【Livestream Clip 2｜Dr. Franklin Wu: It's Long-Term Yields, Not Earnings, That Hit High-Valuation Tec

【LIVESTREAM RECAP｜Quantitative Anaysis Framework & Trading Logic for AI + Semiconductor Investing】

Hi Tigers! In this session a quant researcher walked us through AI and semiconductor investing using just four words — market, business, price, and risk. The flow was clean: first, is the macro environment helping us or fighting us; then, is the AI demand story still real; next, is this a good place to enter on the chart; and finally, what do we do if we're wrong. Along the way he brought in long-term yields, VIX, QQQ, and SOXX — the indicators you can actually use — and kept it substantive, never hand-wavy.
Full replay 👉 Quantitative Anaysis Framework & Trading Logic for AI + Semiconductor Investing

【ABOUT THE GUEST】

Our speaker, Dr. Franklin Wu, holds a PhD from the University of Chicago. After graduation he joined a top brokerage in China, and he is now a quantitative researcher at a financial institution in Shanghai. His background blends physics, quant research, and strategy development. What makes his perspective rare: instead of buying stocks based on stories, he uses data and frameworks to separate the information that matters from the noise.

【HIGHLIGHTS】

1. A four-word framework: market → business → price → risk, so you don't pick a ticker first and hunt for reasons after.

2. Three counterintuitive takeaways: AI semis are still strong but not every "AI" stock wins; rates hit high-valuation tech harder than earnings; 3x ETFs are not 3x long-term returns.

3. A practical dashboard: just five reads — 10Y Treasury yield, Fed expectations, VIX, QQQ, and SOXX.

Live Recap:

Live Recap 1: A Hawkish Jackson Hole, the "Bessent Put," and Why Tech Is Watching the 30-Year

Live Recap 2: Why Semiconductors Are Still the "Hard Currency" of the AI Trade

Live Recap 3: Turning a Bullish View Into a Trade — Technicals, QQQ and SPCX Case Studies

Live Recap 4: Leveraged ETFs, the September Playbook, and Q&A Highlights

【THIS CLIP】Why do good companies still fall? Franklin nails it: the company story tells you what you want to own, while the market setting tells you what to be careful about. When safe bonds suddenly pay more, investors won't pay a huge price for profits that arrive 5 to 10 years out — so high-valuation tech gets pressured. He shares his own experience holding Nvidia through its 50%+ drop in 2022 and its full recovery the year after. The best part: he explains the rates-to-valuation logic with zero formulas — the very piece most retail traders overlook.

We genuinely recommend watching the full replay — the parts many people skip are exactly how rates transmit to tech step by step, and why 3x ETFs struggle to recover long term. Fill those in and your read on AI investing gets a lot more grounded.

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(For education only, not investment advice.)

Full replay 👉 Quantitative Anaysis Framework & Trading Logic for AI + Semiconductor Investing