
ALO35: Why Macro Investing Is Becoming More Systematic ft. George Patterson
Mittwoch, 3. Juni 2026 · 1 h 02
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Shownotes
How do quantitative investors adapt when markets, technology and macro regimes are constantly changing? In this conversation, Alan Dunne sits down with George Patterson, CIO of PGIM Quant Solutions, to explore the evolution of systematic investing from the 1990s to today’s AI driven landscape. They discuss regime detection, inflation risk, portfolio construction, machine learning, private markets, volatility overlays and the growing role of language models in investment research. George also shares insights from decades in quant investing, including lessons from Covid, the importance of model discipline and why communication skills matter as much as technical expertise.
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Episode TimeStamps:
- Introduction to George Patterson and his journey from physics to quantitative investing
- Why multidisciplinary teams matter in modern quant investing
- Inside PGIM Quant Solutions and the evolution of multi asset investing
- How markets and macro investing have changed since the 1990s
- The future of the 60/40 portfolio and institutional portfolio construction
- Private markets, liquidity challenges and institutional investor concerns
- Inflation, commodities and building modern inflation hedges
- Detecting macro regimes using quantitative models
- The hardest part of systematic investing: trusting the process
- Covid, model failures and managing regime shifts in real time
- Portfolio protection, options strategies and volatility overlays
- How AI and large language models are transforming quantitative research
- Fiscal risks, inflation concerns and the changing rate environment
- Simplicity versus complexity in quantitative model design
- Why markets evolve faster today and how models must adapt
- Retail investors, meme stocks and market distortions
- Emerging markets and where long term opportunities may exist
- The future of quant investing and the limits of AI hype
- George Patterson’s career advice for aspiring quants
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