Main Conference Day OneTuesday, 17 November 2026 - GMT (Greenwich Mean Time, GMTZ)

The industrialization of quantitative investing and the rise of QIS platforms have dramatically expanded the universe of investable strategies. As implementation becomes increasingly standardized, the key challenge is no longer to generate alpha, but to select the most appropriate strategy for prevailing market conditions. This talk explores how the quant problem is shifting from alpha discovery to alpha selection, and discusses possible frameworks for defining performance and quantifying risk in a world of almost limitless choice.

• Known modelling challenges of historic VaR and Monte Carlo VaR
• Reactivity challenge to joint projections. Persistence of joint tail behaviour in stress market regimes
• Modelling extreme loss scenarios. EVT distributions. Joint tail behaviour and choice of copula
• Can we derive a ‘universal’ copula within VaR/CVaR frameworks?
• Dissection of high dimensional empirical copula into analytical components
• Market regimes and implications for portfolio modelling

We look at XVA through the lens that underlies deep hedging, viewing it as the result of hedging under a utility function. This reveals a generalisation of standard XVAs, generating the classic CVA and FVA, along with HVA (hedging costs) and a number of non-classical contributions that arise from the realities of a real-world hedging strategy. The full framework leads to formulae that can be solved by approximation or via a deep learning approach.