Forecasting EREIT Returns
Authors:
Camilo Serrano
Martin Hoesli
Start Page: 293
End Page: 310
Volume: 13
Issue Number: 4
Year: 2007
Publication: Journal of Real Estate Portfolio Management
Abstract:
This paper analyzes the role played by financial assets, direct real estate,
and the
Fama and French (1993) factors in explaining equity real estate investment
trust (EREIT) returns and examines the usefulness of these variables in
forecasting returns. Four models are analyzed and their predictive potential
is assessed by comparing three forecasting methods: time varying coefficient
(TVC) regressions, vector autoregressive (VAR) systems, and neural networks
models. Trading strategies on these forecasts are compared to a passive
buy-and-hold strategy. The results show that EREIT returns are better
explained by models including the Fama and French factors. The VAR forecasts
are better than the TVC forecasts, but the best predictions are obtained
with neural networks and especially when they are applied to the model using
stock, bond, real estate,
size, and book-to-market factors.

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