So I have a database of all earnings announcements for all US stocks down to the millisecond for the past 10 years, and I want to make reasonable predictions on when exactly next earnings will be released. Any ideas on how I could accomplish this? Perhaps something with machine learning? Any help is appreciated!
1 Answer
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You question is unfortunately not as simple as it seems. You probably know that you can buy such calendars, that are progressively replacing "expected earning dates" by "announced earning dates".
The main difficulty stems from the informational content of the date not being the one expected. Indeed, if you can predict the exacte date, and if it deviates from the "expected date" (the one that you could get from historical calendars, using the "best ML tool"), they you will get information about the content of the earning announcement!
From this paper: Johnson, Travis L., and Eric C. So. "Time will tell: Information in the timing of scheduled earnings news." Journal of Financial and Quantitative Analysis 53, no. 6 (2018): 2431-2464.
Our first tests show that high-R SCORE firms (i.e., “advancers”) subsequently report better earnings news than low-R SCORE firms (i.e., “delayers”) at their earnings announcements. Specifically, advancers report statistically and economically greater return on assets (ROA), same-quarter growth in ROA, and analyst-based earnings surprises compared with delayers. Together, these results highlight the predictive power of scheduling disclosures for firms’ earnings news and thus provide strong evidence that earnings scheduling is itself an information event that is commonly observable weeks ahead of firms’ actual announcement dates.
It implies there is no correct answer to your question
one the one hand if you can predict the next earning date (with no other informations that calendars) then it has no value,
on the other hand given that you cannot predict this date, then it has some value...
