Into the microseconds: market relationships at the highest resolution using particle physics methodology

This study introduces a methodology for analyzing high-frequency financial market relationships at microsecond resolution, inspired by particle physics techniques. This methodology addresses the trade-off between message data and snapshot data and provides a market behavior analysis that scales well to ultra-high resolution. By examining data from the Chicago Mercantile Exchange (CME), we analyze market interdependencies within the agriculture, energy, and metal complexes. Based on microsecond differences between markets, we reveal significant leading-following relationships among these markets, highlighting the dominant influence of corn in agriculture, crude oil in energy, and gold in metals. Additionally, we explore cross-domain interactions, revealing complex dynamics influenced by broader economic indicators. This research is the first to analyze market relationships at microsecond resolution over a complete year, which is made possible by the methodological and software infrastructure developed for particle physics at CERN (The European Organization for Nuclear Research).