Quantifying Sentiment with Google Trends in the Housing Market

40 Pages Posted: 13 Feb 2024

See all articles by Abdolreza Nazemi

Abdolreza Nazemi

Karlsruhe Institute of Technology

Seyedmostafa Zamanishandiz

Karlsruhe Institute of Technology

Frank J. Fabozzi

Johns Hopkins University - Carey Business School

Andreas Geyer-Schulz

Karlsruhe Institute of Technology

Date Written: January 24, 2024

Abstract

The informativeness of search data of households can be used to screen and monitor any market whose participants can use Internet search to gather information before entering that market. In this paper, we analyze the information content of a type of digital footprint (i.e., information that homebuyers and sellers leave online simply by searching on Google) for predicting house prices based on the households' search behaviors. For the period 2006 to 2020, we find that Google housing sentiment from easily accessible digital footprints explains a significantly larger house price variation than typical drivers of house prices identified in the literature.

JEL Classification: G12. G14

Suggested Citation

Nazemi, Abdolreza and Zamanishandiz, Seyedmostafa and Fabozzi, Frank J. and Geyer-Schulz, Andreas, Quantifying Sentiment with Google Trends in the Housing Market (January 24, 2024). Available at SSRN: https://ssrn.com/abstract=4704873 or http://dx.doi.org/10.2139/ssrn.4704873

Abdolreza Nazemi (Contact Author)

Karlsruhe Institute of Technology ( email )

Kaiserstraße 12
Karlsruhe, Baden Württemberg 76131
Germany

Seyedmostafa Zamanishandiz

Karlsruhe Institute of Technology ( email )

Kaiserstraße 12
Karlsruhe, Baden Württemberg 76131
Germany

Frank J. Fabozzi

Johns Hopkins University - Carey Business School ( email )

100 International Drive
Baltimore, MD 21202
United States

Andreas Geyer-Schulz

Karlsruhe Institute of Technology ( email )

Kaiserstraße 12
Karlsruhe, Baden Württemberg 76131
Germany

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