David Wright, Head of Quantitative Investments for Pictet Asset Management, joined Keith Black, Managing Director of RIA Channel, to discuss how AI is enhancing quantitative investing and the firm’s approach to ensuring effective model performance.
While the rise of AI has reshaped portfolio construction for many investors, Wright highlights that quantitative investors have long sought more effective solutions to generate active returns using technology and data. The evolution of AI has enabled quantitative managers to increase data analysis efficiency and improve the incorporation of that data into evolving stock views.
Within quantitative investing, enhanced indexing has gained increasing interest, with recent popularity driven by factor strategies and smart beta. Wright notes that Pictet’s AI approach can strip out factor risk, ensuring investment decisions are stock-specific and independent of traditional style factors such as momentum, value, or quality. He adds that this approach has the potential to deliver more consistent active returns with a higher compounding benefit.
Rather than focusing on a specific time period or market environment, Wright explains that the firm’s models are trained on over 15 years of data. This allows the models to capture a range of economic environments, market cycles, interest rate levels, and inflationary conditions. Wright emphasizes that this approach prevents the model from becoming dominated by patterns and relationships from the recent past.
Concerns have been raised that traditional quantitative factor models, such as value, growth, or momentum, may struggle during regime changes, including the recent transition from a global trade environment to a more protectionist one. Wright explains that Pictet’s strategy focuses on AI-driven learning and largely stock specific views, which limits exposure to risk on those common dimensions and allows the strategy to navigate regime changes more effectively.
WEBCAST – 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 Wright 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.
Accepted for 1 CFP / IWI / CFA CE Credit
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