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Optimization of a Portfolio of Investment Projects: A Real Options Approach Using the Omega Measure

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  • Javier G. Castro

    (Department of Production Engineering, Technology Center, Universidade Federal de Santa Catarina—UFSC, Florianópolis 88040-900, Brazil)

  • Edison A. Tito

    (Department of Management, IAG Business School, Pontifical Catholic University of Rio de Janeiro—PUC-Rio, Rio de Janeiro 22451-045, Brazil)

  • Luiz E. Brandão

    (Department of Management, IAG Business School, Pontifical Catholic University of Rio de Janeiro—PUC-Rio, Rio de Janeiro 22451-045, Brazil)

Abstract

Investment decisions usually involve the assessment of more than one financial asset or investment project (real asset). The most appropriate way to analyze the viability of a real asset is not to study it in isolation but as part of a portfolio with correlations between the input variables of the projects. This study proposes an optimization methodology for a portfolio of investment projects with real options based on maximizing the Omega performance measure. The classic portfolio optimization methodology uses the Sharpe ratio as the objective function, which is a function of the mean-variance of the returns of the portfolio distribution. The advantage of using Omega as an objective function is that it takes into account all moments of the portfolio’s distribution of returns or net present values (NPVs), not restricting the analysis to its mean and variance. We present an example to illustrate the proposed methodology, using the Monte Carlo simulation as the main tool due to its high flexibility in modeling uncertainties. The results show that the best risk-return ratio is obtained by optimizing the Omega measure.

Suggested Citation

  • Javier G. Castro & Edison A. Tito & Luiz E. Brandão, 2021. "Optimization of a Portfolio of Investment Projects: A Real Options Approach Using the Omega Measure," JRFM, MDPI, vol. 14(11), pages 1-17, November.
  • Handle: RePEc:gam:jjrfmx:v:14:y:2021:i:11:p:530-:d:674068
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    References listed on IDEAS

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    1. Maier, Sebastian & Pflug, Georg C. & Polak, John W., 2020. "Valuing portfolios of interdependent real options under exogenous and endogenous uncertainties," European Journal of Operational Research, Elsevier, vol. 285(1), pages 133-147.
    2. van Bekkum, Sjoerd & Pennings, Enrico & Smit, Han, 2009. "A real options perspective on R&D portfolio diversification," Research Policy, Elsevier, vol. 38(7), pages 1150-1158, September.
    3. Mansini, Renata & Ogryczak, Wlodzimierz & Speranza, M. Grazia, 2014. "Twenty years of linear programming based portfolio optimization," European Journal of Operational Research, Elsevier, vol. 234(2), pages 518-535.
    4. Avinash K. Dixit & Robert S. Pindyck, 1994. "Investment under Uncertainty," Economics Books, Princeton University Press, edition 1, number 5474.
    5. James L. Smith and Rex Thompson, 2008. "Managing a Portfolio of Real options: Sequential Exploration of Dependent Prospects," The Energy Journal, International Association for Energy Economics, vol. 0(Special I), pages 43-62.
    6. Medaglia, Andres L. & Graves, Samuel B. & Ringuest, Jeffrey L., 2007. "A multiobjective evolutionary approach for linearly constrained project selection under uncertainty," European Journal of Operational Research, Elsevier, vol. 179(3), pages 869-894, June.
    7. James E. Smith, 2005. "Alternative Approaches for Solving Real-Options Problems," Decision Analysis, INFORMS, vol. 2(2), pages 89-102, June.
    8. Hassanzadeh, Farhad & Nemati, Hamid & Sun, Minghe, 2014. "Robust optimization for interactive multiobjective programming with imprecise information applied to R&D project portfolio selection," European Journal of Operational Research, Elsevier, vol. 238(1), pages 41-53.
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