The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
In Search of Attention
Open accessAbstract
We propose a new and direct measure of investor attention using search frequency in Google (Search Volume Index (SVI)). In a sample of Russell 3000 stocks from 2004 to 2008, we find that SVI (1) is correlated with but different from existing proxies of investor attention; (2) captures investor attention in a more timely fashion and (3) likely measures the attention of retail investors. An increase in SVI predicts higher stock prices in the next 2 weeks and an eventual price reversal within the year. It also contributes to the large first‐day return and long‐run underperformance of IPO stocks.
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Cited by
The Sum of All FEARS Investor Sentiment and Asset Prices
Da, Z., Engelberg, J., & Gao, P. (2015) · Review of Financial Studies · doi:10.1093/rfs/hhu072 · Cited by 1,379
Self-citationWisdom of Crowds: The Value of Stock Opinions Transmitted Through Social Media
Chen, H., De, P., Hu, Y. (., & Hwang, B.-H. (2014) · Review of Financial Studies · doi:10.1093/rfs/hhu001 · Cited by 1,251
Ilhan, E., Sautner, Z., & Vilkov, G. (2021) · The Review of Financial Studies · doi:10.1093/rfs/hhaa071 · Cited by 1,136
Ilhan, E., Sautner, Z., & Vilkov, G. (2018) · SSRN Electronic Journal · doi:10.2139/ssrn.3204420 · Cited by 1,136
From Predictive to Prescriptive Analytics
Bertsimas, D., & Kallus, N. (2020) · Management Science · doi:10.1287/mnsc.2018.3253 · Cited by 784
Metadata
- Authors
- DA, Z., ENGELBERG, J., & GAO, P.
- Venue
- The Journal of Finance
- Publisher
- Wiley
- Published
- 2011-09-21
- Volume
- 66
- Issue
- 5
- Pages
- 1461-1499
- ISSN
- 0022-1082 (ISSN-L)
- 1540-6261
- OpenAlex
- W3122136669
- Cited by
- 3,067
- References
- 3
- FWCI
- 136.47
- Type
- journal article
- Language
- en
- Open access
- bronze
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.