ABSTRACT
Purpose:
To analyze the predictability of Google's search queries in the Brazilian financial market.
Originality/gap/relevance/implications:
Despite a growing foreign literature using Google's search query data, there is no acknowledgement of work on this area in Brazil. An application to the Brazilian financial market shows new sources of information about market movements and may contribute to researchers and practitioners to understand how changes in specific search queries affect the market.
Key methodological aspects:
Following previous studies, we estimate VAR models and Granger causality tests to investigate the effects over three variables in both stock and fixed income markets: traded volume, return and volatility. Following this procedure, we verify both the hypothesis of financial variables being affected by search queries, as well as the opposite relationship. Weekly data from Google's search queries and financial markets was gathered for the period between 2007 and 2014.
Summary of key results:
The existence of a predictive effect between search query data and financial variables, particularly in the stock market, is evident. However, this result was not robust in all cases studied. It is noteworthy that, for the inverse relationship, i.e. financial market impacting search queries on Google, strong evidence of a causal relationship has been found. A trading strategy based on this type of data yielded higher returns than the defined benchmarks.
Key considerations/conclusions:
A significant relationship between Google's search query data and the financial market has been discovered. Results provide a new source of information that affects the Brazilian financial market.
KEYWORDS
Google Trends; Investor attention; Market efficiency; Market microstructure; VAR Models
Source: Elaborated by the authors.
Source: Elaborated by the authors.