Quantifying Volatility Reduction in German Day-ahead Spot Market in the Period 2006 through 2016

TL;DR

This study analyzes the evolution of price volatility in the German day-ahead electricity market from 2006 to 2016, using matrix decomposition techniques to account for unique data challenges, and finds a decreasing trend in volatility.

Contribution

It introduces a novel application of singular value decomposition to measure volatility in electricity prices, addressing issues like negative prices and diurnal patterns.

Findings

Market volatility has decreased over the studied period.

Matrix decomposition provides a robust measure against outliers.

Method addresses unique challenges of electricity price data.

Abstract

In Europe, Germany is taking the lead in the switch from the conventional to renewable energy. This poses new challenges as wind and solar energy are fundamentally intermittent, weather-dependent and less predictable. It is therefore of considerable interest to investigate the evolution of price volatility in this post-transition era. There are a number of reasons, however, that makes the practical studies difficult. For instance, EPEX prices can be zero or negative. Consequently, the standard approach in financial time series analysis to switch to logarithmic measures is inapplicable. Furthermore, in contrast to the stock market prices which are only available for trading days, EPEX prices cover the whole year, including weekends and holidays. Accordingly, there is a lot of underlying variability in the data which has nothing to do with volatility, but simply reflects diurnal activity patterns. An important distinction of the present work is the application of matrix decomposition techniques, namely the singular value decomposition (SVD), for defining an alternative notion of volatility. This approach is systematically more robust toward outliers and also the diurnal patterns. Our observations show that the day-ahead market is becoming less volatile in recent years.