Orion's The Weighing Machine Michelle Cluver of Global X ETFs - The Long Game of AI
Today on the podcast, Ben Vaske is joined by Michelle Cluver, Head of ETF Model Portfolios at Global X ETFs. Michelle joined Global X in 2018. She is responsible for overseeing the model portfolio solutions team in the construction and management of Global X’s suite of ETF model portfolios. Michelle and her team develop the macroeconomic and market views that shape portfolio positioning. Additionally, she works closely with the ETF model portfolio team on maintaining and assessing the quantitative models behind Global X’s thematic model portfolios. Previously, Michelle worked at Merrill Lynch Wealth Management in its ETF model portfolio business. Prior to Merrill, Michelle worked for a boutique asset management firm, with a focus on both South African and developed market equities. Michelle holds a master's degree in International Finance from the Amsterdam Business School and is a CFA Charterholder.
Key Takeaways
- What is Michelle’s favorite home-cooked meal or recipe?
- Learn about Michelle’s current role at Global X ETFs and her career background
- What were the coolest and strangest things Michelle saw at the CES (Consumer Electronics Show) Conference in Las Vegas this year?
- In Michelle’s opinion, where are we today in terms of the AI adoption cycle? Are we in early experimentation or getting into early commercialization?
- Are there any key differences or similarities between the AI boom and the dot com or mobile phone boom that Michelle would highlight?
- In terms of AI use cases and real world adoption today, are there any industries or business functions that are seeing true, tangible gains from AI currently?
- Is there anything that Michelle thinks investors are misunderstanding about how quickly or slowly this AI adoption is going to show up in company fundamentals?
- As Michelle thinks about the CapEx wave, does she think it is sustainable and does she think this level of CapEx will need to continue for AI to continue to advance?
- What less obvious areas does Michelle think investors should be looking at in the broader AI ecosystem?
- How generational of an innovation is AI and are we in a place where we can say “yes, this is going to be the thing for the next few decades?”
- Does Michelle view AI as inflationary, long-term deflationary or structurally neutral?
- Are there shifts in the dynamics around the competitive edge between large and small AI companies and are there opportunities in the space for small companies to make a big impact?
- How should investors and advisors be thinking about valuations in the present day given the level of optimism that’s already priced in?
- What sort of signals should our listeners look for that may show we’ve reached peak enthusiasm in AI?
- For the average investor, what would Michelle’s key point of advice be for a simple way to gain exposure to AI but doing so in a risk-aware way?
- What might getting AI right in a long-term portfolio actually look like for a long-term investor?mizue
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