Real-World & Alternative DataExtended setexperimental liveNew

Degree Days Utility Revenue Lead

Updated dailyData needs: lowlong only
paper
2023
Source
Addoum, J.M., Ng, D.T. & Ortiz-Bobea, A. (2023). "Temperature shocks and industry earnings news." Journal of Financial Economics 150(1), 1-45.
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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.

No live results for this strategy yet. Charts appear once it has earned a top spot on at least one stock, either on its own or as part of a blend of several strategies.
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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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For informational and educational purposes only. Not financial advice. Learn more