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Sentiment-based commercial real estate forecasting with Google search volume data

Marian Alexander Dietzel (IREBS – International Real Estate Business School, University of Regensburg, Regensburg, Germany)
Nicole Braun (IREBS – International Real Estate Business School, University of Regensburg, Regensburg, Germany)
Wolfgang Schäfers (IREBS – International Real Estate Business School, University of Regensburg, Regensburg, Germany)

Journal of Property Investment & Finance

ISSN: 1463-578X

Article publication date: 26 August 2014

2039

Abstract

Purpose

The purpose of this paper is to examine internet search query data provided by “Google Trends”, with respect to its ability to serve as a sentiment indicator and improve commercial real estate forecasting models for transactions and price indices.

Design/methodology/approach

This paper examines internet search query data provided by “Google Trends”, with respect to its ability to serve as a sentiment indicator and improve commercial real estate forecasting models for transactions and price indices.

Findings

The empirical results show that all models augmented with Google data, combining both macro and search data, significantly outperform baseline models which abandon internet search data. Models based on Google data alone, outperform the baseline models in all cases. The models achieve a reduction over the baseline models of the mean squared forecasting error for transactions and prices of up to 35 and 54 per cent, respectively.

Practical implications

The results suggest that Google data can serve as an early market indicator. The findings of this study suggest that the inclusion of Google search data in forecasting models can improve forecast accuracy significantly. This implies that commercial real estate forecasters should consider incorporating this free and timely data set into their market forecasts or when performing plausibility checks for future investment decisions.

Originality/value

This is the first paper applying Google search query data to the commercial real estate sector.

Keywords

Citation

Alexander Dietzel, M., Braun, N. and Schäfers, W. (2014), "Sentiment-based commercial real estate forecasting with Google search volume data", Journal of Property Investment & Finance, Vol. 32 No. 6, pp. 540-569. https://doi.org/10.1108/JPIF-01-2014-0004

Publisher

:

Emerald Group Publishing Limited

Copyright © 2014, Emerald Group Publishing Limited

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