In the wake of the continuous digital transformation and the rapid increase in the amount of available data, trading on financial markets takes place at ever higher frequencies. This development does not only concern classical financial markets but also the comparatively young electricity markets. Apart from the massive expansion of renewable energy sources, increasing demand-side flexibility and increasing storage capabilities, high-frequency trading is one of the major trends shaping the electricity markets of the future. This thesis explores high-frequency trading on two German electricity markets: the intraday electricity market and the electricity futures market.

The first part of this thesis develops an econometric price model with fundamental impacts for intraday electricity markets of 15-minute contracts. We analyze a unique data set of high-frequency transaction data, fundamental supply and demand data, and intradaily updated forecasts of renewable power generation. Our empirical analysis shows that, on average, prices of 15-minute contracts exhibit a sawtooth-shaped and trading volumes a U-shaped hourly seasonality. Furthermore, market liquidity increases sharply within the last trading hour before gate closure. We calibrate our econometric model for morning, noon, evening, and night contracts and use a threshold regression technique to examine how 15-minute 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-minute contracts. Additionally, prices of neighboring contracts exhibit strong explanatory power and a positive impact on prices of a given contract. These findings are independent of the time of day and thus generic features of the price formation process on the intraday market. In contrast, intraday auction prices have higher explanatory power for the pricing of night contracts than day contracts. We observe an asymmetric effect of renewable forecast changes on intraday prices depending on the slope of the merit order curve. In general, renewable forecasts have a higher explanatory power at noon and at night than in the morning and evening, but price information is the main driver of 15-minute intraday trading at all times of day. Overall, we show that the importance of influencing factors on the intraday electricity market has changed from fundamental towards trading-related factors. This novel finding illustrates that the intraday electricity market has become increasingly mature.

The second part of this thesis conducts an empirical analysis of volatility and liquidity on electricity futures markets. We investigate high-frequency quote data of electricity month futures contracts, which are fundamental building blocks of power derivatives markets. We estimate volatility and liquidity by several measures from the scientific literature and particularly acknowledge that financial high-frequency data are not equally spaced in time. Empirical evidence suggests that volatility of electricity futures decreases as time approaches maturity, while coincidently liquidity increases. In contrast to previous research, we reveal a novel reciprocal relationship between volatility and liquidity on electricity markets. Established continuous-time stochastic models for electricity futures prices involve a growing volatility function in time and are thus not able to capture our empirical findings a priori. In Monte Carlo simulations, we demonstrate that increasing liquidity dominates the models' volatility function and gives rise to a decreasing volatility evolution. Therefore, including liquidity is key to model the volatility of electricity futures.

Overall, this thesis delivers a comprehensive picture of high-frequency trading mechanisms on electricity markets and thereby contributes to a better understanding of one of the most important trends in the electricity sector.