In this article we will discuss the use of quantitative models at PGGM Real Estate Investments and describe an ARFIMA time series model. We have created a framework for the description and estimation of an ARFIMA model and its use for making forecasts of property returns. The method that we have applied uses the theory of wavelets. The theory of wavelets consists of a mathematical technique that can filter data sequences. Furthermore we go into detail as to apply wavelets for maximum likelihood estimation of an ARFIMA model. We present the results of a study about the forecasting of PGGMís Property Market Indicator using an ARFIMA model. Finally we discuss the relevance of the ARFIMA methodology as an instrument for defining a property investment strategy and tactical allocation.