Some execution algorithm providers approach the design of futures algorithms by starting with an equity algorithm as a base and editing the details to tailor to the specificities of trading futures. While this approach may create a fair foundation, on average, it leads to unnecessarily high trading costs—sometimes in extreme fashion—because futures come with their own unique market structure and market microstructure challenges.

In this paper, we introduce five of the biggest challenges associated with optimizing futures execution algorithms and how they can impact execution costs, including volume prediction, navigating long queues for passive execution, widely varied volatility profiles across contracts, exchange matching rules, and 24-hour trading. Readers will likely agree that using an algorithm designed for equities execution as a foundation for futures algorithms can have serious consequences for trading costs.