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Real option valuation with neural networks

Author

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  • Alfred Taudes
  • Martin Natter
  • Michael Trcka

Abstract

We propose to use neural networks to value options when analytical solutions do not exist. The basic idea of this approach is to approximate the value function of a dynamic program by a neural net, where the selection of the network weights is done via simulated annealing. The main benefits of this method as compared to traditional approximation techniques are that there are no restrictions on the type of the underlying stochastic process and no limitations on the set of possible actions. This makes our approach especially attractive for valuing Real Options in flexible investments. We, therefore, demonstrate the method proposed by valuing flexibility for costly switch production between several products under various conditions. © 1998 John Wiley & Sons, Ltd.

Suggested Citation

  • Alfred Taudes & Martin Natter & Michael Trcka, 1998. "Real option valuation with neural networks," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 7(1), pages 43-52, March.
    • Handle: RePEc:wly:isacfm:v:7:y:1998:i:1:p:43-52
    DOI: 10.1002/(SICI)1099-1174(199803)7:13.0.CO;2-D
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    Cited by:

    1. James R. Coakley & Carol E. Brown, 2000. "Artificial neural networks in accounting and finance: modeling issues," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 9(2), pages 119-144, June.
    2. Julia Bennell & Charles Sutcliffe, 2004. "Black–Scholes versus artificial neural networks in pricing FTSE 100 options," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 12(4), pages 243-260, October.
    3. Daniel E. O'Leary, 2009. "Downloads and citations in Intelligent Systems in Accounting, Finance and Management," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 16(1‐2), pages 21-31, January.
    4. Giovanni Villani, 2022. "A Neural Network Approach to Value R&D Compound American Exchange Option," Computational Economics, Springer;Society for Computational Economics, vol. 60(1), pages 305-324, June.

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