Predicting Securitized Real Estate Returns: Financial and Real Estate Factors vs. Economic Variables

Securitized real estate returns have traditionally been forecasted using economic variables. However, no consensus exists regarding the variables to use. Financial and real estate factors have recently emerged as alternative forecasting variables that proxy for the set of economic variables that should be useful in forecasting securitized real estate returns. Therefore, a question that arises is whether the predictive ability of the two sets of variables differ. This paper employs fractional cointegration analysis to identify whether long-run nonlinear relations exist between securitized real estate and the two sets of forecasting variables. Fractionally Integrated Error Correction Model (FIECM) forecasts are used in a trading strategy to compare the forecasting ability of the two sets of variables. Empirical analyses are conducted using data for the U.S., the U.K., and Australia. The results show that financial and real estate factors generally outperform economic variables in forecasting securitized real estate returns. The latter is supported by the fractional cointegration analysis in which long memory (long-range dependence) is generally found between securitized real estate and stocks, bonds, and direct real estate.