Monte Carlo Simulations for Real Estate Valuation
We use the Adjusted Present Value (APV) method with Monte Carlo simulations for real estate valuation purposes. Monte Carlo simulations make it possible to incorporate the uncertainty of valuation parameters, in particular of future cash flows, of discount rates and of terminal values. We use empirical data to extract information about the probability distributions of the various parameters and suggest a simple model to compute the discount rate. We forecast the term structure of interest rates using a Cox et al. (1985) model, and then add a premium that is related to both the real estate market and selected property-specific characteristics. Our empirical results suggest that the central values of our simulations are in most cases slightly less than the hedonic values. The confidence intervals are found to be most sensitive to the long-term equilibrium interest rate being used and to the expected growth rate of the terminal value.
|Date of creation:||Jun 2005|
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FAME Research Paper Series
rp90, International Center for Financial Asset Management and Engineering.
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- 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.
- 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.
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