  Optimal execution, i.e., the determination of the most cost-effective way to
trade volumes in continuous trading sessions, has been a topic of interest in
the equity trading world for years. Electricity intraday trading slowly follows
this trend but is far from being well-researched. The underlying problem is a
very complex one. Energy traders, producers, and electricity wholesale
companies receive various position updates from customer businesses, renewable
energy production, or plant outages and need to trade these positions in
intraday markets. They have a variety of options when it comes to position
sizing or timing. Is it better to trade all amounts at once? Should they split
orders into smaller pieces? Taking the German continuous hourly intraday market
as an example, this paper derives an appropriate model for electricity trading.
We present our results from an out-of-sample study and differentiate between
simple benchmark models and our more refined optimization approach that takes
into account order book depth, time to delivery, and different trading regimes
like XBID (Cross-Border Intraday Project) trading. Our paper is highly relevant
as it contributes further insight into the academic discussion of algorithmic
execution in continuous intraday markets and serves as an orientation for
practitioners. Our initial results suggest that optimal execution strategies
have a considerable monetary impact.
