Chapter 279 : The Invisible Hand (14)
The dot-com bubble was, quite literally, mass hysteria.
Just by tacking “.com” onto the end of a company’s name, money poured in like rain.
For example, there was a company that sold records through TV commercials.
But when it created a subsidiary, launched a website, and added “.com” to its name?
Within just a week, its market cap skyrocketed tenfold, and its daily trading volume shot up by 91,000% compared to normal.
The market had gone completely insane.
But—
Here’s the real question.
Wall Street joined in on this stupidity?
Amazingly, even the front-line players of Wall Street took part in the madness.
If it had been retail investors, that would’ve been understandable.
They often rely more on trends or gut feelings than solid information.
But Wall Street is different, isn’t it?
They move by the numbers, not emotions.
Revenue, cash flow, P/E ratios, ROE…
They live and breathe numbers, and make decisions based on them.
And yet, even Wall Street tossed out their precise calculations and rode the bubble during the dot-com craze.
Why?
Later, people explained it this way.
—It was all FOMO. Everyone else was making money, and they were afraid of missing out.
In the end, it was all said to be greed.
But that’s wrong.
That wasn’t the real reason Wall Street moved.
They weren’t piling in just to make more money.
The real reason the so-called “smart money” acted so foolishly was…
Because of the relative performance system.
On Wall Street, performance isn’t measured in absolute returns, but in relative returns.
In other words, success isn’t judged by “how much did you make,” but by “how much more did you make compared to the benchmark,” like the S&P 500.
But during the dot-com bubble, that benchmark itself went crazy.
Take 1999, for instance.
The S&P 500 posted a 21% return, while the Nasdaq surged over 85%.
Meanwhile, value investors who stuck to number-driven analysis made just 8–10% that year.
“How are you supposed to compete with that?”
Now, think from a client’s perspective.
You paid hefty fees to park your money in a hedge fund…
And all you got was a 10% return?
Meanwhile, the S&P 500 next door doubled that?
At that point, wouldn’t you just cash out and dump your money into the Nasdaq?
Inevitably, rational investors on Wall Street faced relentless pressure from performance comparisons.
If they wanted to keep their clients, they had no choice but to beat the bubble.
But—
That was impossible.
With indexes doubling in a frenzy, how could rational investing ever catch up?
There was only one option left.
Climb aboard the bubble too.
Even knowing it was a bubble, they had to ride it.
Even knowing it would eventually pop, they had no choice but to stay on until the very end.
The lesson here is clear.
What drives Wall Street institutions isn’t FOMO.
It’s the relative performance system.
So if I want to inflate a bubble, I need to exploit that system.
Inside the rules of relative evaluation, I’ll leave no option but AI.
That’s my plan.
***
Not long after, this news shook the markets.
<Pareto Innovation, Launches ‘AFII ETF’ with BlackRocks>
<Investors Eye AI Infrastructure-Heavy Basket>
Ha Si-heon had launched an ETF (exchange-traded fund).
In plain terms, it’s a “stock basket.”
Instead of picking individual stocks one by one, you just buy the basket and instantly invest in everything inside.
This new ETF, named AFII, contained 35 high-growth AI infrastructure and hardware companies handpicked by Ha Si-heon.
And among retail investors, the reaction was explosive.
—Saint Sean blesses us with 35 chosen stocks—the survivors of the coming AI judgment!
—No more memorizing EBITDA.
—With one click, Sean’s philosophy is copied into my portfolio.”
—Praise the mercy of Saint Sean, who knows what retail can’t do and gifts us the holy Ctrl+C+V investment method.”
—‘Money doesn’t grow on trees,’ they say—yet Sean gifts us an orchard. Just enter $AFII.
Normally, investing in stocks requires careful study.
And when it comes to AI stocks, the difficulty was off the charts.
The term “AI company” itself was already too broad.
A semiconductor firm designing GPUs, an outsourcing company labeling images, or even a SaaS startup slapping “AI solution” on an API—all carried the same label.
Just trying to understand what an API or SaaS was could give you a headache.
To figure out which ones actually had money-making tech required the equivalent of a master’s thesis worth of research.
But now—
There was no need to even pretend to study.
Ha Si-heon had bundled the picks himself and put them neatly into a basket.
All you had to do was buy the basket.
AFII sold like wildfire.
<AFII Sees $100 Million Retail Inflows on First Day of Listing>
<Ranks in Top 1% of First-Day Inflows Among All New ETFs>
Usually, if a new ETF pulled in $20 million on day one, it would be considered a success.
But astonishingly, AFII saw $100 million flood in within a single day.
That kind of figure usually required institutional investors seeding the fund.
But Ha Si-heon pulled it off with nothing but retail investors’ blind faith.
However—
Even as massive sums poured into AI, Ha Si-heon had a different agenda.
