IDEAS home Printed from https://ideas.repec.org/a/dug/actaec/y2014i2p193-204.html
   My bibliography  Save this article

Tactical Assets Allocation: Evidence from the Nigerian Banking Industry

Author

Listed:
  • Adedoyin Isola Lawal

    (Landmark University)

Abstract

The core of portfolio selection theory centers on striking a balance between risk-return trade-off of a given investment layout so as to maximize benefits. Literature reveals that portfolio selection or asset allocation problems often involve the use of mathematical programming in propounding solution. This paper uses a blend of simultaneous equation and graphical approach to linear programming algorithm to help solve investors‘ problem in allocating assets among various alternatives when faced with problems associated with risk-return trade-off. We strongly suggest that practioners as well as policy makers use this approach to obtain optimal solution when faced with decision making given various investment alternatives.

Suggested Citation

  • Adedoyin Isola Lawal, 2014. "Tactical Assets Allocation: Evidence from the Nigerian Banking Industry," Acta Universitatis Danubius. OEconomica, Danubius University of Galati, issue 10(2), pages 193-204, April.
    • Handle: RePEc:dug:actaec:y:2014:i:2:p:193-204
    as

    Download full text from publisher

    File URL: http://journals.univ-danubius.ro/index.php/oeconomica/article/view/2204/2094
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Andrea Consiglio & Alessandro Staino, 2012. "A stochastic programming model for the optimal issuance of government bonds," Annals of Operations Research, Springer, vol. 193(1), pages 159-172, March.
    2. Date, P. & Canepa, A. & Abdel-Jawad, M., 2011. "A mixed integer linear programming model for optimal sovereign debt issuance," European Journal of Operational Research, Elsevier, vol. 214(3), pages 749-758, November.
    3. PInar, Mustafa Ç. & Salih, AslIhan & CamcI, Ahmet, 2010. "Expected gain-loss pricing and hedging of contingent claims in incomplete markets by linear programming," European Journal of Operational Research, Elsevier, vol. 201(3), pages 770-785, March.
    4. Date, Paresh & Wang, Chieh, 2009. "Linear Gaussian affine term structure models with unobservable factors: Calibration and yield forecasting," European Journal of Operational Research, Elsevier, vol. 195(1), pages 156-166, May.
    5. Massimiliano Adamo & Anna Lisa Amadori & Massimo Bernaschi & Claudia La Chioma & Alessia Marigo & Benedetto Piccoli & Simone Sbaraglia & Adamo Uboldi & Davide Vergni & Paola Fabbri & Davide Iacovoni &, 2004. "Optimal Strategies For The Issuances Of Public Debt Securities," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 7(07), pages 805-822.
    6. Tehrani Nejad Moghaddam, Alireza & Michelot, Christian, 2009. "A contribution to the linear programming approach to joint cost allocation: Methodology and application," European Journal of Operational Research, Elsevier, vol. 197(3), pages 999-1011, September.
    7. 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.
    8. Ghahtarani, Alireza & Najafi, Amir Abbas, 2013. "Robust goal programming for multi-objective portfolio selection problem," Economic Modelling, Elsevier, vol. 33(C), pages 588-592.
    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. Yusuf Olatunji Oyedeko & Olusola Segun Kolawole & Regina Samson & Olena Voloshyna, 2023. "Moderating Effect of Tactical Asset Allocation on the Risk-Return Relationship in the Nigerian Stock Market," Oblik i finansi, Institute of Accounting and Finance, issue 2, pages 83-91, June.

