Predictability of stock market activity using Google search queries
Helena Veiga (),
Sofia Ramos and
DES - Working Papers. Statistics and Econometrics. WS from Universidad Carlos III de Madrid. Departamento de Estadística
This paper analyzes whether web search queries predict stock market activity in a sample of the largest European stocks. We provide evidence that i) an increase in web searches for stocks on Google engine is followed by a temporary increase in volatility and volume and a drop in cumulative returns. ii) An increase for web search queries for the market index leads to a decrease in the returns of the index as well as of the stock index futures and an increase in implied volatility. iii) Attention interacts with behavioral biases. The predictability of web searches for return and liquidity is enhanced when firm prices and market prices hit a 52-week high and diminished when the market hits a 52-week low. iv) Investors tend to process more market information than firm specific information in investment decisions, confirming limited attention theory.
Keywords: Behavioral; Finance; Google; Search; Volume; Index; Investor; Attention; Predictability (search for similar items in EconPapers)
JEL-codes: G02 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-fmk and nep-for
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4) Track citations by RSS feed
Downloads: (external link)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:cte:wsrepe:ws130605
Access Statistics for this paper
More papers in DES - Working Papers. Statistics and Econometrics. WS from Universidad Carlos III de Madrid. Departamento de Estadística
Bibliographic data for series maintained by Ana Poveda ().