In a recent series of papers, we sequentially introduced the RavenPack Earnings Intelligence package exploiting different alternative, earnings-related, data sources. We demonstrated that these business cycle signals, derived from earnings-related news, earnings call transcripts and insider transactions between reporting periods, can be used to construct portfolios that outperform the market across different regions and capitalizations over a broad range of holding periods.

In this paper, we generate signals using the insights from shifts in earnings announcement dates, tracked using the RavenPack Earnings Dates dataset, and demonstrate how to incorporate these signals into the RavenPack Earnings Intelligence framework [1-4]. In particular:

• We show that advances/delays in earnings announcement dates can be predictive of positive/negative earnings results on the release date. We use this information to build a profitable strategy around earnings announcement events.

• We also show that changes in earnings announcement dates (earnings calendar change events) are followed by outsized price reactions, with the resulting strategy delivering robust returns with a slow decay.

• A combined strategy of earnings announcement events and earnings calendar change events delivers Annualized Returns of 8.7% for U.S. mid/large-caps and 20.9% for small-caps, with information ratios of 0.9 and 1.4, respectively.

• Incorporating the Earnings Dates combined strategy into our Earnings Intelligence framework results in consistent performance improvements in the U.S. mid/large-cap strategies. We observe a 15% increase in information ratios for effective holding periods of a week or above and more than a 10% increase in annualized returns over shorter holding periods.

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