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The paper proposes an adaptive decision station to create real estate portfolios. The decision station would be useful for investors interested in real estate investment and for environments where data needs to be constantly updated by using the internet. The Findlay model was selected for the portfolio management engine of the decision station gives its simplicity and previous results. A prototype was built based on the proposed model and tested by using real estate data collected from 63 cities from different metropolitan areas in the United States for each quarter from 1999 to 2005. The results showed that the station was able to determine which properties should be selected from a set of input choices in order to minimize risk and maximize return of investment.
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