Monte Carlo Simulations for Real Estate Valuation
AbstractWe 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.
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Bibliographic InfoPaper provided by International Center for Financial Asset Management and Engineering in its series FAME Research Paper Series with number rp148.
Date of creation: Jun 2005
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Real estate valuation; Monte Carlo simulations; Adjusted Present Value (APV);
Find related papers by JEL classification:
- R32 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Other Spatial Production and Pricing Analysis
- G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
- G23 - Financial Economics - - Financial Institutions and Services - - - Non-bank Financial Institutions; Financial Instruments; Institutional Investors
This paper has been announced in the following NEP Reports:
- NEP-ALL-2005-08-13 (All new papers)
- NEP-CMP-2005-08-13 (Computational Economics)
- NEP-FIN-2005-08-13 (Finance)
- NEP-FMK-2005-08-13 (Financial Markets)
- NEP-URE-2005-08-13 (Urban & Real Estate Economics)
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