Understanding Systematic Risk in Real Estate Markets

Abstract

A one-factor pricing model is employed to investigate the internal consistency of singlefamily home and professionally-managed property prices. The risk factor used here is the U.S. real estate index, which has much stronger explanatory power than the S&P 500 Index for real estate assets. Empirical tests with this model lead to several surprising results. First, portfolios of East Coast or West Coast cities have negative risk-adjusted returns (alpha), while a portfolio of all inland cities has positive alpha. Second, a momentum strategy does not outperform the U.S. real estate index on a transaction and risk-adjusted basis, despite its ability to pick the largest-growth cities. Third, high-beta cities have negative alpha, while low-beta cities have positive alpha, even after considering transaction costs. Fourth, high rental yield cities have positive alpha and vice versa, even after transaction costs. Fifth, large cities have negative alpha, while small cities have positive alpha. Finally, expensive cities have negative alpha and vice-versa. A possible explanation for these abnormal returns is that some cities are systematically neglected by investors.