Preconference Day: Summits & WorkshopsMonday, 16 November 2026 - GMT (Greenwich Mean Time, GMTZ)

A big picture look across asset classes. How are allocators and managers adapting to market shifts, evolving risk dynamics, and the rise of quant integration in multi-asset portfolios?

How are investors implementing AI successfully? A deep dive into model development, data infrastructure, back testing frameworks, and real-world performance attribution.

How are quants adapting to tail risk in a year of sharp market moves? Lessons in stress testing and model resilience.

A practical exploration of how firms are constructing portfolios across asset classes while optimising for risk, cost, and return.

At mid-frequency and with meaningful capacity, a systematic crypto strategy is effectively trading a single asset, BTC or ETH, with only a few years of usable history. There is no cross-section to average away noise, so overfitting becomes the central problem. This talk walks through a strategy step by step, from idea to live trading, using the single-asset setting as the hardest possible test of whether an edge is real. We look at where an idea and its data come from; how a deliberately simple signal is built and sized, including the practical choices that quietly move PnL; how to tell whether a Sharpe is genuine, through parameter sensitivity, behaviour across coins, and a Monte-Carlo test on a single price path; and what changes in production. The methods are shown on real signals and carry over to any market with a short history and few instruments, in or out of crypto.

How are systematic ETF strategies being used for liquidity, factor exposure, and tactical tilts?