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.
Authors
- Hsiu‐Lang Chen (ORCID: https://orcid.org/0000-0003-2125-3149)
- Jolana Stejskalová (ORCID: https://orcid.org/0000-0002-3777-2560)
Institutions
- University of Illinois Chicago (US)
- Mendel University in Brno (CZ)
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
Funders
- University of Pennsylvania