Degree Days Utility Revenue Lead
In plain terms
When heating/cooling demand spikes far above the 5-year norm, regulated utilities tend to beat revenue expectations 30 days out.
How it works
Extreme temperature (HDD/CDD) shocks move within-quarter utility demand and revenue, and analysts/investors under-react to observable temperature shocks (Addoum, Ng & Ortiz-Bobea 2023 JFE). The 30d-anomaly z-score trading rule itself is an in-house heuristic motivated by that finding, not a backtest replicated from any paper.
Data dependencies
- Daily prices
Adjusted-close OHLCV for every US-listed ticker; primary price feed.
- Eia degree days
A data feed this strategy reads, refreshed on its normal schedule.
Expected edge
- Reported return
- n/a (in-house heuristic; the paper documents temperature-shock predictability of industry earnings news and analyst under-reaction, not this rule's alpha)
- Tested over
- 21/42/63d
~1-2% over 21-42d on extreme weather quarters.
Example tickers where this is likely to fire
Illustrative only, the signal fires based on the live data, not a fixed list.
Related families
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Storm enters Gulf of Mexico → refiner and chemical stocks (VLO/MPC/PSX/LYB/DOW) drop 1-3% for a week.
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