The Predictability of Real Estate Excess Returns: An Out-of-Sample Economic Value Analysis

Massimo Guidolin, Manuela Pedio () and Milena T. Petrova ()
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Manuela Pedio: Bicocca University
Milena T. Petrova: Syracuse University

The Journal of Real Estate Finance and Economics, 2023, vol. 67, issue 1, No 5, 108-149

Abstract: Abstract We examine the predictability of private and public real estate returns using recursive, out-of-sample, linear and Markov switching models, employing a rich set of predictor variables. We find considerable improved predictive power compared to simple regression models, especially at the intermediate horizon. Next, we test whether such improved forecasting accuracy translates into a positive risk-adjusted out-of-sample performance by performing a recursive mean-variance portfolio allocation analysis. We observe significant improvements in realized Sharpe ratios and mean-variance utility scores, especially when employing Markov switching models and exploiting predictability at intermediate horizons. Furthermore, our results are robust to the inclusion of transaction costs.

Keywords: Public real estate; REITs; Private real estate; Return predictability; Non-linear models; Out-of-sample analysis; Mean-variance portfolios (search for similar items in EconPapers)
Date: 2023
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Working Paper: The Predictability of Real Estate Excess Returns: An Out-of-Sample Economic Value Analysis (2019)
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DOI: 10.1007/s11146-020-09769-2

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