Joint Modelling of Gas and Electricity spot prices

TL;DR

This paper introduces a joint mean-reverting stochastic model for gas and electricity spot prices that captures correlation, spikes, and heavy tails, calibrated on French and UK markets, to improve risk assessment.

Contribution

It develops a novel joint modeling approach using Ornstein processes with parameterized diffusion coefficients, effectively capturing key statistical features of energy prices.

Findings

Model reproduces observed price behaviors accurately.

Calibration method is efficient and statistically sound.

Correlation and spikes significantly impact risk measures.

Abstract

The recent liberalization of the electricity and gas markets has resulted in the growth of energy exchanges and modelling problems. In this paper, we modelize jointly gas and electricity spot prices using a mean-reverting model which fits the correlations structures for the two commodities. The dynamics are based on Ornstein processes with parameterized diffusion coefficients. Moreover, using the empirical distributions of the spot prices, we derive a class of such parameterized diffusions which captures the most salient statistical properties: stationarity, spikes and heavy-tailed distributions. The associated calibration procedure is based on standard and efficient statistical tools. We calibrate the model on French market for electricity and on UK market for gas, and then simulate some trajectories which reproduce well the observed prices behavior. Finally, we illustrate the importance of the correlation structure and of the presence of spikes by measuring the risk on a power plant portfolio.