Purpose - To identify the relative contribution of selected sustainability features to property value risk with the aim of generating a risk-based weighting system for a property sustainability rating.Approach - For a given set of sustainability features, a discounted cash flow (DCF) model is used to derive the weights. The anticipated demand for each sustainability feature is described by three future states of nature. 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. The weights are deduced by comparing the estimated property value distribution with and without each specific sustainability feature in question.Findings - For Switzerland, the highest single impact on the property value risk of 42 modeled sustainability sub-indicators (features) stems from 'thermal energy' (29.3%), followed by 'public transportation' (16.3%), 'day light' (9.6%) and 'story height' (6.3%). At the level of the five groups of aggregated sustainability features, 'resource consumption and greenhouse gases' has the highest relative weight (32.1%), followed by 'health and comfort' (30.6%), 'location and mobility' (22.5%), 'flexibility' (13.5%), as well as 'safety and security' (1.3%). Practical implications - The resulting rating serves as a basis for real estate investment decisions by illustrating how sustainability features affect the risk of specific properties. Value - An effort is made to rigorously found sustainability ratings in financial theory.