Sustainability and risk in real estate investments: combining monte carlo simulation and dcf

Abstract

This paper identifies the relative contribution of sustainability criteria to property value risk. We use a discounted cash flow (DCF) model to assess the effect of a given set of 42 sustainability sub-indicators on property value. The anticipated demand for each sustainability sub-indicator is described by four future states of nature. Their impact on costs and/or revenue is estimated and included in the model. Subjective probability distributions describe the occurrence of the future states of nature. Monte Carlo simulations of the DCF model are then used to estimate the impact of an individual feature on the risk (volatility) of the property value distribution. Our results for Switzerland show that 'use of thermal energy' (29.3%), followed by 'access to public transportation' (16.3%), 'day light' (9.6%) and 'story height' (6.3%) have the highest single on property value risk. The results are used for a risk-based weighting of a sustainability rating. The rating illustrates how sustainability criteria affect the risk of specific properties and is used as a basis for real estate investment decisions.