An econometric model for intraday electricity trading

Abstract

This paper develops an econometric price model with fundamental impacts for intraday electricity markets of 15-min contracts. A unique dataset of intradaily updated forecasts of renewable power generation is analysed. We use a threshold regression model to examine how 15-min intraday trading depends on the slope of the merit order curve. Our estimation results reveal strong evidence of mean reversion in the price formation mechanism of 15-min contracts. Additionally, prices of neighbouring contracts exhibit strong explanatory power and a positive impact on prices of a given contract. We observe an asymmetric effect of renewable forecast changes on intraday prices depending on the merit-order-curve slope. In general, renewable forecasts have a higher explanatory power at noon than in the morning and evening, but price information is the main driver of 15-min intraday trading. This article is part of the theme issue ‘The mathematics of energy systems’.

Volatility and Dispersion of Hourly Electricity Contracts on the German Continuous Intraday Market

“…What is more, the price fluctuations during the final trading hour of contract h are correlated with the fluctuations during the final trading hour of the previously expired contract h − 1. This observation is in line with [20,21], who found similar results for the prices and price changes of 15-min contracts. Figure 6 illustrates these correlations for the measure VSD.…”

“…Besides external drivers, we showed that characteristics of the (cross-sectional) time series of contracts can be used as forecasting variables. This complements the findings of [20,21], who found a similar correlation for 15-min contracts on prices. Because of (auto-)correlations, realized price fluctuations of previously expired contracts as well as fluctuations during the elapsed trading time of the contract itself have an explanatory power for price fluctuations during the (final) peak trading hour.…”

“…The impact of intraday updated forecasts on the prices of 15-min contracts in the intraday market was found by [4,21]. In our research, this kind of data was missing.…”

“…With regard to volatility, they used data from observed trades for a 15-min contract and calculated the difference between consecutive prices as the basis for price fluctuations. Further price analysis of 15-min contracts was also performed by [20,21]. Forecasting price distributions of hourly contracts over quantiles that occur in the last 3 h before delivery was the focus of [22].…”

Introduction: the mathematics of energy systems

“…Limited access to high-quality high-frequency trading data, however, has so far somewhat hindered research on new models for intra-day trading, and few models have so far been proposed in the literature. Kremer et al [9] consider a novel and extensive dataset which contains high-frequency electricity price transaction data for 15 min contracts from the German market and linked fundamental supply and demand data. What is more, it includes the same intra-daily updated forecasts of wind and solar power generation available to traders on the intraday market.…”