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A Hedged Monte Carlo Approach to Real Option Pricing

  • Edgardo Brigatti
  • Felipe Macías
  • Max O. Souza
  • Jorge P. Zubelli
Part of the Fields Institute Communications book series (FIC, volume 74)

Abstract

In this work we are concerned with valuing optionalities associated to invest or to delay investment in a project when the available information provided to the manager comes from simulated data of cash flows under historical (or subjective) measure in a possibly incomplete market. Our approach is suitable also to incorporating subjective views from management or market experts and to stochastic investment costs.

It is based on the Hedged Monte Carlo strategy proposed by Potters, Bouchaud, Sestovic (Phys. A Stat. Mech. Appl. 289(3–4):517–525, 2001) where options are priced simultaneously with the determination of the corresponding hedging. The approach is particularly well-suited to the evaluation of commodity related projects whereby the availability of pricing formulae is very rare, the scenario simulations are usually available only in the historical measure, and the cash flows can be highly nonlinear functions of the prices.

Keywords

Cash Flow Real Option Incomplete Market Traded Asset Historical Measure 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

E.B. developed this work while visiting IMPA under the Cooperation Agreement between IMPA and Petrobras. MOS was partially supported by CNPq grant 308113/2012-8 and FAPERJ. JPZ was supported by CNPq grants 302161/2003-1 and 474085/2003-1 and by FAPERJ through the programs Cientistas do Nosso Estado and Pensa Rio. All authors acknowledge the IMPA-PETROBRAS cooperation agreement.

The authors would like to acknowledge and thank a number of discussions with Fernando Aiube (PUC-RJ and Petrobras). We also thank Milene Mondek for the implementation of a number of preliminary examples of the HMC algorithm and Luca P. Mertens for help with the R software and the calibration procedure in the examples.

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Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Edgardo Brigatti
    • 1
  • Felipe Macías
    • 2
  • Max O. Souza
    • 3
  • Jorge P. Zubelli
    • 2
  1. 1.Instituto de FísicaUniversidade Federal do Rio de JaneiroRio de JaneiroBrazil
  2. 2.IMPARio de JaneiroBrazil
  3. 3.Departamento de Matemática AplicadaUniversidade Federal FluminenseNiteroiBrazil

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