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Contrasting two approaches in real options valuation: contingent claims versus dynamic programming

Author

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  • Margaret Insley

    (Department of Economics, University of Waterloo)

  • Tony Wirjanto

    (Department of Economics, University of Waterloo)

Abstract

This paper compares two well-known approaches for valuing a risky investment using real options theory: contingent claims (CC) with risk neutral valuation and dynamic programming (DP) using a constant risk adjusted discount rate. Both approaches have been used in valuing forest assets. A proof is presented which shows that, except under certain restrictive assumptions; DP using a constant discount rate and CC will not yield the same answers for investment value. A few special cases are considered for which CC and DP with a constant discount rate are consistent with each other. An optimal tree harvesting example is presented to illustrate that the values obtained using the two approaches can differ whcn we depart from these special cases to a more realistic scenariio. Further, the implied risk adjusted discount rate calculated from CC is found to vary with the stochastic state variable and stand age. We conclude that for real options problems the CC approach should be used.

Suggested Citation

  • Margaret Insley & Tony Wirjanto, 2008. "Contrasting two approaches in real options valuation: contingent claims versus dynamic programming," Working Papers 08002, University of Waterloo, Department of Economics.
    • Handle: RePEc:wat:wpaper:08002
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    Cited by:

    1. Ewald, Christian Oliver & Taub, Bart, 2022. "Real options, risk aversion and markets: A corporate finance perspective," Journal of Corporate Finance, Elsevier, vol. 72(C).
    2. Galay, Gregory, 2018. "The impact of spatial price differences on oil sands investments," Energy Economics, Elsevier, vol. 69(C), pages 170-184.
    3. Chen, Shan & Insley, Margaret, 2012. "Regime switching in stochastic models of commodity prices: An application to an optimal tree harvesting problem," Journal of Economic Dynamics and Control, Elsevier, vol. 36(2), pages 201-219.
    4. Abdullah Almansour and Margaret Insley, 2016. "The Impact of Stochastic Extraction Cost on the Value of an Exhaustible Resource: An Application to the Alberta Oil Sands," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2).
    5. Davis, Graham A. & Cairns, Robert D., 2012. "Good timing: The economics of optimal stopping," Journal of Economic Dynamics and Control, Elsevier, vol. 36(2), pages 255-265.
    6. Chang, Sun Joseph & Zhang, Fan, 2023. "Active timber management by outsourcing stumpage price uncertainty with the American put option," Forest Policy and Economics, Elsevier, vol. 154(C).
    7. Insley, Margaret & Lei, Manle, 2007. "Hedges and Trees: Incorporating Fire Risk into Optimal Decisions in Forestry Using a No-Arbitrage Approach," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 32(3), pages 1-23, December.
    8. Graeme Guthrie & Dinesh Kumareswaran, 2009. "Carbon Subsidies, Taxes and Optimal Forest Management," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 43(2), pages 275-293, June.
    9. Di Corato, Luca & Gazheli, Ardjan & Lagerkvist, Carl-Johan, 2013. "Investing in energy forestry under uncertainty," Forest Policy and Economics, Elsevier, vol. 34(C), pages 56-64.
    10. Luca Di Corato & Tsegaye Ginbo, 2020. "Climate change and coffee farm relocation in Ethiopia: a real-options approach," Working Papers 2020:02, Department of Economics, University of Venice "Ca' Foscari".

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    Keywords

    optimal tree harvesting; real options; contingent claims; dynamic programming;
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