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Quantcast – a Risk.net Cutting Edge podcast
Alvaro Cartea, 19/07/2024
Jul 24, 2024
Alvaro Cartea, Oxford-Man Institute director, discusses the potential anti-competitive effects of machine learning-based trading. Topics include evolving trading strategies, unintentional collusion, market integrity through academic research, collaboration between regulatory bodies and industry professionals, and the impact of automated market making in decentralized markets like Bitcoin.
44:29
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Quick takeaways
- Algorithmic trading has shifted to machine learning for real-time adaptation.
- Black box algorithms may unintentionally reveal information through signaling behavior.
Deep dives
Algorithmic Trading Evolution
Algorithmic trading strategies have evolved over the years, transitioning from static rules-based systems to dynamic algorithms that learn in real-time from their trading activities. These new algorithms utilize sophisticated techniques such as machine learning and artificial intelligence to adapt and optimize trading strategies continuously, reflecting a paradigm shift in trading sophistication and efficiency.
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