. & Bilbao Terol, A. & Perez Gladish, B. & Rodriguez Uria, M. V., 2005. "Solving a multiobjective possibilistic problem through compromise programming," European Journal of Operational Research, Elsevier, vol. 164(3), pages 748-759, August.
    8. Arenas Parra, M. & Bilbao Terol, A. & Rodriguez Uria, M. V., 1999. "Solving the multiobjective possibilistic linear programming problem," European Journal of Operational Research, Elsevier, vol. 117(1), pages 175-182, August.
    9. Shing, Chue & Nagasawa, Hiroyuki, 1999. "Interactive decision system in stochastic multiobjective portfolio selection," International Journal of Production Economics, Elsevier, vol. 60(1), pages 187-193, April.
    10. Srichander Ramaswamy, 1998. "Portfolio selection using fuzzy decision theory," BIS Working Papers 59, Bank for International Settlements.
    11. Various, 1973. "Conference Programs," NBER Chapters, in: The New Realities of the Business Cycle, pages 126-131, National Bureau of Economic Research, Inc.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Xu, Wangtu & Lin, Weihua, 2016. "Selecting the public transit projects with PCA-DP technique: The example of Xiamen City," Transport Policy, Elsevier, vol. 46(C), pages 56-71.
    2. D. Pla-Santamaria & M. Bravo, 2013. "Portfolio optimization based on downside risk: a mean-semivariance efficient frontier from Dow Jones blue chips," Annals of Operations Research, Springer, vol. 205(1), pages 189-201, May.
    3. Aouni, Belaid & Colapinto, Cinzia & La Torre, Davide, 2014. "Financial portfolio management through the goal programming model: Current state-of-the-art," European Journal of Operational Research, Elsevier, vol. 234(2), pages 536-545.
    4. Cinzia Colapinto & Raja Jayaraman & Simone Marsiglio, 2017. "Multi-criteria decision analysis with goal programming in engineering, management and social sciences: a state-of-the art review," Annals of Operations Research, Springer, vol. 251(1), pages 7-40, April.
    5. Ballestero, Enrique & Bravo, Mila & Pérez-Gladish, Blanca & Arenas-Parra, Mar & Plà-Santamaria, David, 2012. "Socially Responsible Investment: A multicriteria approach to portfolio selection combining ethical and financial objectives," European Journal of Operational Research, Elsevier, vol. 216(2), pages 487-494.
    6. Li, Jun & Xu, Jiuping, 2009. "A novel portfolio selection model in a hybrid uncertain environment," Omega, Elsevier, vol. 37(2), pages 439-449, April.
    7. Bilbao-Terol, Amelia & Arenas-Parra, Mar & Cañal-Fernández, Verónica & Antomil-Ibias, José, 2014. "Using TOPSIS for assessing the sustainability of government bond funds," Omega, Elsevier, vol. 49(C), pages 1-17.
    8. Cinzia Colapinto & Davide Torre & Belaid Aouni, 2019. "Goal programming for financial portfolio management: a state-of-the-art review," Operational Research, Springer, vol. 19(3), pages 717-736, September.
    9. Juana Rivera-Lirio & María Muñoz-Torres, 2010. "The Effectiveness of the Public Support Policies for the European Industry Financing as a Contribution to Sustainable Development," Journal of Business Ethics, Springer, vol. 94(4), pages 489-515, July.

