A new research paper – Trading the Post-Earnings-Announcement Drift – combines PEAD signals with the StarMine Analyst Revisions Model (ARM) to provide investors with a clearer vision of the quarterly earnings cycle.
- The StarMine Analysts Revisions Model tracks the likelihood of future upward or downward analyst revisions, providing great insight into analyst expectations for how a company’s fiscal quarter is playing out after it reports its earnings.
- ARM uses the ‘Predicted Surprise’ metric that looks at how likely a company is to beat or miss its analyst estimates at the time of reporting and helps to indicate potential surprises.
- The combination of PEAD signals and ARM gives a broader picture of the entire quarterly earnings cycle and produces risk-adjusted returns superior to any of the individual inputs and the equal-weighted market index.
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The StarMine Analyst Revisions Model (ARM) has been a popular and performant model since its inception over two decades ago.
The model, which tracks the likelihood of future upward or downward analyst revisions, gives great insight into analyst expectations for how a company’s fiscal quarter is playing out.
Indicator of earnings surprises
ARM also incorporates the ‘Predicted Surprise’ metric that provides an indicator of how much we think a company will beat or miss analyst estimates at report time and has shown to be a useful indicator of potential earnings surprises.
However, a measure of how we expect the price of a stock to move after it reports its earnings has been missing from the StarMine suite. This notion has long been studied in finance and is given the term ‘post-earnings-announcement drift’ (PEAD).
Predicting price drift
In our research, we construct a simple model of PEAD using some of the well-studied informative factors from prior research and show our PEAD model accurately predicts price drift following an earnings announcement.
However, the most exciting performance comes when we combine our PEAD model with ARM.
By doing this, we can incorporate information about how a company’s fiscal quarter is progressing, whether or not they are likely to beat or miss estimates at reporting, and finally how the stock price will move in the days following the announcement.
This combination gives a complete picture of the entire quarterly earnings cycle (leading up to an announcement, the announcement itself, and finally the days following the announcement) and produces risk-adjusted returns superior to any of the individual inputs and the equal-weighted market index.
To find out more about how to achieve a more complete view of the quarterly earnings cycle by developing a linear model to construct tradable portfolios download our white paper: Trading the Post-Earnings-Announcement Drift