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Explicit Value at Risk Goal Function in Bi-Level Portfolio Problem for Financial Sustainability

Author

Listed:
  • Todor Stoilov

    (Institute of Information and Communication Technologies, Bulgarian Academy of Sciences, 1113 Sofia, Bulgaria)

  • Krasimira Stoilova

    (Institute of Information and Communication Technologies, Bulgarian Academy of Sciences, 1113 Sofia, Bulgaria)

  • Miroslav Vladimirov

    (Management and Administration, University of Economics-Varna, 9002 Varna, Bulgaria)

Abstract

The mean-variance (MV) portfolio optimization targets higher return for investment period despite the unknown stochastic behavior of the future asset returns. That is why a risk is explicitly considering, quantified by algebraic characteristics of volatilities and co-variances. A new probabilistic definition of portfolio risk is the Value at Risk (VaR). The paper makes explicit inclusion and minimization of VaR as a quantitative measure of financial sustainability of a portfolio problem. Thus, the portfolio weights as problem solutions will respect not only the MV requirements for risk and return, but also the additional minimization of risk defined by VaR level. The portfolio problem is defined in a new, bi-level form. The upper level minimizes and evaluates the VaR value. The lower level evaluates the optimal assets weights by minimizing portfolio risk and maximizing the return in MV form. The bi-level model allows to have extended set of portfolio solutions with the portfolio weights and the value of VaR. Graphical interpretation of this bi-level definition of the portfolio problem explains the differences with the MV portfolio definition. Thus, the bi-level portfolio problem evaluates the optimal weights, which makes maximization of portfolio return and minimization of the risk in its algebraic and probabilistic form of definition.

Suggested Citation

  • Todor Stoilov & Krasimira Stoilova & Miroslav Vladimirov, 2021. "Explicit Value at Risk Goal Function in Bi-Level Portfolio Problem for Financial Sustainability," Sustainability, MDPI, vol. 13(4), pages 1-14, February.
  • Handle: RePEc:gam:jsusta:v:13:y:2021:i:4:p:2315-:d:502840
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    References listed on IDEAS

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    1. Lam Weng Hoe & Jaaman Saiful Hafizah & Isa Zaidi, 2010. "An empirical comparison of different risk measures in portfolio optimization," Business and Economic Horizons (BEH), Prague Development Center, vol. 1(1), pages 39-45, April.
    2. Keith Kuester & Stefan Mittnik & Marc S. Paolella, 2006. "Value-at-Risk Prediction: A Comparison of Alternative Strategies," Journal of Financial Econometrics, Oxford University Press, vol. 4(1), pages 53-89.
    3. P. Bonami & M. A. Lejeune, 2009. "An Exact Solution Approach for Portfolio Optimization Problems Under Stochastic and Integer Constraints," Operations Research, INFORMS, vol. 57(3), pages 650-670, June.
    4. James Ming Chen, 2018. "On Exactitude in Financial Regulation: Value-at-Risk, Expected Shortfall, and Expectiles," Risks, MDPI, vol. 6(2), pages 1-28, June.
    5. Hiroshi Konno & Hiroaki Yamazaki, 1991. "Mean-Absolute Deviation Portfolio Optimization Model and Its Applications to Tokyo Stock Market," Management Science, INFORMS, vol. 37(5), pages 519-531, May.
    6. Todor Stoilov & Krasimira petrova Stoilova & Miroslav Vladimirov, 2020. "Saving Time in Portfolio Optimization on Financial Markets," Chapters, in: Fausto Pedro Garcia Marquez (ed.), Application of Decision Science in Business and Management, IntechOpen.
    7. Lwin, Khin T. & Qu, Rong & MacCarthy, Bart L., 2017. "Mean-VaR portfolio optimization: A nonparametric approach," European Journal of Operational Research, Elsevier, vol. 260(2), pages 751-766.
    8. Pierre Bonami & Miguel A. Lejeune, 2009. "An Exact Solution Approach for Integer Constrained Portfolio Optimization Problems Under Stochastic Constraints," Post-Print hal-00421756, HAL.
    9. Seyoung Park & Eun Ryung Lee & Sungchul Lee & Geonwoo Kim, 2019. "Dantzig Type Optimization Method with Applications to Portfolio Selection," Sustainability, MDPI, vol. 11(11), pages 1-32, June.
    10. Zhiping Chen & Xinkai Zhuang & Jia Liu, 2019. "A Sustainability-Oriented Enhanced Indexation Model with Regime Switching and Cardinality Constraint," Sustainability, MDPI, vol. 11(15), pages 1-14, July.
    11. Zongxin Li & Xinge Li & Yongchang Hui & Wing-Keung Wong, 2018. "Maslow Portfolio Selection for Individuals with Low Financial Sustainability," Sustainability, MDPI, vol. 10(4), pages 1-11, April.
    12. Benita, Francisco & López-Ramos, Francisco & Nasini, Stefano, 2019. "A bi-level programming approach for global investment strategies with financial intermediation," European Journal of Operational Research, Elsevier, vol. 274(1), pages 375-390.
    13. Deng, Xiao-Tie & Li, Zhong-Fei & Wang, Shou-Yang, 2005. "A minimax portfolio selection strategy with equilibrium," European Journal of Operational Research, Elsevier, vol. 166(1), pages 278-292, October.
    14. Hoe, Lam Weng & Saiful Hafizah, Jaaman & Zaidi, Isa, 2010. "An empirical comparison of different risk measures in portfolio optimization," Business and Economic Horizons (BEH), Prague Development Center (PRADEC), vol. 1(1), pages 1-7, April.
    15. Polak, George G. & Rogers, David F. & Sweeney, Dennis J., 2010. "Risk management strategies via minimax portfolio optimization," European Journal of Operational Research, Elsevier, vol. 207(1), pages 409-419, November.
    16. Kanwal Iqbal Khan & Syed M. Waqar Azeem Naqvi & Muhammad Mudassar Ghafoor & Rana Shahid Imdad Akash, 2020. "Sustainable Portfolio Optimization with Higher-Order Moments of Risk," Sustainability, MDPI, vol. 12(5), pages 1-14, March.
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