Forecasting returns for particular sectors and markets is perforce an exercise in generalities. Forecasting models use historical relationships between returns and their drivers to estimate likely future returns for an office market, for example. The risk to that forecast is defined in terms of the historic variability of the series being forecast. The provision of these forecasts provides an useful context to any investment decision but the actual performance of that investment over time will be determined by a range of spatial, political and socio-economic factors that will only have been incorporated loosely in the forecasting model, if at all. Worse, in the excitement of the pre-recessionary bubble in real estate investment, in many cases these risk factors were disregarded completely. The objective of this paper is to define an holistic risk framework that captures the potential risks in a market at a more granular level than forecasts provide. This model will then be tested against conventional econometric forecasts for sample market sector combinations.