Are Securitized Real Estate Returns More Predictable than Stock Returns?

Posted: 6 Apr 2010

See all articles by Camilo Serrano

Camilo Serrano

IAZI AG - CIFI SA

Martin Hoesli

University of Geneva - Geneva School of Economics and Management (GSEM); Swiss Finance Institute; University of Aberdeen - Business School

Multiple version iconThere are 2 versions of this paper

Date Written: April 5, 2010

Abstract

This paper examines whether the predictability of securitized real estate returns differs from that of stock returns. It also provides a cross-country comparison of securitized real estate return predictability. In conrtast to most of the literature on this issue, the analysis is not based on a multifactor asset pricing framework as much analyses may bias the results. We use a time series approach and thus create a level playing field to compare the predictability of the two asset classes. Forecasts are performed with ARMA and ARMA-EGARCH models and evaluated by comparing the entire empirical distributions of prediction errors, as well as with a trading strategy. The results, based on daily data for the 1990-2007 period, show that securitized real estate returns are generally more predictable than stock returns in countries with mature and well established REIT regimes. ARMA-EGARCH models are found to have portfolio outperformance potential even in the presence of transaction costs, with generally better results for securitized real estate than for stocks.

Keywords: Predictability, Time Series Models, ARMA-EGARCH, REITs, Securitized real estate

JEL Classification: C53, C22, G15

Suggested Citation

Serrano, Camilo and Hoesli, Martin Edward Ralph, Are Securitized Real Estate Returns More Predictable than Stock Returns? (April 5, 2010). Journal of Real Estate Finance and Economics, Vol. 41, No. 2, 2010, Available at SSRN: https://ssrn.com/abstract=1584802

Camilo Serrano

IAZI AG - CIFI SA ( email )

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Martin Edward Ralph Hoesli (Contact Author)

University of Geneva - Geneva School of Economics and Management (GSEM) ( email )

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Swiss Finance Institute

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University of Aberdeen - Business School ( email )

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