    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. Mila Bravo & Dylan Jones & David Pla-Santamaria & Francisco Salas-Molina, 2022. "Encompassing statistically unquantifiable randomness in goal programming: an application to portfolio selection," Operational Research, Springer, vol. 22(5), pages 5685-5706, November.
    2. Dimitris Andriosopoulos & Michalis Doumpos & Panos M. Pardalos & Constantin Zopounidis, 2019. "Computational approaches and data analytics in financial services: A literature review," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 70(10), pages 1581-1599, October.
    3. Date, P. & Canepa, A. & Abdel-Jawad, M., 2011. "A mixed integer linear programming model for optimal sovereign debt issuance," European Journal of Operational Research, Elsevier, vol. 214(3), pages 749-758, November.
    4. Christopher Cameron, 2018. "Visualizing Treasury Issuance Strategy," Papers 1802.03376, arXiv.org, revised Feb 2020.
    5. Mónica García-Melón & Blanca Pérez-Gladish & Tomás Gómez-Navarro & Paz Mendez-Rodriguez, 2016. "Assessing mutual funds’ corporate social responsibility: a multistakeholder-AHP based methodology," Annals of Operations Research, Springer, vol. 244(2), pages 475-503, September.
    6. Jang Ho Kim & Yongjae Lee & Woo Chang Kim & Frank J. Fabozzi, 2022. "Goal-based investing based on multi-stage robust portfolio optimization," Annals of Operations Research, Springer, vol. 313(2), pages 1141-1158, June.
    7. Tomasz R. Bielecki & Igor Cialenco & Ismail Iyigunler & Rodrigo Rodriguez, 2012. "Dynamic Conic Finance: Pricing and Hedging in Market Models with Transaction Costs via Dynamic Coherent Acceptability Indices," Papers 1205.4790, arXiv.org, revised Jun 2013.
    8. Bugarinovic, Mirjana & Boskovic, Branislav, 2015. "A systems approach to access charges in unbundling railways," European Journal of Operational Research, Elsevier, vol. 240(3), pages 848-860.
    9. Florian Methling & Rüdiger Nitzsch, 2019. "Thematic portfolio optimization: challenging the core satellite approach," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 33(2), pages 133-154, June.
    10. Panos Xidonas & Eric Essner, 2024. "On ESG Portfolio Construction: A Multi-Objective Optimization Approach," Computational Economics, Springer;Society for Computational Economics, vol. 63(1), pages 21-45, January.
    11. Muñoz, Fernando, 2016. "Cash flow timing skills of socially responsible mutual fund investors," International Review of Financial Analysis, Elsevier, vol. 48(C), pages 110-124.
    12. Trinks, Arjan & Ibikunle, Gbenga & Mulder, Machiel & Scholtens, Bert, 2017. "Greenhouse Gas Emissions Intensity and the Cost of Capital," Research Report 17017-EEF, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
    13. Hanks, Robert W. & Weir, Jeffery D. & Lunday, Brian J., 2017. "Robust goal programming using different robustness echelons via norm-based and ellipsoidal uncertainty sets," European Journal of Operational Research, Elsevier, vol. 262(2), pages 636-646.
    14. Farshad Noravesh & Kristiaan Kerstens, 2022. "Some connections between higher moments portfolio optimization methods," Papers 2201.00205, arXiv.org.
    15. Constantin Zopounidis & Michael Doumpos, 2013. "Rejoinder on: Multicriteria decision systems for financial problems," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 21(2), pages 282-286, July.
    16. Clara Calvo & Carlos Ivorra & Vicente Liern, 2016. "Fuzzy portfolio selection with non-financial goals: exploring the efficient frontier," Annals of Operations Research, Springer, vol. 245(1), pages 31-46, October.
    17. Moreno, Manuel & Platania, Federico, 2015. "A cyclical square-root model for the term structure of interest rates," European Journal of Operational Research, Elsevier, vol. 241(1), pages 109-121.
    18. Li, Haitao & Ye, Xiaoxia & Yu, Fan, 2020. "Unifying Gaussian dynamic term structure models from a Heath–Jarrow–Morton perspective," European Journal of Operational Research, Elsevier, vol. 286(3), pages 1153-1167.
    19. Utz, Sebastian & Wimmer, Maximilian & Steuer, Ralph E., 2015. "Tri-criterion modeling for constructing more-sustainable mutual funds," European Journal of Operational Research, Elsevier, vol. 246(1), pages 331-338.
    20. Francisco Salas-Molina & Juan Antonio Rodr'iguez Aguilar & Filippo Bistaffa, 2020. "Shared value economics: an axiomatic approach," Papers 2006.00581, arXiv.org.

    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:dug:actaec:y:2014:i:2:p:193-204. 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: Daniela Robu (email available below). General contact details of provider: https://edirc.repec.org/data/fedanro.html .

    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.