Operational and Technology Risks in Algorithmic Trading

Summary

This event announcement outlines a talk on risk oversight for automated trading. It emphasizes that algorithmic systems add operational and technology concerns to familiar market, financial, credit, and liquidity risks. The proposed discussion uses failures at Knight Capital, Deutsche Bank, Infinium Capital, and HanMag Securities as case studies, with examples of losses or regulatory consequences stated in the announcement.

The session is framed around assessing access, consistency, quality, algorithms, technology, and scalability, followed by regulatory requirements for quantitative strategies. It offers a useful map of risk categories and incidents to investigate, but provides no detailed case analysis, controls, or evidence about how particular safeguards performed. As an invitation rather than a full presentation, it does not teach an implementable risk process.

Key ideas

• Algorithmic trading introduces system and operational risks alongside market, credit, financial, and liquidity risks.
• The announcement proposes examining several trading failures as risk oversight case studies.
• Its broad risk framework covers access, consistency, quality, algorithms, technology, and scalability.
• The planned talk also includes regulatory requirements for algorithmic quantitative strategies.

Tags

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.