When two worlds collide: Using particle physics tools to visualize the limit order book

Abstract

We introduce a methodology to visualize the limit order book (LOB) using a particle physics lens. Open-source data-analysis tool ROOT, developed by CERN, is used to reconstruct and visualize futures markets. Message-based data is used, rather than snapshots, as it offers numerous visualization advantages. The visualization method can include multiple variables and markets simultaneously and is not necessarily time dependent. Stakeholders can use it to visualize high-velocity data to gain a better understanding of markets or effectively monitor markets.In addition, the method is easily adjustable to user specifications to examine various LOB research topics, thereby complementing existing methods.

Unravelling the JPMorgan spoofing case using particle physics visualization methods

“…These messages can be used to recreate the LOB with millisecond precision. The open‐source ROOT software framework, developed by CERN, among others, to analyse the massive data generated in the Large Hadron Collider, is used to reconstruct and visualize the LOB (Brun & Rademakers, 1997; CERN, 2018b; Verhulst et al, 2021). ROOT is used in particle physics to save, access and mine data, among other applications, as well as to generate visualizations (CERN, 2018a).…”

“…However, these papers, as well as other LOB‐related papers (e.g., Biais et al, 2010; Menkveld & Yueshen, 2019), lack visualizations of the LOB. Visualizations help academics, industry participants and regulators to better understand the market; they allow them, among other things, to identify and understand anomalies such as spoofing (Verhulst et al, 2021). LOB visualization literature is thus scarce (Aidov & Daigler, 2015; Paddrik et al, 2016).…”

“…As a result, information is lost as the information is being aggregated. In addition, the literature provides no uniform method to achieve optimal snapshot size (Verhulst et al, 2021). Snapshot sizes that have been used in LOB analyses so far are: 5 minutes (Chordia et al, 2019; Kahraman & Tookes, 2017), 1 minute (Hautsch & Horvath, 2019; Mendonça & de Genaro, 2020; Yao & Ye, 2018), 10 seconds (Cont et al, 2014), 5 seconds (Brogaard & Garriott, 2019), 3 seconds (Ito & Yamada, 2018) and 1 second (Battalio et al, 2016; Brogaard et al, 2019; Colliard & Hoffmann, 2017; Dugast, 2018).…”

“…Using a visualization methodology developed in particle physics by the European Organization for Nuclear Research (CERN) (Antcheva et al, 2009; CERN, 2018b; Verhulst et al, 2021), we describe the LOB in a novel way, providing new insights into the JPM spoofing case. Specifically, we visualize all spoofing examples as documented in the CFTC report (CFTC, 2020).…”

The Analysis of High-Frequency Finance Data using ROOT

“…Finally, the function run is called, which initiates the event loop, and starts the analysis. This component was recently used in related work to build a novel visualisation of the LOB over a period of time [14]. The use of ROOT and the proposed extension was instrumental in storing and reconstructing the large data volume received from the financial exchange.…”