The Meb Faber Show
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Andrew Ang: Should AI Agents Run Your Asset Allocation? | #653
In today's episode, Andrew explains how a swarm of AI agents can reinvent the investment workflow rather than automating pieces of it. He shows how specialized agents, each running its own asset class or portfolio method, vote on one another's allocation calls. He also argues for diversification across signals, factors and time. To close, Andrew reveals how the quiet drag of taxes erases roughly 36% of a stock investor's returns over 30 years.
Key Points
- AI agents can broaden investment research, challenge each other productively, and improve decision-making when they operate within clear governance and guardrails.
- Taxes can quietly consume a large share of long-term returns, making account placement, asset location, and tax-aware portfolio design a major source of after-tax alpha.
- Diversification matters at every level, from using multiple signals and factor models to combining different sources of value, momentum, and quality in a portfolio built for changing regimes.
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Transcript
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