  We take inspiration from statistical physics to develop a novel conceptual
framework for the analysis of financial markets. We model the order book
dynamics as a motion of particles and define the momentum measure of the system
as a way to summarise and assess the state of the market. Our approach proves
useful in capturing salient financial market phenomena: in particular, it helps
detect the market manipulation activities called spoofing and layering. We
apply our method to identify pathological order book behaviours during the
flash crash of the LUNA cryptocurrency, uncovering widespread instances of
spoofing and layering in the market. Furthermore, we establish that our
technique outperforms the conventional Z-score-based anomaly detection method
in identifying market manipulations across both LUNA and Bitcoin cryptocurrency
markets.
