Decode the Market. Build the Future.Capture the Alpha.
The Future Alpha Focus Day brings together investment teams, quants, risk specialists, engineers and data leaders for a day of technical depth and hands-on learning - not lectures, working sessions.
This is fully practical, laptop-based training. Bring a laptop - you'll be building, coding, and modelling throughout the day.
Built to address genuine skills gaps identified by the market, you can choose from two focus days - AI in Trading or Financial Modelling - each led by leading experts and designed to unite teams in deep-dive sessions that build cross-functional fluency and sharpen alpha-ready capabilities. These are working rooms, built for practitioners to leave with something they can actually use.
From Hype to Execution: AI in Trading
AI is no longer optional, and the leaders who adapt now will set the pace for everyone else. This working day gives senior quant and trading leaders the genuine new skills to do that. Most AI efforts stall not because the technology doesn't work, but because nobody builds in the context a model actually needs. This session fixes that directly: how to brief AI properly, how to tell a real edge from a relabelled one, and how to take a strategy from prototype to live production without losing control of it. Hands-on and laptop-based throughout, led by AI trained practitioners. Attendees leave with five working artifacts, including a real prototype built live in the room.
From Theory to Trade: The Financial Modelling Working Day
A working day for investment teams, quants, risk specialists and data leaders who want to go beyond the classical factor model and into where financial modelling is actually heading. From new data sources to new modelling techniques, the gap is rarely the math - it's translating frontier research into something that survives contact with a live book. Hands-on and laptop-based throughout, led by academics and practitioners rather. Attendees leave with five working artifacts, including live-coded models they take with them.
MODULE 1: What AI in Trading Actually Is - and Where It Actually Helps
An anti-hype framing of what's genuinely new versus existing quant practice relabeled as AI, plus a practical primer on getting more out of the tools already in use
MODULE 2: Edge & Risk Management
Hands-on work identifying a genuine edge versus a back tested coincidence, sizing and entry timing, and building a disciplined, rules-based kill switch, worked against a live example.
MODULE 3: From Prototype to Production
A live build of a real, working prototype in the room, showing how to prove a strategy or tool in a contained way before scaling it across the book, plus an honest brief on what's still iterative work afterwards.
MODULE 1: Modern Financial Modelling - What's Actually Changed
Orientation: where classical factor models still hold, where new data and techniques are genuinely reshaping signal construction, and where it's relabelling. Sets expectations for the rest of the day.
MODULE 2: Language as Signal - Textual Analysis & LLM Modelling
The flagship technical block, a practitioner-led blueprint of the modelling pipeline, a hands-on Jupyter session building a live LLM-based signal, and group feedback/Q&A.
MODULE 3: Stress-Testing the Model - Overfitting, Robustness & Walk-Forward Discipline
Hands-on work pressure-testing a model for overfitting and regime sensitivity, building a reusable validation framework rather than trusting a single backtest.
Refreshment & Networking Break
MODULE 4: Culture, Talent & Governance
Why most "AI failures" are organizational, not technical: a practical build-vs-hire-vs-train talent model, controlled rollout versus uncontrolled access, and calibrating enthusiasm against evidence.
MODULE 5: Cross-Enterprise Integration Workshop
A closing working session, not a panel: small groups map the day's frameworks onto their own desk and walk out with a concrete action plan, tying the day's five artifacts into one through-line.
MODULE 4: From Model to Book - Deployment, Decay & Monitoring
How a validated model actually goes live: deployment discipline, detecting signal decay, retraining cadence, and rules-based triggers for pulling a model rather than letting it quietly fail.
MODULE 5: Cross-Functional Model Governance Workshop
A closing working session, not a panel: small groups build a model validation/governance checklist for their own shop, tying the day's five artifacts into one through-line.
