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Contingency estimating using option pricing theory: closing the gap between theory and practice

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  • R. David Espinoza

Abstract

Valuation of contingency budgets for construction projects considering technical and market uncertainties as well as the time it takes to execute the project can be estimated using option pricing theory. Although option pricing theory provides an attractive framework for calculation of contingency budgets, it typically results in complex highly non-linear partial differential equations that require the use of numerical algorithms and computer intensive techniques, thus making it difficult for practitioners to adopt this valuation technique. An attempt to bridge the gap between theory and practice is made by proposing an equivalent linear stochastic process to model the complex non-linear random variation with time of the technical and market uncertainty for projects. The approximation allows estimation of contingency budgets using either closed-form solutions for pricing options, or the intuitive binomial approach. To validate the proposed equivalent linear solution, its results were compared to the solution to the non-linear partial differential equation that governs the pricing of contingency budgets solved by Monte Carlo simulations. A parametric study of the error shows that the proposed approximation to estimate contingency budgets compares well with the results obtained from simulation. The main advantages of the proposed solution are its simplicity and straightforward implementation.

Suggested Citation

  • R. David Espinoza, 2011. "Contingency estimating using option pricing theory: closing the gap between theory and practice," Construction Management and Economics, Taylor & Francis Journals, vol. 29(9), pages 913-927, July.
  • Handle: RePEc:taf:conmgt:v:29:y:2011:i:9:p:913-927
    DOI: 10.1080/01446193.2011.610328
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    Cited by:

    1. Espinoza, R. David & Rojo, Javier, 2017. "Towards sustainable mining (Part I): Valuing investment opportunities in the mining sector," Resources Policy, Elsevier, vol. 52(C), pages 7-18.
    2. Dou, Shi-quan & Liu, Jiang-yi & Xiao, Jian-zhong & Pan, Wen, 2020. "Economic feasibility valuing of deep mineral resources based on risk analysis: Songtao manganese ore - China case study," Resources Policy, Elsevier, vol. 66(C).
    3. Espinoza, R. David & Morris, Jeremy W.F., 2017. "Towards sustainable mining (part II): Accounting for mine reclamation and post reclamation care liabilities," Resources Policy, Elsevier, vol. 52(C), pages 29-38.
    4. Tatiana Ponomarenko & Eugene Marin & Sergey Galevskiy, 2022. "Economic Evaluation of Oil and Gas Projects: Justification of Engineering Solutions in the Implementation of Field Development Projects," Energies, MDPI, vol. 15(9), pages 1-22, April.
    5. João Adelino Ribeiro & Paulo Jorge Pereira & Elísio Brandão, 2012. "Reaching an Optimal Mark-Up Bid through the Valuation of the Option to Sign the Contract by the Successful Bidder," CEF.UP Working Papers 1201, Universidade do Porto, Faculdade de Economia do Porto.

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