Trading Electrons: Predicting DART Spread Spikes in ISO Electricity Markets

TL;DR

This paper develops a multi-zone, impact-aware trading strategy for forecasting and trading DART price spreads in U.S. electricity markets, improving risk-return profiles.

Contribution

It extends spike prediction to multiple zones, models price impacts structurally, and derives optimal trading strategies considering cross-zone effects.

Findings

Impact-aware strategy outperforms unit-size trading in NYISO.

Significant heterogeneity across markets and seasons.

Closed-form solutions for optimal trading vectors.

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.