Information Visualization of Participant Behavior in Market Surveillance

Abstract: Financial markets are now undergoing exponential growth in data, as high-frequency trading is widespread. The need for effective market surveillance is, therefore, become more prominent. Domain experts in exchanges, trading participants, and regulators must provide evidence in their market surveillance investigation. Still, the increased number of participants and its transaction leads to a complicated task that needs to be analyzed more resource-efficient. One way of performing market surveillance is through an at-a- glance view, which can systematically and timely handle this data. Dashboards are today the widely adopted tool for processing large amounts of data in the financial sector. This study seeks to enhance the user experience of a market surveillance system developed with information visualization of participants’ statistical measures. The research was carried out in an industrial setting and followed the case study paradigm. The user research produced a list of expected tasks, translating into design requirements by reflecting on related research on effective dashboard design for interactive high-dimensional data exploration. The design requirements formed the design elements embedded into the low- and high-fidelity prototypes development. During prototype development, the participants’ statistical measures shown as the predefined dimensions on the dashboard were selected using feature selection methods correlate to their number of alerts. User evaluation of the final high-fidelity prototype suggests that interactive high-dimensional data exploration using parallel coordinates plots could improve the market surveillance process. The gap of effectiveness and efficiency scores between first-time users and experts and the feedback from both users show a steep learning curve in visual exploration.