May 18, 2026 | 1:00pm ET | 1 CE Credit
Enhanced index using AI: outperformance potential without factor risk
Artificial intelligence is increasingly influencing how portfolios are built — but for advisors, the real question is how AI can improve investment outcomes without adding complexity or changing how you work with clients. Join David Wright, Head of Quantitative Investments at Pictet Asset Management, as he explains how artificial intelligence is being used inside equity portfolios to support better investment outcomes for clients. You’ll gain actionable takeaways to strengthen client relationships and support more informed investment conversations.
Topics will include:
- AI as an Investment Engine: How machine learning is used to forecast stock‑level returns and construct diversified equity portfolios — without relying on traditional factor bets.
- How an AI model can withstand different market regimes: Why a tree-based machine-learning approach — trained on long histories and continuously retrained — is designed to remain effective across different market environments.
- Portfolio Applications for Advisors: How AI‑enhanced ETFs can be used as a core equity allocation or a diversifying complement alongside passive and active strategies.
Speakers
Insights from Pictet Asset Management
AI: the next chapter
The artificial intelligence (AI) boom is creating a sense of optimism around the world – but also concern about a potential new bubble. We believe AI continues to offer attractive investment opportunities, supported by strong demand from both businesses and consumers.
The human face of AI investing
Alexandra Nagy, investment manager in Pictet Asset Management’s Quantitative Investment team, talks about AI development.
3 reasons to consider Pictet Cleaner Planet
As the past few years show, if the economy is to thrive in the 21st century, it will need affordable energy, abundant natural resources and the ability to adapt to extreme weather.
David Wright on AI in Investing
David Wright explores how Pictet’s equity strategies use machine-learning techniques — specifically gradient-boosted decision trees — trained on 15 years of data and hundreds of company features.
