Multivariate Constrained Robust M-Regression for Shaping Forward Curves in Electricity Markets

TL;DR

This paper introduces a multivariate constrained robust M-regression method for estimating shaping coefficients in electricity forward prices, ensuring arbitrage-free and robust results with low computational cost, demonstrated on German electricity data.

Contribution

The paper presents a novel multivariate constrained robust M-regression approach that simultaneously estimates shaping coefficients, ensuring arbitrage-free and robust modeling in electricity markets.

Findings

Model effectively rules out arbitrage at an elementary level.

Method is robust to outliers, providing stable results.

Efficient algorithm reduces computational costs.

Abstract

In this paper, a multivariate constrained robust M-regression (MCRM) method is developed to estimate shaping coefficients for electricity forward prices. An important benefit of the new method is that model arbitrage can be ruled out at an elementary level, as all shaping coefficients are treated simultaneously. Moreover, the new method is robust to outliers, such that the provided results are stable and not sensitive to isolated sparks or dips in the market. An efficient algorithm is presented to estimate all shaping coefficients at a low computational cost. To illustrate its good performance, the method is applied to German electricity prices.