Monte Carlo simulations for real estate valuation

Purpose – To address formally the issue of uncertainty in valuing real estate. Design/methodology/approach – Monte Carlo simulations are used to incorporate the uncertainty of valuation parameters. The probability distributions of the various parameters are constructed using empirical data and a simple model is suggested to compute the discount rate. Findings – The central values of the 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. Research limitations/implications – Further research should focus on the stability of the model when other portfolios are used and for different periods of the real estate cycle. It would also be fruitful to dig deeper in the relation between capital expenses and property values. Practical implications – Risk can be assessed by valuers as they can measure the probability that the value of a property be less than a given threshold. Originality/value – By incorporating uncertainty, the analysis does not yield merely a point estimate of the property's value but rather the entire distribution of values. Also this paper constitutes a contribution to the debate about valuation variation and the margin of error in valuing properties.