A Wall Street Genius's Final Investment Playbook-Chapter 279: The Invisible Hand (14)
The dot-com bubble was, quite literally, a case of mass hysteria.
Just adding ".com" to the end of a company’s name could cause money to pour in like rain.
Take this one example: there was a company that sold music records via TV commercials. Then it launched a subsidiary, built a website, and added ".com" to its name.
The result?
Within just a week, its market cap skyrocketed tenfold, and its daily trading volume surged by 91,000% compared to the average.
Put simply, the market had gone mad.
But here, one question arises:
— Did even Wall Street get caught up in this nonsense?
Surprisingly, yes. Even the players on the front lines of Wall Street joined in the frenzy.
If it were retail investors, it’d make more sense. They often rely on trends or gut feelings over concrete information.
But Wall Street? That’s supposed to be different. They don’t operate on emotion but on rigorous systems. Revenue, cash flow, P/E ratios, ROE... It’s a world where decisions are made based on clear, quantifiable data.
Yet, even Wall Street tossed aside their precise calculations and jumped on the bubble train during the dot-com era.
Why?
In hindsight, people have come to explain this phenomenon as follows...
"— This is the true power of FOMO."
Everyone else is making money, and I’m just afraid of missing out. In the end, it was all driven by greed.
But… that’s wrong. That’s not why Wall Street jumped in.
They didn’t join the craze to earn more. The real reason smart money acted so recklessly was because of the relative performance system.
In Wall Street, success isn’t measured by absolute returns, but by relative ones. That is, returns are evaluated based on how much better (or worse) they are compared to market benchmarks like the S&P 500.
And during the dot-com bubble, those benchmarks went completely insane.
Take 1999, for example. The S&P 500 yielded a 21% return. NASDAQ? It soared over 85%. Meanwhile, value investors using fundamentals were posting a modest 8–10% return.
"How are you supposed to beat that?"
Put yourself in the shoes of a client for a moment. You’re paying a hefty fee to a hedge fund, and in return, you get a 10% gain? Meanwhile, your neighbor’s S&P index fund is up more than twice that?
At that point, wouldn’t you just cash out and throw it all into NASDAQ?
Eventually, even the most "rational" Wall Street had no choice but to chase those returns. If they wanted to retain clients, they had to outperform the bubble.
But…
"That’s impossible."
With the indexes soaring at breakneck speed, how could anyone catch up using traditional methods?
There was only one way.
"Get on the train — just like everyone else."
Even if they knew it was a bubble, they had to ride it. Even knowing it would pop, they couldn’t afford to stay out before it did. That was the game back then.
And the lesson here is clear:
— Wall Street isn’t driven by FOMO. It’s driven by the relative performance system.
So, if I want to fuel the bubble, that’s the structure I need to exploit.
"I have to create a world where, within the relative performance system, AI is the only viable choice."
That’s my plan.
Shortly after, this news shook the markets:
<Pareto Innovation and Blackrocks launch the ‘AFII ETF’>
<Investors flock to AI infrastructure-focused basket>
Ha Siheon had just launched an ETF (Exchange-Traded Fund). To put it simply, it’s a stock basket — instead of picking individual stocks, investors can just buy into this one basket and gain exposure to everything inside it.
And this new ETF, named AFII, included 35 high-growth AI infrastructure and hardware companies, personally selected by Ha Siheon himself.
The launch was met with explosive enthusiasm, especially among retail investors:
— Saint Sean hath bestowed upon us 35 chosen stocks. These are the ones who shall survive the coming AI reckoning!
— No need to memorize EBITDA anymore. One click and Sean’s philosophy is copied straight into your portfolio.
— Praise Saint Sean’s mercy, who knew exactly what small investors couldn’t do and gave us direct Ctrl+C/V investment methods.
— They say ‘money doesn’t grow on trees,’ but Sean gifted us an entire orchard. $AFII—just get in the door.
Stocks are supposed to be hard—each one requires individual study. AI-related stocks are even more mind-numbing: The label “AI company” covers everything from GPU designers, outsourced image-labeling shops, even SaaS startups slapped with an “AI solution” API. Just understanding what an API or SaaS is made your head spin—and don’t mention figuring out which can actually make money. That would’ve required a master’s thesis worth of research.
But now—there’s no need to pretend to study. Ha Siheon handpicked and bundled the stocks, and you can just add the whole basket in one click.
AFII sold like wildfire.
