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A Probabilistic Alternative Approach to Optimal Project Profitability Based on the Value-at-Risk

Author

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  • Yonggu Kim

    (Graduate Institute of Ferrous Technology & Graduate School of Engineering Mastership, Pohang University of Science and Technology, 77, Cheongam-ro, Nam-gu, Pohang-si, Gyeongsangbuk-do 37673, Korea)

  • Eul-Bum Lee

    (Graduate Institute of Ferrous Technology & Graduate School of Engineering Mastership, Pohang University of Science and Technology, 77, Cheongam-ro, Nam-gu, Pohang-si, Gyeongsangbuk-do 37673, Korea)

Abstract

This paper focuses on an investment decision-making process for sustainable development based on the profitability impact factors for overseas projects. Investors prefer to use the discounted cash-flow method. Although this method is simple and straightforward, its critical weakness is its inability to reflect the factor volatility associated with the project evaluation. To overcome this weakness, the Value-at-Risk method is used to apply the volatility of the profitability impact factors, thereby reflecting the risks and establishing decision-making criteria for risk-averse investors. Risk-averse investors can lose relatively acceptable investment opportunities to risk-neutral or risk-amenable investors due to strict investment decision-making criteria. To overcome this problem, critical factors are selected through a Monte Carlo simulation and a sensitivity analysis, and solutions to the critical-factor problems are then found by using the Theory of Inventive Problem Solving and a business version of the Project Definition Rating Index. This study examines the process of recovering investment opportunities with projects that are investment feasible and that have been rejected when applying the criterion of the Value-at-Risk method. To do this, a probabilistic alternative approach is taken. To validate this methodology, the proposed framework for an improved decision-making process is demonstrated using two actual overseas projects of a Korean steel-making company.

Suggested Citation

  • Yonggu Kim & Eul-Bum Lee, 2018. "A Probabilistic Alternative Approach to Optimal Project Profitability Based on the Value-at-Risk," Sustainability, MDPI, vol. 10(3), pages 1-24, March.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:3:p:747-:d:135418
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    Cited by:

    1. Dong-Hyun Kim & Eul-Bum Lee & In-Hyeo Jung & Douglas Alleman, 2019. "The Efficacy of the Tolling Model’s Ability to Improve Project Profitability on International Steel Plants," Energies, MDPI, vol. 12(7), pages 1-18, March.
    2. Jae-Il Yoo & Eul-Bum Lee & Jin-Woo Choi, 2018. "Balancing Project Financing and Mezzanine Project Financing with Option Value to Mitigate Sponsor’s Risks for Overseas Investment Projects," Sustainability, MDPI, vol. 10(5), pages 1-21, May.

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