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Trading Electrons: Predicting DART Spread Spikes in ISO Electricity Markets

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  • Emma Hubert
  • Dimitrios Lolas
  • Ronnie Sircar

Abstract

We study the problem of forecasting and optimally trading day-ahead versus real-time (DART) price spreads in U.S. wholesale electricity markets. Building on the framework of Galarneau-Vincent et al., we extend spike prediction from a single zone to a multi-zone setting and treat both positive and negative DART spikes within a unified statistical model. To translate directional signals into economically meaningful positions, we develop a structural and market-consistent price impact model based on day-ahead bid stacks. This yields closed-form expressions for the optimal vector of zonal INC/DEC quantities, capturing asymmetric buy/sell impacts and cross-zone congestion effects. When applied to NYISO, the resulting impact-aware strategy significantly improves the risk-return profile relative to unit-size trading and highlights substantial heterogeneity across markets and seasons.

Suggested Citation

  • Emma Hubert & Dimitrios Lolas & Ronnie Sircar, 2026. "Trading Electrons: Predicting DART Spread Spikes in ISO Electricity Markets," Papers 2601.05085, arXiv.org.
    • Handle: RePEc:arx:papers:2601.05085
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