Paper: arXiv 2307.16619

Abstract

In this paper, we propose a multidimensional statistical model of intraday electricity prices at the scale of the trading session, which allows all products to be simulated simultaneously. This model, based on Poisson measures and inspired by the Common Shock Poisson Model, reproduces the Samuelson effect (intensity and volatility increases as time to maturity decreases). It also reproduces the price correlation structure, highlighted here in the data, which decreases as two maturities move apart. This model has only three parameters that can be estimated using a moment method that we propose here. We demonstrate the usefulness of the model on a case of storage valuation by dynamic programming over a trading session.

Complexity vs Empirical Score

  • Math Complexity: 7.5/10
  • Empirical Rigor: 6.0/10
  • Quadrant: Holy Grail — high math complexity, high empirical rigor

Why this score: The paper employs advanced mathematics including Poisson measures and dynamic programming for a specialized model, while also demonstrating strong empirical rigor through data analysis on French and German markets, back-testing with battery valuation, and proposing an estimation method.

Research Flowchart

  flowchart TD
  Goal["Research Goal: Model multidimensional<br>intraday electricity prices<br>to value battery storage"]

  Data["Data: European Power Exchange<br>Intraday Price Data"]

  Model["Methodology: Common Shock<br>Poisson Model"]
  
  Est["Computational Process:<br>Moment Method Estimation<br>3 parameters only"]

  Sim["Computational Process:<br>Dynamic Programming<br>for Battery Valuation"]

  Out["Key Outcomes:<br>1. Reproduces Samuelson Effect<br>2. Captures Price Correlations<br>3. Enables accurate storage valuation"]

  Goal --> Data
  Data --> Model
  Model --> Est
  Est --> Sim
  Sim --> Out