Adaptive Conjoint Analysis (ACA) is a well established PC-based market research technique (Johnson, 1987; Green et al., 1990) used in marketing to determine the optimal features of projected, as yet, undeveloped products and services. The premise of ACA is that every product and service has multiple attributes, each with a different utility value to the consumer and that individual values can be quantified, summed, and forecasting in a market simulation perspective. Our paper intends to show an ACA application to the real estate market and it is organised in the followed sections: the first compares the performances of different formats of CA ñ CVA (Conjoint Value Analysis), ACA (Adaptive Conjoint Analysis) and CBC (Choice Based Analysis) ñ given the availability of several alternative procedures for consumer preferences measurement and it focuses on the best format when a larger and qualitatives number of attributes do exist. The second section presents the case-study: the real estate market area of Turin (Italy) and its own present trend within the market cycle, while the third shows the results of the empirical observations and stress on the problem of real estate market simulation and demand forecasting. Portfolio Management Intensity and Performance Implications: An International