‘I need to beat the relative performance system.’
In truth, that’s where an ETF’s real power lay.
AFII: +35.4%
S&P 500: +3.2%
NASDAQ: -2.75%
With performance compared in real time, the effect was undeniable.
But Ha Si-heon didn’t stop there.
<AFII Performance Comparison Report: Return Analysis vs. Major Indices (YTD/Monthly)>
<AFII Risk Indicators Summary: Volatility, Beta, Benchmark Tracking Error>
Normally, ETFs release a simple performance summary every month or quarter.
But Ha Si-heon was different.
He released the reports daily.
Each one compared AFII with various sectors, presented in easy-to-read tables and visualizations.
It looked something like this:
Index
YTD Return
Monthly Return
5-Day Return
AFII
+35.4%
+12.6%
+4.2%
S&P 500
+3.2%
+1.1%
+0.4%
Nasdaq
-2.75%
+0.8%
+0.1%
QQQ
+1.7%
+0.9%
+0.3%
XLK
+2.4%
+1.3%
+0.6%
XLI
+0.9%
+0.4%
-0.2%
ARKK
+4.1%
+2.2%
+1.5%
These reports were posted every morning at 8:45 AM on Pareto Innovation’s official website, free of charge.
They were also automatically linked to major investment platforms and financial portals so anyone in the market could access them easily.
The production costs for this system were far from cheap considering its simplicity, but Ha Si-heon spared no expense.
“When the numbers are good, you have to show them.”
When you’re crushing the competition in relative performance, all you need to do is wave the scorecard.
And once clients saw the reports, they began tilting their heads.
“AI returns… are actually pretty strong.”
Soon, they picked up the phone and called their fund managers.
“I’ve noticed AI is performing quite well lately. Do we have any exposure to it in our portfolio?”
The person on the other end scrambled to keep calm.
“AFII has only recently launched, so we’re still in the monitoring phase internally.”
“Most of its holdings are tied to LLM-related companies, which are currently overheated based on market expectations. Even Stark hasn’t finalized its product release schedule yet, so sustainability of earnings remains to be seen.”
“Our approach is fundamentally driven, so—”
The explanation was long, but the conclusion was short.
“So, in other words, we don’t really have any exposure right now?”
“…Yes, that’s correct.”
And after hanging up, only one calculation remained in the client’s mind.
“If I had just put my money into that ETF, I’d be sitting on a 35% return right now.”
Meanwhile, their hedge fund was charging 2% annually, plus 20% of performance fees.
And last year, they couldn’t even break double digits in returns.
By contrast, the ETF’s expense ratio was just 0.25% per year.
The decision wasn’t hard.
“Time to switch.”
And so, capital began flowing out of hedge funds and mutual funds en masse, and straight into Ha Si-heon’s ETF.
The timing was perfect.
By 2016, many hedge funds and mutual funds were already staggering under the rapid rise of ETFs.
Their fees were steep, and for two years straight, they had failed to beat ETF returns.
Now Ha Si-heon was publishing daily scorecards, openly distributing humiliating comparisons of their underperformance.
As a result, countless funds were getting bombarded by client inquiries: “Are we investing in AI too?”
They could no longer hold the line.
In the end, a wave of mutual funds, asset managers, and hedge funds begrudgingly poured into AFII.
Thanks to that—
41.34.
43.12.
Ha Si-heon’s ETF, which had debuted at just $20, broke $40 in less than a week.
Inflowed capital had already surged past $1.1 billion.
***
“Good.”
A satisfied smile crept across my face.
But I still didn’t let my guard down.
The capital inflows were nice, but another challenge loomed just as large.
“I need to make sure the bubble doesn’t burst.”
To be honest, the money pouring in now was indeed a bubble—swollen with hope and hype.
And bubbles are fragile things.
If earnings don’t back them up, or if the waiting drags on, they always burst.
And once a bubble pops, the narrative instantly flips: “AI was just another mirage.”
When that happens, the capital already invested would flood back out, potentially slowing AI’s very development.
‘That’s something I absolutely can’t allow.’
What I needed now was… a safe bubble.
Not easy, of course.
But not impossible either.
I already had a plan.
Executing it, however, required an enemy.
For the plan to work, I needed the cooperation—unwitting or not—of those I had designated as “the enemy.”
‘At this point, it’s about time an attack comes.’
And by “enemy,” I meant the macro funds allied with Gooble.
In the past, I had already cracked Gooble’s camp, split off Stein, and broken their alliance.
That fallout had inflicted huge losses on Gooble and the macro funds tied to it.
No doubt they were still sharpening their knives in silence, waiting for a chance to strike back.
But that was exactly what I was hoping for.
Because only if they moved against me would this bubble become safe.
And sure enough, the moment arrived.
<AI ETFs: Bubble? Experts Issue Warnings>