IDEAS home Printed from
   My bibliography  Save this paper

Monte Carlo Simulations for Real Estate Valuation


  • Elion Jani
  • Martin Hoesli
  • André Bender


In this paper, we use the adjusted present value methodology with Monte Carlo simulations in a real estate valuation context. Monte Carlo simulations make it possible to incorporate the uncertainty in the components of future cash flows and in the discount rate. We use empirical data to extract information about the probability distributions of the various parameters. In particular, we propose a simple model to compute the appropriate discount rate. We forecast the term structure of interest rates using a Cox Ingersoll Ross (1985) model, and then add a premium that is function of both the real estate market and of selected hedonic characteristics of the buildings. Our empirical results suggest that the central values of our simulations are close to the hedonic values. Not surprisingly, the confidence intervals are found to be most sensitive to the discount rate and the exit cap rate being used.

Suggested Citation

  • Elion Jani & Martin Hoesli & André Bender, 2005. "Monte Carlo Simulations for Real Estate Valuation," ERES eres2005_212, European Real Estate Society (ERES).
  • Handle: RePEc:arz:wpaper:eres2005_212

    Download full text from publisher

    File URL:
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    1. Neil Crosby & Anthony Lavers & John Murdoch, 1998. "Property valuation variation and the 'margin of error' in the UK," Journal of Property Research, Taylor & Francis Journals, vol. 15(4), pages 305-330, January.
    2. John C. Cox & Jonathan E. Ingersoll Jr. & Stephen A. Ross, 2005. "A Theory Of The Term Structure Of Interest Rates," World Scientific Book Chapters, in: Sudipto Bhattacharya & George M Constantinides (ed.), Theory Of Valuation, chapter 5, pages 129-164, World Scientific Publishing Co. Pte. Ltd..
    3. Jim Clayton, 1996. "Market Fundamentals, Risk and the Canadian Property Cycle: Implications for Property Valuation and Investment Decisions," Journal of Real Estate Research, American Real Estate Society, vol. 12(3), pages 347-368.
    4. Larry E. Wofford, 1978. "A Simulation Approach to the Appraisal of Income Producing Real Estate," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 6(4), pages 370-394, December.
    5. Åke Gunnelin & Patric H. Hendershott & Martin Hoesli & Bo Söderberg, 2004. "Determinants of Cross‐Sectional Variation in Discount Rates, Growth Rates and Exit Cap Rates," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 32(2), pages 217-237, June.
    6. Ferson, Wayne E & Harvey, Campbell R, 1991. "The Variation of Economic Risk Premiums," Journal of Political Economy, University of Chicago Press, vol. 99(2), pages 385-415, April.
    7. Fama, Eugene F. & French, Kenneth R., 1989. "Business conditions and expected returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 25(1), pages 23-49, November.
    8. Fernandez, Pablo, 2003. "Equivalence of ten different methods for valuing companies by cash flow discounting," IESE Research Papers D/524, IESE Business School.
    Full references (including those not matched with items on IDEAS)


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

    Cited by:

    1. Michel Baroni & Fabrice Barthélémy & Mahdi Mokrane, 2007. "Optimal holding period for a real estate portfolio," Journal of Property Investment & Finance, Emerald Group Publishing, vol. 25(6), pages 603-625, October.
    2. Erika Meins & Daniel Sager, 2013. "Sustainability and Risk: Towards a Risk-Based Sustainability Rating for Real Estate Investments," ERES eres2013_254, European Real Estate Society (ERES).
    3. Charles-Olivier Amédée-Manesme & Fabrice Barthélémy & Michel Baroni & Etienne Dupuy, 2013. "Combining Monte Carlo simulations and options to manage the risk of real estate portfolios," Journal of Property Investment & Finance, Emerald Group Publishing, vol. 31(4), pages 360-389, July.
    4. Michele Leonardo Bianchi & Agostino Chiabrera, 2012. "Italian real estate investment funds: market structure and risk measurement," Questioni di Economia e Finanza (Occasional Papers) 120, Bank of Italy, Economic Research and International Relations Area.
    5. Goran Karanovic & Bisera Gjosevska, 2012. "Analysis of Risk and Uncertainty Using Monte Carlo Simulation and its Influence on Project Realization," Annals - Economic and Administrative Series -, Faculty of Business and Administration, University of Bucharest, vol. 6(1), pages 145-162, December.

    More about this item

    JEL classification:

    • R3 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location


    Access and download statistics


    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:arz:wpaper:eres2005_212. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Architexturez Imprints). General contact details of provider: .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.