    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. Arenas Parra, M. & Bilbao Terol, A. & Rodriguez Uria, M. V., 2001. "A fuzzy goal programming approach to portfolio selection," European Journal of Operational Research, Elsevier, vol. 133(2), pages 287-297, January.
    2. A Bilbao & M Arenas & M Jiménez & B Perez Gladish & M V Rodríguez, 2006. "An extension of Sharpe's single-index model: portfolio selection with expert betas," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(12), pages 1442-1451, December.
    3. Bilbao, A. & Arenas, M. & Rodriguez, M.V. & Antomil, J., 2007. "On constructing expert Betas for single-index model," European Journal of Operational Research, Elsevier, vol. 183(2), pages 827-847, December.
    4. Tsaur, Ruey-Chyn, 2013. "Fuzzy portfolio model with different investor risk attitudes," European Journal of Operational Research, Elsevier, vol. 227(2), pages 385-390.
    5. Liu, Yong-Jun & Zhang, Wei-Guo, 2015. "A multi-period fuzzy portfolio optimization model with minimum transaction lots," European Journal of Operational Research, Elsevier, vol. 242(3), pages 933-941.
    6. Domenech, B. & Ferrer-Martí, L. & Pastor, R., 2015. "Hierarchical methodology to optimize the design of stand-alone electrification systems for rural communities considering technical and social criteria," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 182-196.
    7. Masafumi Nakano & Akihiko Takahashi & Soichiro Takahashi, 2017. "Robust Technical Trading with Fuzzy Knowledge-based Systems," CIRJE F-Series CIRJE-F-1053, CIRJE, Faculty of Economics, University of Tokyo.
    8. Huang, Xiaoxia, 2007. "Two new models for portfolio selection with stochastic returns taking fuzzy information," European Journal of Operational Research, Elsevier, vol. 180(1), pages 396-405, July.
    9. Tee, Kai-Hong, 2009. "The effect of downside risk reduction on UK equity portfolios included with Managed Futures Funds," International Review of Financial Analysis, Elsevier, vol. 18(5), pages 303-310, December.
    10. Madlener, Reinhard & Glensk, Barbara & Weber, Veronika, 2011. "Fuzzy Portfolio Optimization of Onshore Wind Power Plants," FCN Working Papers 10/2011, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN), revised Jul 2014.
    11. Chang, C-L. & McAleer, M.J. & Wong, W.-K., 2015. "Informatics, Data Mining, Econometrics and Financial Economics: A Connection," Econometric Institute Research Papers EI2015-34, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    12. Koronakos, Gregory & Sotiros, Dimitris & Despotis, Dimitris K. & Kritikos, Manolis N., 2022. "Fair efficiency decomposition in network DEA: A compromise programming approach," Socio-Economic Planning Sciences, Elsevier, vol. 79(C).
    13. Guadalajara-Olmeda, N. & Rua-Aguilar, M. Jose, 2015. "Programación y compromiso. Cómo equilibrar dos objetivos, económico y ambiental, en una promoción de viviendas," Economia Agraria y Recursos Naturales, Spanish Association of Agricultural Economists, vol. 15(01).
    14. Zhang, Wei-Guo & Zhang, Xi-Li & Xiao, Wei-Lin, 2009. "Portfolio selection under possibilistic mean-variance utility and a SMO algorithm," European Journal of Operational Research, Elsevier, vol. 197(2), pages 693-700, September.
    15. Smimou, K. & Bector, C.R. & Jacoby, G., 2007. "A subjective assessment of approximate probabilities with a portfolio application," Research in International Business and Finance, Elsevier, vol. 21(2), pages 134-160, June.
    16. Fang, Yong & Lai, K.K. & Wang, Shou-Yang, 2006. "Portfolio rebalancing model with transaction costs based on fuzzy decision theory," European Journal of Operational Research, Elsevier, vol. 175(2), pages 879-893, December.
    17. Rodríguez, Beatriz & Molina, Julián & Pérez, Fátima & Caballero, Rafael, 2012. "Interactive design of personalised tourism routes," Tourism Management, Elsevier, vol. 33(4), pages 926-940.
    18. Li, Hua & Bai, Zhidong & Wong, Wing-Keung & McAleer, Michael, 2022. "Spectrally-Corrected Estimation for High-Dimensional Markowitz Mean-Variance Optimization," Econometrics and Statistics, Elsevier, vol. 24(C), pages 133-150.
    19. Mousavi, M. & Gitinavard, H. & Mousavi, S.M., 2017. "A soft computing based-modified ELECTRE model for renewable energy policy selection with unknown information," Renewable and Sustainable Energy Reviews, Elsevier, vol. 68(P1), pages 774-787.
    20. Masafumi Nakano & Akihiko Takahashi & Soichiro Takahashi, 2017. "Fuzzy Logic-based Portfolio Selection with Particle Filtering and Anomaly Detection," CIRJE F-Series CIRJE-F-1037, CIRJE, Faculty of Economics, University of Tokyo.

    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:eee:jomega:v:35:y:2007:i:1:p:75-88. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/375/description#description .

    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.