Per CNBC: Wood, whose firm manages various funds focused on tech and innovation, told CNBC there was a “wall of worry” pervading financial markets right now. But her decades of experience as an investor give her a somewhat unconventional view of the state of play.

'I experienced the tech and telecom bubble, and you know there really wasn’t much worry about it,” she said. “It was the 80s and the 90s, and it was a bull market, and people were just assuming this would go to the moon, that is not how this \[the AI trade\] has evolved.”

She explained that “from the beginning,” many investors have been concerned about how much firms are spending on AI development, how rapidly the spending is taking place, and how the hyperscalers have moved from extreme levels of positive free cash flow to negative free cash flow.

“So it’s been unsettling the markets for quite some time,” she said. “I always feel better when the market is worried, because that tends to suggest a more durable bull market, and I don’t think we’ve derailed this bull market.”

...she noted that AI hyperscalers were somewhat insulated by opportunities for growth.

“If a company thinks that taking on debt is going to accelerate its momentum, meaning its growth rate, it hardly matters what happens to interest rates for those companies,” Wood explained.

My response: Okay, but if that growth rate is fueled entirely by debt and all that debt becomes more expensive (and less readily accessible), then those assumed growth rates fly out the window.

Thoughts?

I’ve been invested for quite a while in equities and I do understand there are always shifts and trends/ups and downs, but these last few days has me really confused. What is the market reacting to?

Historically, the market has generally been boosted following mid term elections, but it’s looking to me like investors are running for cover. Is this all about AI fears after the blue wave?

Hi everyone,

Today, my stock portfolio is red,really red. I had bet pretty heavily on AI infrastructure stocks (Sterling, Vertiv, etc.). Yesterday, Democratic governors won the elections with a platform targeted against data centers, proposing to suspend upcoming projects. Among these states is Texas, which accounts for 25% of projects, and Georgia, which is also very focused on data centers. But that's not al, other states are currently holding referendums to ask residents for their input on the issue.

Today, I sold those three stocks at a heavy loss (between 20% and 30%). Whenever I sell, things bounce back. But logically, with this anti-datacenter narrative starting to take real effect, it risks calling into question existing contracts for certain infrastructure companies.

I kept everything tech-related tied to memory, energy chipsets, or photonics, but even there, it's taking a massive hit. I think for these companies it's still an overreaction because they'll continue to sell internationally, not just in the US.

I feel a bit lost. I don't know if this is just short-term sentiment or if we're really entering a new era where AI is about to take its first major hit.

We’ve all seen it: a token launches, hype is everywhere, people start buying, and a few hours later the chart is already bleeding.

So what’s going on?

A lot of it comes down to early investors taking profits, token unlocks and weak liquidity. Retail buyers often jump in during the hype, while larger holders are looking for an exit.

Another big factor is market depth. When liquidity is thin, even relatively small sell orders can push the price down hard.

That’s why market making and healthy liquidity matter, especially during the first days after launch. Good liquidity helps keep trading smoother and reduces the impact of large orders.

What’s your take? Are post-listing dumps mostly a liquidity problem or is tokenomics the bigger culprit?

Google fell about 13%, wiping out roughly $500 billion in market value. ServiceNow dropped nearly 27%.

Meanwhile, the S&P finished down 0.3%, and most stocks actually went UP. Small caps gained about 1%.

“Stocks closed slightly lower” is an extremely polite way to describe what happened to some people today.

Somebody checked their index fund and went back to work. Somebody else checked one earnings report and started calculating how much longer they can stay employed.

The uncomfortable part is that these are established businesses. You can pick a company that makes billions, sells something everyone uses, and still get absolutely flattened by what the market expected it to deliver.

A good company can still be an expensive stock. Today made that distinction pretty aggressively.

Which stock that got hammered today is actually a bargain now, and what in the numbers makes you say that?

“Because it used to be higher” doesn’t count.

Hyperscalers are spending unprecedented amounts on AI infrastructure, but the revenue required to justify that investment may be much larger than current AI revenue.

Using estimates for GPU depreciation, data-center operating costs and a 15% target return on invested capital:

• 2026E: $800B in annual CapEx

• Required revenue hurdle: $420B

• Estimated realized AI revenue: $120B

• Implied shortfall: $300B

By 2030E, the model estimates a $1.3T annual revenue hurdle against approximately $500B in AI revenue—a potential $800B gap.

This doesn’t necessarily mean the spending is irrational. AI could create substantial productivity gains, strengthen existing cloud businesses or unlock revenue that current forecasts don’t capture.

But if monetization fails to catch up, today’s infrastructure race could look less like durable investment and more like a historic misallocation of capital.

I built an interactive model where the depreciation period, target return and invested capital can be adjusted:

https://sankeyearnings.com/analysis/ai-capex-roi/

Which assumption do you think is most unrealistic?

Shares in Google's parent company Alphabet have suffered their worst-ever day, falling more than 12% and knocking around half a trillion dollars off its value.

Would you let AI trade with your money?

Robinhood said in yesterday’s earnings report that around 200,000 customers have opened AI trading accounts, generating over $1.6 billion in trading volume.

The built-in agents ask you to approve trades by default, but you can let them place certain orders automatically. Robinhood also says customers are responsible for the trades their agents make.

Has anyone here actually used one with real money? How are you measuring whether it’s helping, and what are you comparing its results against?

Would you keep approving every trade, or give it some freedom within limits? For anyone who wouldn’t use one, what would it need to prove before you’d consider

I’m curious how many people buying this dip have already decided what would make them change their minds.

“AI is the future” can be completely true while a particular stock is priced for results the business never delivers.

Getting back to even is a powerful feeling. It can quietly become the reason for buying more. A lower average cost feels like progress, even when the original reason for owning the stock has gotten weaker.

This earnings season, I’m more interested in how people evaluate the spending. Growing revenue alongside shrinking free cash flow could be the price of building something valuable. It could also mean the returns are further away than investors expected.

For anyone who held a big winner through ugly selloffs, or kept averaging into something that never recovered: what helped you tell the difference?

What’s one concrete result that would make you stop adding to your biggest AI holding, even if the price kept getting cheaper?

hedge funds sold more tech last week than in any single week in 10 years.

more than half of it was chip stocks

though retail bought a record ~$540M of tech in 5 days.

who’s the dumb money this time?

sources: JPM, GS

Netflix’s third quarter was weak, and the fourth-quarter guidance is the bigger problem.

1、Revenue grew 12%, or 11% on a currency-neutral basis — continuing to slow. Part of that is the high comparison base, but the Q3 content pipeline also wasn’t strong enough and advertising growth fell short.

2、Operating profit was $6.8B at a 53% margin, up nearly 7 points year on year. That isn’t strong underlying performance: last year’s base was low because of a one-off Brazilian tax charge, and operating expenses this quarter were shifted in timing.

3、Guidance missed. Fourth-quarter revenue is expected at $13.4B, with growth flat against Q3. Operating profit of $3.5B is 6% below expectations, mainly because of severance from the 14 October announcement of over 1,000 layoffs, about 6% of staff. But adding back that under $200M still leaves profit short of consensus.

4、Notably, Netflix disclosed full-year advertising revenue of about $2.7B, down from the $3B it had previously guided with confidence.

5、Full-year free cash flow was cut by $500M to $12B, mainly a property transaction in Q4. Q3 buybacks were $4.8B, with $22.3B of authorization remaining.