Using Sentiment and Momentum to Predict Stock Returns
Kevin Lansing and
Michael Tubbs
FRBSF Economic Letter, 2018
Abstract:
Studies that seek to forecast stock price movements often consider measures of market sentiment or stock return momentum as predictors. Recent research shows that a multiplicative combination of sentiment and momentum can help predict the return on the Standard & Poor?s 500 stock index over the next month. This predictive power derives mainly from periods when sentiment has been declining over the past year and recent return momentum is negative?periods that coincide with an increase in investor attention to the stock market as measured by a Google search volume index.
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)
Downloads: (external link)
https://www.frbsf.org/economic-research/files/el2018-29.pdf Full text (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:fip:fedfel:00180
Ordering information: This journal article can be ordered from
reference.library@sf.frb.org
Access Statistics for this article
More articles in FRBSF Economic Letter from Federal Reserve Bank of San Francisco Contact information at EDIRC.
Bibliographic data for series maintained by Federal Reserve Bank of San Francisco Research Library (reference.library@sf.frb.org).