Quantcast – a Risk.net Cutting Edge podcast

Imperial College’s mathematical finance head introduces new tool to measure slippage and trade quality

Dario Villani, Co-founder and CEO of Duality Group, and Kharen Musaelian, Co-founder and CIO, share insights from their pioneering work in quantum cognition machine learning (QCML). They discuss the game-changing impact of integrating quantum theory into finance, emphasizing how QCML can improve predictions with noisy data. The duo dives into the complexities of statistical learning and the contrasting views of uncertainty in classical versus quantum frameworks. They also explore advancements in healthcare and the pressing need for regulation as AI and quantum technologies evolve.

BoE quant discusses a top-down counterparty risk framework that uses Gaussian distributions and copulae

Trio of senior quants explain how autoencoders can reduce dimensionality in yield curves

Lyudmil Zyapkov on modelling forward variance skew

Adia quant explains how to apply hierarchical risk parity to a minimum-variance portfolio

Alexei Kondratyev on quantum computing

Quantcast: Piterbarg and Nowaczyk on decorrelating variables. A novel data manipulation technique strengthens backtesting on correlated data.

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.

JP Morgan quant Lorenzo Ravagli discusses a unified framework for trading the volatility skew premium, exploring strategies in the FX market, client interactions in hedge funds, and principles applicable across asset classes.