Abstract
In this chapter we will discuss different approaches to real options pricing. We will start with the analytical solution of the Black-Scholes equation, which will be applied to the case of Netscape. Subsequently, we will present the Cox-Ross-Rubinstein Approach to option pricing, a numerical method for solving dynamic programming problems. Dynamic programming problems are often solved by partial differential equations, which can become very complex and their analytical solutions are even more complex. Therefore, analytical dynamic programming is beyond the scope of this book. But, we will elaborate on numerical dynamic programming using the numerical method of Copeland and Antikarov (2001), which is applied to the case of Portes. This method is a combination of dynamic programming, contingent claims and Monte Carlo simulation. Furthermore, the case of Boeing is used to demonstrate an application of the Monte Carlo simulation approach by Datar and Mathews (2007). We will conclude the discussion on real options approaches with the spreadsheet approach of de Neufville et al. (2006), which includes the use of Monte Carlo simulation in Excel®, and optimizes the decision regarding the design of a parking garage. This final method is more known to the field of engineering, however, it’s a very interesting method to use, because it demonstrates the impact and importance of probability distributions on real options value. We will discuss this in more detail in Chap. 4. The concluding part of this chapter is the evaluation of the real options approaches by discussing the pros and cons of each approach.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
- 2.
This equation holds, because we are dealing here with a European call option. In case of an American option, this equation only holds if mS + B > S – K. Otherwise this is C = S – K.
- 3.
A continuous process is one where the price movements of a stock show small constant changes and we are able to follow these changes without having to remove the pen from the paper. In contrast to this, a jump process where stock price movements are discrete, i.e. discrete movements called jumps. Here the stock price can change only at certain fixed points in time.
References
Netscape: Black-Scholes
Black F, Scholes M (1973) The pricing of options and corporate liabilities. J Pol Econ 81(3):637–654
Buckley A, Tse K, Rijken H, Eijgenhuijsen H (2002) Stock market valuation with real options lessons from netscape. Eur Manage J 20(5):512–526
Copeland T, Antikarov V (2001a) Real options a practitioners guide. TEXERE, New York/London
Hull JC (2009a) Options, futures and other derivatives, 7th edn. Pearson Prentice Hall, New Jersey
Marathe RR, Ryan SM (2005) On the validity of the geometric Brownian motion assumption. Eng Econ J Devoted Prob Capital Invest 50(2):159–192. doi:10.1080/00137910590949904
Yen G, Yen EC (1999) On the validity of the Wiener process assumption in option pricing models: contradictory evidence from Taiwan. Rev Quant Finance Account 12(4):327–340. doi:10.1023/A:1008309307499
Option Pricing: Cox, Ross and Rubinstein
Copeland T, Antikarov V (2001b) Real options a practitioner’s guide. TEXERE, New York/London
Cox JC, Ross SA, Rubinstein M (1979) Option pricing: a simplified approach. J Financ Econ 1460(7):229–263
Hull JC (2009b) Options, futures and other derivatives, 7th edn. Pearson Prentice Hall, New Jersey
The Portes Case: Copeland and Antikarov
Borison A (2005) Real options analysis: where are the Emperor’s clothes? J Appl Corp Finance 17/2:17–31
Copeland T, Antikarov V (2001c) Real options a practitioner’s guide. TEXERE, New York/London
Copeland T, Antikarov V (2005) Real options: meeting the Georgetown challenge. J Appl Corp Finance 17/2:32–51
Godinho P (2006) Monte Carlo estimation of project volatility for real options analysis. J Appl Finance 16(1), Spring/Summer p 15–30
Haahtela T (2011) Estimating changing volatility in cash flow simulation-based real option valuation with the regression sum of squares error method. J Real Options 1(1):33–52
The Boeing Approach: Datar Mathews
Datar VT, Mathews SH (2004) European real options: an intuitive algorithm for the black-scholes formula. J Appl Finance 14(1), Spring/Summer 2004 p 45–51
Datar VT, Mathews SH (2007) A practical method for valuing real options: the Boeing approach. J Appl Corp Finance 19(2), Spring 2007 p 95–104
Parking Garage: de Neufville, Scholtes and Wang
Hull JC (2009c) Options, futures and other derivatives, 7th edn. Pearson Prentice Hall, New Jersey
de Neufville R, Scholtes S, Wang T (2006) Real options by spreadsheet: parking garage case example. ASCE J Infrastruct Syst 12(2):107–111
Peters L (2016) Impact of probability distributions on real options valuation. J Infrastruct Syst. doi:10.1061/(ASCE)IS.1943-555X.0000289, 04016005
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Peters, L. (2016). Real Options Methods Illustrated. In: Real Options Illustrated. SpringerBriefs in Finance. Springer, Cham. https://doi.org/10.1007/978-3-319-28310-4_3
Download citation
DOI: https://doi.org/10.1007/978-3-319-28310-4_3
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-28309-8
Online ISBN: 978-3-319-28310-4
eBook Packages: Economics and FinanceEconomics and Finance (R0)