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Sep 3 20 tweets 6 min read Read on X
How to find 10 baggers according to Mark Mahaney🧵

10 timeless lessons for public tech investors. Image
The dude has covered tech stocks for the last 25 years Image
He's had some notable misses:

SELL on $AMZN
SELL on $TWTR
BUY on $SNAP
BUY on $APRN

But he's v v transparent. Image
Lesson 1: Pick bad stocks and you're fucked.

You're gonna lose money.

ESPECIALLY if you trade around stocks.

(He's not a technicals guy) Image
Lesson 2: Even if you pick right, expect disgusting downside volatility.

Even best in class stocks crash 20-40%
This is even worse if you're highly concentrated. Image
Lesson 3: Don't trade around quarters.

Buy and hold companies for their long term fundamentals.

To trade around quarters, you need to be:

1. Right on fundamentals.
2. Right on near term expectations (difficult to do).

Just stick to the long term.

Ignore short term prices. Image
Lesson 4: Tech stocks follow revenue growth.

Revenue.
Revenue.
Revenue.

Look for 20%+ Revenue.

Stock prices SOMETIMES follow earnings.

Stock prices ALWAYS follow revenue. Image
Top tip #1: focus on Growth Curve Initiatives (GCI)

E.g. new products, new markets, new pricing tiers, anything that expands the TAM. Image
Pro tip #2: Only a FEW tech companies can truly grow >20% QoQ for sustained periods of time.

Double down on these if you find them. Image
Pro tip #3: Product innovation is king.

Companies that have avenues/areas to reinvest excess FCF at high rates of return will continue to compound for a long long time. Image
Lesson 6: BIG TAM + Low penetration = HUGE runway.

TAM leads to growth at scale. Image
Lesson 7: Follow the consumer VALUE PROP - not the money.

Customer love is key. Image
Lesson 8: Management matters.

Founder-led companies.
Long term vision.
Deep industry knowledge.
Customer obsession.
Strong technical backgrounds.
Quality c-suite. Image
Lesson 9: Valuation isn't precise - just be in the right "ballpark."

Valuation is more art than science.

Don't fall into the precision trap.

Valuation is SECONDARY to business fundamentals.

The question you need to answer is "does this valuaiton look ballpark reasonable?" Image
(Esp. when companies have minimal earnings like $NFLX) Image
Lesson 10: Hunt for Dislocated High Quality (DHQ)

How to minimize the 2 investing risks:

1. Fundamentals -> pick high quality tech cos
2. Valuation -> buy stocks when they're 20/30 off the highs or trading at discount to its growth rate.

This works EVEN with high risky stocks.
What makes a high quality company?

1. >20% revenue growth
2. Product innovation
3. Large TAMs.
4. Customer value prop
5. Great management Image
How often do they get "dislocated?" -> Frequently. Image
CONCLUSION: 10 lessons summarized. Image
If you're looking for a stock screener to find 10 baggers using this criteria - I recommend Koyfin.

It's hands down the BEST investment platform I've tried and I now use this exclusively over a bloomberg terminal. Just incredible software.

koyfin.com/affiliate/koyf…

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More from @zoomyzoomm

Aug 28
$40k -> $600

Unreal. Image
Jesus fucking Christ man. Image
No shit you’re done with options bro Image
Read 12 tweets
Aug 16
🧵Why the mag 7 are about to implode:

1/ The AI capex wave by $AMZN $MSFT $GOOG $META due to rising gen AI inference workloads has a significant unintended consequence the market is not ready for.

The hidden AI killer is IMPAIRMENT LOSS (led by overusage and tech obsolescence). Image
2/ In 2025, AI capex spend will hit >$300b, funneled toward data centers & GPUs to support generative AI workloads.

This is rational given training and inference demand, but it overlooks a critical issue: hardware is being utilized at rates FAR exceeding original design specs. Image
3/ Traditional depreciation schedules for GPUs are 5Y, yet the intense demands of gen AI (continuous, high-load operations)cause physical wear and tear much quicker (within 2-3Y).

Eg $NVDA shift to annual GPU architecture upgrades makes existing investments outdated more rapidly Image
Read 9 tweets
Aug 16
The "AI Trade" has largely played out in the US in the last 3Y since ChatGPT led to:

An explosion in:
GPU spend $NVDA
Hyperscaler inference $MSFT $GOOG $AMZN
AI startups founded

Missed the US AI trade? This is how you can catch the China AI trade (which hasn't even begun yet):
1. The bottom of the stack: GPUs.

Personally, I think this stack is not as investible. Just long $NVDA as most China cos will buy H20s.

China doesn't have a "Dominant GPU champion" that you can buy given Huawei is private & the chips are inferior.

$SMICY $HHUSF are far behind Image
2. The second layer of the stack: hyperscalers.

In contrast to the US cloud giants, cloud adoption in China is SO far behind (5% of the size of the USA).

All Gen AI inference workloads will pass through these guys.

Expect far higher 3Y growth rates:

$BABA $TCEHY $BIDU $KC Image
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Read 11 tweets
Aug 14
Why AI is a house of cards:

1. You pay $200 a year for an AI app (like Cursor).

2. Cursor pays OpenAI $500 for API tokens ($300 of which is VC funding).

3. OpenAI pays AWS $1000 for compute ($500 of which is VC funding).

4. $AWS pays $10k for $nvda GPUs.

See the problem?
Unless you as a user are miraculously comfortable paying $1k for the AI app

The only thing propping up AI is VC funding

No VC funding:
The AI application layer is unprofitable
The LLM layer is unprofitable
The compute layer is unprofitable
The GPu layer is unsustainable
The bulls say that inference cost is dropping exponentially (it is)

Which would mean the cost of compute to LLMs like OpenAI (and by extension to the AI apps like cursor) drops too

But this must happen BEFORE they run out of VC funding

And hinges on how much users will pay
Read 17 tweets
Aug 5
Your job is to find a way to hit $1-3 million and become unemployed by age 40.
Make your money

Then get off the grid.

This is all that matters.

It's a lot easier than you think.

Read 11 tweets
Jul 27
When your portfolio gets big enough you can just retire and withdraw cash on margin whilst staying fully long and never sell stocks (or incur taxes).

Billionaires do this all the time.

It’s possible for everyone with a few hundred thousand (although works better at scale).
BTW

This strategy becomes increasingly more attractive as interest rates get closer to 0%, margin rates drop, CD/risk free rate drops, discount rate drops and equities rip higher
Read 8 tweets

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