FSD: Jane Street — Lumida Wealth : Non-Consensus Invest Beyond the Ordinary

In this FSD episode, the day's actual alpha comes first (go buy flowers, seriously), then it splits between two things worth thinking about. First, a health and longevity segment fresh off a cardiologist visit: why cardiovascular disease is the number one killer, the fork between insulin resistance and atherosclerosis, a carnivore-diet experiment that sent LDLs the wrong way, and the case for trying a PCSK9 inhibitor. Then the focus shifts to what's really driving this market: the factor "kill box" versus "reward box," why the winning move is front-running the quant flows at Jane Street, and how an AI-built breakout strategy became the best performer on the book.

(00:00) 80s synth-pop, puns, and the flowers tip
(02:30) Cardiology visit: cardiovascular disease as the top preventable killer
(04:00) Insulin resistance vs atherosclerosis and the diet fork
(06:00) The carnivore diet experiment and rising LDLs
(08:00) The statin debate and trying a PCSK9 inhibitor
(10:00) Exercise as the drug that would be worth more than Lilly or Nvidia
(12:00) Longevity as an investing theme: senior living, travel and leisure, aging demographics
(14:00) A Jane Street market and the factor kill box vs reward box
(16:30) Front-running Jane Street and why it needs less capital than you'd think
(18:00) The factor tools coming to the Lumida app
(19:30) Communication sector setup for mean reversion
(20:30) Momentum broadening away from semis, still holding DRAM
(21:30) Buy stocks two weeks before earnings, and the bank setup for July
(23:00) Why OpenAI's delayed IPO hurt Goldman and Morgan Stanley
(24:00) Buy-the-dip research and the AI breakout-detection strategy
(26:00) Why AI will be hugely disruptive to investing
(27:30) Penthouse social event and a hello from his son

About the show: Non-Consensus Investing is Ram Ahluwalia's running commentary on markets, where he shares how he's actually positioning capital and talks through the ideas most investors are missing. Real-time analysis, specific names, and a bias toward what's overlooked rather than what's crowded.

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