April 4, 2022
In our latest research paper, we focus specifically on European markets by sequentially overlaying three RavenPack Earnings Intelligence signals
In recent white papers from our Earnings Intelligence research series, we reviewed the alpha-generative properties of several dataset combinations over various universes and holding periods. In our latest research paper, we focus specifically on European markets by sequentially overlaying three RavenPack Earnings Intelligence signals:
❶ Sentiment from earnings-call transcripts
❷ Sentiment from earnings-related news and
❸ Net insider trading activity in between reporting periods.
Our backtests of long-short, dollar-neutral strategies in the European Mid/Large-Cap universe show that:
Document Sentiment from transcripts, which aggregates a machine
learning-generated sentiment measure for every sentence transcribed
from the Earnings call, provides an Information Ratio of 1.0 across
a wide range of effective holding periods, with Annualized Returns
ranging from 7% to 3%.
Combining sentiment from earnings-related news with Earnings-call
transcripts sentiment enhances Information Ratios and Annualized
Returns up to monthly effective holding periods. For an effective
holding period of ten days, a blended signal improves the Information
Ratio of the earnings-news based strategy from 1.3 to 1.5.
Adding an insider transaction overlay to the combined earnings-call
transcripts and earnings-news signals leads to a significant
increase in the Information Ratios, of about 20% over effective
holding periods of more than 5 days.
To read more about RavenPack’s Earnings Intelligence series research
RavenPack Earnings Intelligence combines signals from separate sources augmented with sentiment and thematic analytics for a powerful alternative that removes the limits of isolated vendor data. Learn More
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