Combining Monte Carlo Simulations and Options to Manage the Risk of Real Estate Portfolios
30 Pages Posted: 5 Nov 2012
Date Written: June 6, 2012
This paper aims to show that the accuracy of real estate portfolio valuations and of real estate risk management can be improved through the simultaneous use of Monte Carlo simulations and options theory. Our method considers the options embedded in Continental European lease contracts drawn up with tenants who may move before the end of the contract. We combine Monte Carlo simulations for both market prices and rental values with an optional model that takes into account a rational tenant’s behavior. We analyze to what extent the options exercised by the tenant significantly affect the owner’s income. Our main findings are that simulated cash flows which take account of such options are more reliable that those usually computed by the traditional method of discounted cash flow. Moreover, this approach provides interesting metrics, such as the distribution of cash flows. The originality of this research lies in the possibility of taking the structure of the lease into account. In practice this model could be used by professionals to improve the relevance of their valuations and for risk management purpose: the output as a distribution of outcomes should be of interest to investors. However, some limitations are inherent to our model: these include the assumption of the rationality of tenant’s decisions, and the difficulty of calibrating the model, given the lack of data.
After a brief literature review of simulation methods used for real estate valuation, the paper describes the suggested simulation model, its main assumptions, and the incorporation of tenant’s decisions regarding break options influencing the cash flows. Finally, using an empirical example, we analyze the sensitivity of the model to various parameters, test its robustness and note some limitations.
Keywords: Monte Carlo Simulations, Real Estate Portfolio Valuation, Break Options, Lease Structure, Risk Management, Risk Metrics
JEL Classification: R33, L85, G11, G32, R32
Suggested Citation: Suggested Citation