Insight into trading limits in financial algorithms

Abstract

In this project we aimed to create a post-trading day safeguard system that allows for the identification of bugs in the primary and secondary risk control systems at Optiver. These systems are needed to prevent undesirable exposure to the market from happening, and to ensure that they know exactly what this exposure is. The amount of input data for this project, given in the form of log files, equates to roughly 200 GB per trading day, post sanitation. We have developed a program that can simulate an entire trading day and detect if any limits were breached. This program can be run overnight, allowing for a T+1 report in the morning after the respective trading day. The difficulties in this project were in the acquisition of all knowledge concerning the unique traits of various markets around the world, inconsistencies in the data, incomplete documentation, and optimization of the program to run within the required time.

Organizationally, the project was executed within an agile workflow, with Kanban as software development methodology. Furthermore, the project is tested extensively to ensure the accuracy and correctness of the program.

Concerning the impact of the project, it contributed to the identification and resolution of multiple previously unknown bugs in the control systems at Optiver. Furthermore, our project verified the existence of some previously known issues. In the future, when the software is run to verify all order logs of Optiver, the software will prove its value by either increasing the confidence that there is an absence of bugs in the RiskGuard and autotrading software of Optiver or by identifying breached limits, indicating a bug.