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Trading Electrons: Predicting DART Spread Spikes in ISO Electricity Markets

Trading Electrons: Predicting DART Spread Spikes in ISO Electricity Markets ArXiv ID: 2601.05085 “View on arXiv” Authors: 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. ...

January 8, 2026 · 2 min · Research Team