IDEAS home Printed from https://ideas.repec.org/a/spr/binfse/v3y2011i4p221-230.html
   My bibliography  Save this article

Valuation of Discount Options in Software License Agreements

Author

Listed:
  • Daniel Gull

Abstract

Many companies increasingly rely on licensed standard software for system software and applications. In addition to the regulation of usage conditions, software licensing agreements increasingly include services, such as software upgrades and user training, as a part of the contract or these are optional for a fee, which can be made use of by the licensee during the term of the contract at a reduced price or as a free service. This benefit entitlement is called a discount option and must be valued during the selection and designing of a contract. This paper describes the basic valuation issues as well as some weaknesses of previous approaches, and subsequently presents a model which, on the basis of the real option theory, enables an assessment of the discount options using mathematical methods. As the value of discount options can in many cases only be estimated by using analytical methods under certain conditions, a practical solution method is explained on the basis of numeric backwards induction. The procedure for applying the model and the achieved advances in knowledge are illustrated with an example. Copyright Gabler Verlag 2011

Suggested Citation

  • Daniel Gull, 2011. "Valuation of Discount Options in Software License Agreements," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 3(4), pages 221-230, August.
    • Handle: RePEc:spr:binfse:v:3:y:2011:i:4:p:221-230
    DOI: 10.1007/s12599-011-0170-8
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s12599-011-0170-8
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s12599-011-0170-8?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Longstaff, Francis A & Schwartz, Eduardo S, 2001. "Valuing American Options by Simulation: A Simple Least-Squares Approach," The Review of Financial Studies, Society for Financial Studies, vol. 14(1), pages 113-147.
    2. Andrea Gamba & Nicola Fusari, 2009. "Valuing Modularity as a Real Option," Management Science, INFORMS, vol. 55(11), pages 1877-1896, November.
    3. Thomas Mertens, 2005. "Option pricing with sparse grids," Computing in Economics and Finance 2005 449, Society for Computational Economics.
    4. Bjørn Eraker, 2004. "Do Stock Prices and Volatility Jump? Reconciling Evidence from Spot and Option Prices," Journal of Finance, American Finance Association, vol. 59(3), pages 1367-1404, June.
    5. Daniel Gull & Alexander Wehrmann, 2009. "Optimized Software Licensing – Combining License Types in a License Portfolio," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 1(4), pages 277-288, August.
    6. Black, Fischer & Scholes, Myron S, 1973. "The Pricing of Options and Corporate Liabilities," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 637-654, May-June.
    7. Cox, John C. & Ross, Stephen A. & Rubinstein, Mark, 1979. "Option pricing: A simplified approach," Journal of Financial Economics, Elsevier, vol. 7(3), pages 229-263, September.
    8. Longstaff, Francis A & Schwartz, Eduardo S, 2001. "Valuing American Options by Simulation: A Simple Least-Squares Approach," University of California at Los Angeles, Anderson Graduate School of Management qt43n1k4jb, Anderson Graduate School of Management, UCLA.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Christian Ullrich, 2013. "Valuation of IT Investments Using Real Options Theory," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 5(5), pages 331-341, October.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Pringles, Rolando & Olsina, Fernando & Penizzotto, Franco, 2020. "Valuation of defer and relocation options in photovoltaic generation investments by a stochastic simulation-based method," Renewable Energy, Elsevier, vol. 151(C), pages 846-864.
    2. Lim, Terence & Lo, Andrew W. & Merton, Robert C. & Scholes, Myron S., 2006. "The Derivatives Sourcebook," Foundations and Trends(R) in Finance, now publishers, vol. 1(5–6), pages 365-572, April.
    3. In oon Kim & Bong-Gyu Jang & Kyeong Tae Kim, 2013. "A simple iterative method for the valuation of American options," Quantitative Finance, Taylor & Francis Journals, vol. 13(6), pages 885-895, May.
    4. Duy Nguyen, 2018. "A hybrid Markov chain-tree valuation framework for stochastic volatility jump diffusion models," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 5(04), pages 1-30, December.
    5. Carmen Schiel & Simon Glöser-Chahoud & Frank Schultmann, 2019. "A real option application for emission control measures," Journal of Business Economics, Springer, vol. 89(3), pages 291-325, April.
    6. Li, Chenxu & Ye, Yongxin, 2019. "Pricing and Exercising American Options: an Asymptotic Expansion Approach," Journal of Economic Dynamics and Control, Elsevier, vol. 107(C), pages 1-1.
    7. Cosma, Antonio & Galluccio, Stefano & Scaillet, Olivier, 2012. "Valuing American options using fast recursive projections," Working Papers unige:41856, University of Geneva, Geneva School of Economics and Management.
    8. Weiping Li & Su Chen, 2018. "The Early Exercise Premium In American Options By Using Nonparametric Regressions," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 21(07), pages 1-29, November.
    9. Duffie, Darrell, 2003. "Intertemporal asset pricing theory," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, edition 1, volume 1, chapter 11, pages 639-742, Elsevier.
    10. Ben Hambly & Renyuan Xu & Huining Yang, 2021. "Recent Advances in Reinforcement Learning in Finance," Papers 2112.04553, arXiv.org, revised Feb 2023.
    11. Lin Zhao & Sweder van Wijnbergen, 2013. "A Real Option Perspective on Valuing Gas Fields," Tinbergen Institute Discussion Papers 13-126/VI/DSF60, Tinbergen Institute.
    12. Chen, Ding & Härkönen, Hannu J. & Newton, David P., 2014. "Advancing the universality of quadrature methods to any underlying process for option pricing," Journal of Financial Economics, Elsevier, vol. 114(3), pages 600-612.
    13. Locatelli, Giorgio & Mancini, Mauro & Lotti, Giovanni, 2020. "A simple-to-implement real options method for the energy sector," Energy, Elsevier, vol. 197(C).
    14. Liu, Qiang & Guo, Shuxin, 2020. "An excellent approximation for the m out of n day provision," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    15. Junkee Jeon & Geonwoo Kim, 2022. "Analytic Valuation Formula for American Strangle Option in the Mean-Reversion Environment," Mathematics, MDPI, vol. 10(15), pages 1-19, July.
    16. Penizzotto, F. & Pringles, R. & Olsina, F., 2019. "Real options valuation of photovoltaic power investments in existing buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 114(C), pages 1-1.
    17. Yao Elikem Ayekple & Charles Kofi Tetteh & Prince Kwaku Fefemwole, 2018. "Markov Chain Monte Carlo Method for Estimating Implied Volatility in Option Pricing," Journal of Mathematics Research, Canadian Center of Science and Education, vol. 10(6), pages 108-116, December.
    18. Nelson Areal & Artur Rodrigues & Manuel Armada, 2008. "On improving the least squares Monte Carlo option valuation method," Review of Derivatives Research, Springer, vol. 11(1), pages 119-151, March.
    19. Katarzyna Toporek, 2012. "Simple is better. Empirical comparison of American option valuation methods," Ekonomia journal, Faculty of Economic Sciences, University of Warsaw, vol. 29.
    20. Francesco Rotondi, 2019. "American Options on High Dividend Securities: A Numerical Investigation," Risks, MDPI, vol. 7(2), pages 1-20, May.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:binfse:v:3:y:2011:i:4:p:221-230. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.