The digitalisation and automation of trading in financial markets has allowed new types of manipulation to arise. Using the principle of particle physics, project HighLO aims to identify anomalies that can harm financial markets, so these markets can be better protected from manipulation.
Particle collisions and high-frequency trading
Algorithms are increasingly taking over human trading activity on financial markets where commodities, such as wheat and corn, are being traded. These algorithms act automatically and much faster. In the modern trading environment, speed has become more important and the data size of financial markets has increased tremendously. This is a challenge for regulators and researchers looking for anomalies. Where do you start when there is so much data? With the help of particle physics, these anomalies can be identified.
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Wageningen University & Research, the European Organization for Nuclear Research (CERN), the Commodity Risk Management Expertise Center (CORMEC) and Maastricht University attempt to identify, visualise and predict market manipulation. These activities enable regulators, exchanges and market participants to operate in a safer and more stable market environment. The research may also lead to diagnostic tools to predict financial instability. In addition, this research will indirectly help market participants such as hedgers to better manage their risk, thereby lowering capital costs – a necessary condition for innovation.
Visualisation method and early warning system
The project team is researching limit order book data to identify where anomalies have occurred. The team has developed a visualisation method for financial markets, using tools from particle physics. In the future, the project team aims to develop an early warning system for regulators, exchanges and market participants that contributes to a fairer and better functioning market.