<AFII saw $100 million in retail inflows on day one>
<Top 1% record for first-day inflows among new ETFs>
Normally, a new ETF is considered strong with $20 million on day one. But AFII had $100 million—all from retail investors. Such inflows usually come via institutional seed money. Ha Siheon did it purely on retail faith.
But—his real aim lay elsewhere:
“I need to beat the relative performance system.”
An ETF’s true power lies in performance comparison.
AFII: +35.4% S&P 500: +3.2% NASDAQ: –2.75%
Investors could compare returns in real time. But Ha Siheon didn’t stop there.
<AFII Performance Comparison Report: Key Index vs. AFII (YTD/Monthly)>
<AFII Risk Metrics Summary: Volatility, Beta, Tracking Error Analysis>
Most ETFs publish simple monthly or quarterly updates. He distributed daily reports—tables and visualizations that anyone could understand.
For example, daily at 8:45 AM on the Pareto Innovation website (and automatically to major investment platforms), this table appeared:
Index | YTD Return | 1-Month | 5-Day
---|---|---|---
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%
He paid for—and didn’t scrimp on—the daily reporting infrastructure to make it accessible to all for free.
“When the performance is good, you have to show it.”
In a relative evaluation system, when you’re winning by a landslide, all you need to do is flash the scorecard. And once clients saw that chart, they started tilting their heads.
“That AI return... looks pretty high?”
Soon, they picked up the phone and called their asset managers:
“I’ve seen AI is doing really well lately. Do we have any exposure to that sector in our portfolio?”
The manager on the other end scrambled to keep composure and replied:
“AFII is still newly listed, so internally we’re only monitoring it—”
“Most of its holdings are LLM-related, and the sector is currently overheated due to market sentiment. Since Stark’s product launch schedule isn’t confirmed, it’s too early to assess sustained earnings—”
“Our approach is fundamentally driven, so we prefer—”
The explanation was long, but the conclusion was short:
“So... you're saying we don’t have any exposure right now?”
“...That’s correct.”
And once they hung up, only one thought remained in the client’s head:
“If I’d just put this money into that ETF... I’d be up 35% right now.”
Meanwhile, the hedge fund they were paying takes a 2% annual fee plus 20% of the profits—despite barely clearing single-digit returns last year. The AFII ETF? Only 0.25% annually in fees.
The decision wasn’t hard.
“I’m switching.”
And so, capital started flowing out of hedge funds and mutual funds en masse—straight into Ha Siheon’s ETF.
Timing couldn’t have been better. Back in 2016, many hedge and mutual funds had already been shaken by the rapid rise of ETFs. Despite higher fees, they had failed to outperform ETFs for two years running.
Now, with Ha Siheon publishing performance comparisons daily, in full public view—and showing how poor the traditional funds were doing in contrast—fund managers were swamped with customer questions:
“Are we investing in AI or not?”
They couldn’t hold out any longer. Eventually, mutual funds, asset managers, hedge funds—all begrudgingly piled into AFII.
As a result…
41.34… 43.12…
Ha Siheon’s ETF, which debuted at just $20.00, skyrocketed past $40 in less than a week. Over $1.1 billion had flowed in.
“Nice.”
A satisfied smile crept across his face. But he wasn’t relaxing just yet.
Sure, the money was pouring in—but an even more important task remained:
“I need to make sure the bubble doesn’t burst.”
Frankly speaking, the money that had just come in was—without a doubt—a bubble. A bubble inflated by hope and narrative alone.
And bubbles, by nature, are precarious things. If earnings fail to materialize or if the waiting drags on too long, they inevitably pop. And once a bubble bursts, the world rushes to slap on a label:
“AI was just another illusion.”
Then, even the capital that had already poured in would flee en masse—potentially stalling AI development itself.
"That must never happen."
So what was needed now was... a safely inflated bubble.
"It won’t be easy..."
But it wasn’t impossible either. A plan had already been laid out. To execute it, however, one crucial thing was required: An 'enemy'.
And not just any enemy—specific individuals already assigned the role. Their cooperation, as enemies, was essential to the plan’s success.
“It’s about time they made a move.”
By 'enemy', I meant the macro funds aligned with Gooble. In the past, I had driven a wedge into the Gooble camp and pulled Stein away, shattering their alliances in the process. As a result, Gooble and its allied macro funds had suffered enormous losses.
Even now, they were likely grinding their teeth in silence, waiting patiently for a chance to strike back. But that was exactly what I wanted. Their retaliation was the key to stabilizing the bubble.
And just as I was waiting for the first move—it finally came.
<AI ETFs: Just Hype? Experts Raise Red Flags>
