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Real Estate Returns Predictability Revisited: Novel Evidence from the US REITs Market

Omokolade Akinsomi, Goodness Aye (), Vassilios Babalos, Fotini Economou () and Rangan Gupta
Additional contact information
Goodness Aye: Department of Economics, University of Pretoria
Fotini Economou: Centre of Planning and Economic Research, Greece & Open University of Cyprus, Cyprus.

No 201454, Working Papers from University of Pretoria, Department of Economics

Abstract: In this paper we examine the real estate returns predictability employing US REITs and a set of possible predictors for the period January 1991 to September 2013. To this end we employ several forecasting models to test for REITs predictability under a flexible framework that captures parameter instability. Apart from the traditional factors examined in relevant studies, we also account for a series of sentiment and uncertainty indicators that may be significant predictors of REITs returns, especially during turbulent times when sentiment determines investment decisions to a greater extent. The empirical results indicate that the good predictors of REITs returns vary over time and over the forecast horizons. Our results suggest that economy-wide indicators, monetary policy instrument and sentiment indicators are among the most powerful predictors of REITs returns. The issue of the most suitable forecasting method is also discussed in detail. Our results might entail implications for investors and market authorities.

Keywords: Real estate investment trusts; return predictability; dynamic model averaging; uncertainty indicator (search for similar items in EconPapers)
JEL-codes: C22 C32 E52 R31 (search for similar items in EconPapers)
Pages: 27 pages
Date: 2014-10
New Economics Papers: this item is included in nep-for and nep-mac
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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Journal Article: Real estate returns predictability revisited: novel evidence from the US REITs market (2016) Downloads
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