Retail Investor Attention Dataset
InvestingChannel is a leading online financial marketing and advertising platform, with a network of over 100 financial media publishers globally, including many well-known media properties. Their raw traffic data is available from 2017 onwards, and covers 9,600+ public companies in the U.S. alone, from 68 unique publishers.
We find that the data is predictive of earnings pre-announcement period returns. Specifically, firms in the top 20% by attention tend to report 2.1% larger earnings surprises, 0.5% larger revenue surprises, and 0.52% more in pre-announcement period returns than those in the bottom 20% by attention.
UPDATE: Our latest research for this dataset offers opportunities to discover a new strategy for using alternative data as an overlay. This approach could be useful to any quants who use cross-sectional signals to predict returns.
Request the new white paper to learn this new strategy. The key finding is that Value, Momentum, and other anomalies are less efficiently priced for these high retail attention names. By focusing on this sub-universe, we can significantly increase the returns of these anomalies.
For the high-retail-attention tercile of this universe, where our retail attention metrics have been controlled for firm size, these long-short returns nearly double in certain formulations.
Explore the white paper and learn about the value of investor attention.
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