A Collection of Wisdom in Predicting Sector Returns: The Use of Google Search Volume Index

This study investigates whether the aggregate investor information demand for all stocks in a sector demonstrated in the Google search volume index (SVI) can predict the sector’s performance. The evidence shows that a sector’s abnormal SVI can predict the sector’s performance next month, even after controlling for the sector’s contemporaneous standardized unexpected earnings and lagged returns on both the market and the sector. Also found is a partial reversal in the sector’s long-run performance that is not completely consistent with the price pressure hypothesis. This indicates that some fundamental information about a sector can be captured by the sector’s abnormal SVI on a timely basis.

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Publication Details

Journal
Journal of risk and financial management
Published
2024-10-05
DOI
https://doi.org/10.3390/jrfm17100452
Citations
4
Primary Topic
Financial Markets and Investment Strategies
Type
article
Field-Weighted Citation Impact
2.16

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article

A Collection of Wisdom in Predicting Sector Returns: The Use of Google Search Volume Index

Hsiu‐Lang Chen, Jolana Stejskalová
4 citations
Journal of risk and financial management
Financial Markets and Investment Strategies
2.16
article

A Collection of Wisdom in Predicting Sector Returns: The Use of Google Search Volume Index

Hsiu‐Lang Chen, Jolana Stejskalová
article en
4 citations

Abstract

This study investigates whether the aggregate investor information demand for all stocks in a sector demonstrated in the Google search volume index (SVI) can predict the sector’s performance. The evidence shows that a sector’s abnormal SVI can predict the sector’s performance next month, even after controlling for the sector’s contemporaneous standardized unexpected earnings and lagged returns on both the market and the sector. Also found is a partial reversal in the sector’s long-run performance that is not completely consistent with the price pressure hypothesis. This indicates that some fundamental information about a sector can be captured by the sector’s abnormal SVI on a timely basis.

Journal of risk and financial managementVol. 17(10)
University of Illinois Chicago (US), Mendel University in Brno (CZ)
University of Pennsylvania
Decent work and economic growth
Openalex Percentile: Top 12%
Financial Markets and Investment Strategies
2.16
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A Collection of Wisdom in Predicting Sector Returns: The Use of Google Search Volume Index — Hsiu‐Lang Chen, Jolana Stejskalová · Journal of risk and financial management (2024) | TGRS Research Map | TGRS