Quantcast – a Risk.net Cutting Edge podcast

Quant finance

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.

JP Morgan quant Olivier Daviaud discusses his alternative to Greeks decomposition, exploring path dependency in P&L and implications for vanilla options. He delves into differences in options trading perspectives between market makers and buy side investors, and explores the link between option performance and volatility premium. Daviaud suggests rethinking P&L attribution for options, advocating for a new approach, and discusses portfolio analysis formula's application across asset classes and future research directions.