Constructing price indices for commercial real estate (CPPIs) is challenging due to heterogeneous and limited observations. Common price index methods often result in volatile index series. Attempts to reduce volatility often lead to frequent revisions of the entire index series and a loss of methodological index properties. When it comes to CPPIs in official statistics, both volatility and frequent revisions are undesirable. Revisions could compromise the confidence of users if indicators are allowed to change indefinitely, while instable indices insufficiently reflect structural underlying developments. In this study, a combination of hedonic imputation, multilateral calculations, time series analysis, and window splicing is introduced. The result is a method that produces stable and limited-revisable indices with the ability to detect turning points in an early stage. Commercial real estate transactions in the Netherlands are used to empirically test the method. The resulting CPPIs appear suitable for monitoring financial stability and, therefore, seem appropriate for the use in official statistics.@en