Google search volume sentiment and its impact on REIT market movements
| Published date | 04 April 2016 |
| Date | 04 April 2016 |
| DOI | https://doi.org/10.1108/JPIF-12-2015-0083 |
| Pages | 249-262 |
| Author | Nicole Braun |
| Subject Matter | Property management & built environment |
Google search volume
sentiment and its impact
on REIT market movements
Nicole Braun
IREBS –International Real Estate Business School,
University of Regensburg, Regensburg, Germany
Abstract
Purpose –The purpose of this paper is to analyze the effect of investor sentiment, measured with
Google internet search data, on volatility forecasts of the US REIT market.
Design/methodology/approach –The author uses the S&P US REIT index and collects search
volume datafrom Google Trends for all US REIT. Twodifferent Generalized AutoregressiveConditional
Heteroskedasticmodels are then estimated,namely, the baselinemodel and the Google augmentedmodel.
Using these models, one-step-ahead forecasts are conducted and the forecast accuracies of bothmodels
are subsequently compared.
Findings –The empirical results reveal that search volume data can be used to predict volatility on
the REIT market. Especially in periods of high volatility, Google augmented models outperform the
baseline model.
Practical implications –The results imply that Google data can be used on the REIT market as a
market indicator. Investors could use Google as an early warning system, especially in periods of high
volatility.
Originality/value –This is the first paper to use Google search query data for volatility forecasts
of the REIT market.
Keywords Volatility, Forecasting, Google trends, REIT, GARCH, Search query data
Paper type Research paper
1. Introduction and motivation
The more transparent a market, the more perfect and therefore more attractive it
becomes. As the past has shown, this plays a major role particularly in the real estate
market. Especially in times of turbulences, reliable information is a valuable asset.
Hence, each individual market participant desires early, quickly accessible and relevant
information. Particularly the internet is a convenient channel from which to obtain free
information. The majority of people use search engines to satisfy their demand for
market information. Google, the market leading search engine, is an easy-to-use tool
and accessible for all with various information options. The search queries and their
search volume are collected, collated and provided through Google Trends 2.0
(www.google.com/trends) in the form of a Search Volume Index (SVI). These SVIs are
publicly available and can be downloaded freely for specific search queries over time.
As this data are highly relevant measure of market behavior, it has already often been
used in real estate research. Many studies, such as Kulkarni et al. (2009), use Google
data to forecast house prices more precisely. Dietzel et al. (2014) extend this framework
and test whether search engines are not only utilized for private, but also for
commercial purposes. They show that GT data can also help to predict commercial real
estate market prices and transactions. Whether investors in general can benefit from
GT data to satisfy their demand for financial real estate market information has
already also attracted attention in academia. Rochdi and Dietzel (2015) derive
Journal of Property Investment &
Finance
Vol. 34 No. 3, 2016
pp. 249-262
©Emerald Group Publis hing Limited
1463-578X
DOI 10.1108/JPIF-12-2015-0083
Received 8 December 2015
Revised 8 December 2015
Accepted 24 December 2015
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/1463-578X.htm
249
Google search
volume
sentiment
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