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Real options valuation principle in the multi-period base-stock problem

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  • Berling, Peter

Abstract

This paper analyzes the multi-period base-stock problem where there is a financial risk associated with a stochastic demand. For the single-period problem, it is known that the optimal inventory policy can be obtained with the Black and Scholes option pricing formula. This paper pushes the analysis further by applying the options valuation framework to the multi-period problem and presenting an algorithm for finding the optimal inventory policy. A computational study indicates that the effect of systematic risk is typically negligible (as for the single-period problem). Therefore, it can be concluded that systematic risk in demand is of little importance for optimal inventory control.

Suggested Citation

  • Berling, Peter, 2008. "Real options valuation principle in the multi-period base-stock problem," Omega, Elsevier, vol. 36(6), pages 1086-1095, December.
    • Handle: RePEc:eee:jomega:v:36:y:2008:i:6:p:1086-1095
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    Cited by:

    1. Ni, Jian & Chu, Lap-Keung & Yen, Benjamin P.C., 2016. "Coordinating operational policy with financial hedging for risk-averse firms," Omega, Elsevier, vol. 59(PB), pages 279-289.
    2. Ali Naef Mohammad, 2016. "Valuation Tools for Determining the Value of Assets: A Literature Review," International Journal of Academic Research in Accounting, Finance and Management Sciences, Human Resource Management Academic Research Society, International Journal of Academic Research in Accounting, Finance and Management Sciences, vol. 6(4), pages 63-72, October.
    3. Liang, Liang & Wang, Xihui & Gao, Jianguo, 2012. "An option contract pricing model of relief material supply chain," Omega, Elsevier, vol. 40(5), pages 594-600.
    4. Berling, Peter, 2021. "A note generalizing “an option mechanism to coordinate a dyadic supply chain bilaterally in a multi-period setting”," Omega, Elsevier, vol. 101(C).
    5. Jingtang Ma & Shan Yang, 2024. "High-dimensional stochastic control models for newsvendor problems and deep learning resolution," Annals of Operations Research, Springer, vol. 339(1), pages 789-811, August.
    6. Ramasesh, Ranga V., 2010. "Lot-sizing decisions under limited-time price incentives: A review," Omega, Elsevier, vol. 38(3-4), pages 118-135, June.

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