June 15, 2026 | 1:00pm ET | 1 CE Credit
Emerging market debt is often misunderstood and frequently overlooked in US portfolios, yet shifting macro conditions, changing global capital flows and improving fundamentals across many emerging economies are forcing investors to take a fresh look at the asset class.
While emerging markets are commonly viewed through a regional or growth driven lens, EM hard currency debt represents a distinct US dollar income opportunity—one shaped by global macro forces, country specific fundamentals and dispersion that active investors can potentially harness over a full cycle.
Join experts from Pictet Asset Management for an educational webcast exploring how emerging market hard currency debt fits into today’s evolving fixed income landscape and what it could mean for diversified US investor portfolios.
What you’ll learn:
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:
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.
Alexandra Nagy, investment manager in Pictet Asset Management’s Quantitative Investment team, talks about AI development.
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 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.