Serenity's Investment Strategy: How He Achieved 225x Returns in Undervalued Stocks

Breakdown of the Investment Strategy of Wall Street's Top Retail Investor, Serenity
Original author: nini, cryptocurrency analyst

You bought NVIDIA, sold it after a 30% gain, and felt you still had a bit of cleverness.

It then rose another 120%, and after staring at the K-line chart for five minutes, you grew more and more frustrated.

This is actually how most retail investors look.

In 2022, one person did the exact opposite of the crowd. Instead of buying NVIDIA, he bought a company that supplies NVIDIA—a little-known stock with a $700 million market cap that 90% of people had never heard of: $AXTI. The stock was trading at $12 at the time, but later rose above $70.

This person is named Serenity, and they became a sensation in investment circles both domestically and internationally this year. Of the 35 assets publicly tracked, 31 rose in value, delivering a 225x return, prompting even Bloomberg and Reuters to follow their tweets for coverage.

After reading dozens of his posts, I realized that what he did was completely different from what most people did when buying NVIDIA.

What did the general public do when buying NVIDIA? They checked the P/E ratio, looked at the revenue growth in the financial reports, read news saying AI was about to explode, saw that Northbound funds were buying, and then placed the order. I could do this whole routine with my eyes closed.

What did Serenity do before buying $AXTI?

He started with NVIDIA's GPUs and mapped out the entire supply chain. GPUs require data centers to operate, data centers need optical modules to transmit data, and the most critical component within optical modules is the laser diode, whose raw material is indium phosphide. Then he did something I never would have thought of—he investigated the global production capacity distribution of indium phosphide.

There are two companies worldwide capable of mass-producing indium phosphide substrates. $AXTI holds one-quarter to one-third of the market.

In other words, as long as AI chips continue to be manufactured, all optical module manufacturers will have to source their raw materials from these two companies. And this landscape won’t change anytime soon, since the timeline from factory construction to mass production spans years.

Then he reviewed the company’s patent filings, customer list, production capacity limits, and upstream mining sources. Only after completing all the checks did he place the order.

Perilla leaf theory

He named this strategy the Perilla Leaf Theory.

He says you go to a high-end sushi restaurant where everyone is staring at the fatty tuna belly, but what the kitchen truly can’t run out of is shiso leaves. Without tuna, you lose a few dishes on the menu; without shiso leaves, the whole restaurant might have to shut down.

In the AI industry, NVIDIA, Microsoft, and OpenAI are the fatty tuna belly. Perilla leaf is a material name so obscure you can barely pronounce it—a little-known company with a market cap of billions and no analyst coverage, and a component with only two suppliers worldwide; without it, the entire chain grinds to a halt.

This theory, when broken down, consists of just three steps.

AI boom → surge in GPU demand → GPU manufacturing requires lithography machines → the core component of lithography machines is lenses → who makes lenses globally? Zeiss, the only one. Continue. Who supplies the special glass used in Zeiss lenses? Probably another small Japanese manufacturer.

At each level, ask the same question: What is it that the next level does that no one else can replace?

Most people might stop at the second layer and begin discussing whether NVIDIA's P/E ratio is expensive. But Serenity breaks it down to the fifth and sixth layers, all the way to the company with the smallest market cap and the most unfamiliar name.

More than three, pass! Due to sufficient competition, there is no pricing power.

Two, watch closely.

One company or a de facto monopoly—that’s it.

The logic is simple: the more AI expands, the more money flows upstream along the supply chain. As the water rises, all boats rise with it.

But if a certain link has only one ship, it doesn't just ride the upward trend—it can also hold the downstream parties hostage, forcing them to use only me and making the rules.

Don’t seek approval—instead, we deliberately wait for experts to challenge us.

Someone pointed out that a step in his logic was too rushed, so he went back and reworked it. Someone told him he missed a supplier, so he went back and added it. He kept refining until all gaps were closed and no one could criticize—then he placed the order.

He himself said that ChatGPT won't argue with you. You feed it an analysis, and it will always agree that your reasoning makes sense. So, you need to give the material to a real person.

$SIVE: Second validation using the same methodology

He has used this method more than once.

In 2025, he heavily invested in $SIVE, a Swedish semiconductor company specializing in lasers, with a market cap of billions of dollars, valued in Swedish krona and largely unanalyzed by U.S. analysts.

Why is he targeting it? Because the next-generation optical communication architecture for data centers is CPO, and CPO has a fundamental physical limitation: silicon cannot emit light. If it can’t emit light, how can it transmit data? An external laser module is required. $SIVE’s high-power continuous-wave lasers serve as the external light source for CPO.

He walked through the chain again: NVIDIA GPU → data center expansion → CPO optical interconnect → surge in demand for external light sources → $SIVE is one of the few globally capable of supplying.

After buying it, the asset increased nearly twentyfold.

RPI: The Newly Emerging Demand Wall Street Missed

Then there's the Raspberry Pi he posted in February 2026.

RPI, a UK company that produces low-cost microcomputers, sells a single board for $35, designed for children to learn programming. Wall Street analysts unanimously expect annual revenue growth of 14%.

He wrote another number: 55%.

How did he calculate it? He looked into the developer community. On GitHub, a large number of AI developers have started deploying AI agents using Raspberry Pi, and the growth curve of related repositories is nearly vertical.

He analyzed purchase discussions across various forums and developer growth trends, then deduced that Wall Street’s revenue models completely failed to account for this new demand, missing at least 40 percentage points.

Within two days of the tweet, RPI's stock price rose nearly 90%. Two months later, the earnings report revealed actual growth of 58%, while Wall Street's consensus was 14%.

Three cases: $AXTI, $SIVE, RPI — the underlying logic is exactly the same.

Find a position in the supply chain where pricing has not yet been set, but demand is already locked in.

The three most common pitfalls for retail investors

Speaking of this, I’d like to discuss the three most common mistakes retail investors make when buying stocks, and how this approach can address these issues.

You see a certain sector heating up, a particular coin rising, and everyone talking about it online, so you jump in. But right after you enter, it starts dropping—you can’t hold on and end up selling at a loss. Then, right after you sell, it starts rising again... and you’re left confused.

Why? Because when something becomes so popular that even someone with limited knowledge like me has heard of it, its price has already been fully priced in by the market.

Companies at the first and second layers—NVIDIA, Microsoft, TSMC—are being watched by analysts worldwide and bought by capital from around the globe. Why do I think I’m faster than everyone else?

Serenity’s approach is to dig deeper. Below the third layer, analysts don’t cover them, and institutions don’t build positions because the market cap is too small and liquidity too poor for them to enter. These areas contain numerous pricing inefficiencies to exploit.

This solves a problem: you don’t have to race against the smartest people in the world—you can slowly turn things over on a track where no one is competing with you.

The real reason for the panic is simply that you don’t know what your purchase is actually worth.

You might have bought because you thought it was going to rise. But when it looks like it’s going to fall, will you sell? Without your own judgment anchor, any small market movement can shake your mindset.

Serenity’s approach forces you to answer three questions before placing an order: Is this step indispensable? How many suppliers are there globally? Is downstream demand rising or falling?

After answering these three questions, you have a logical anchor independent of the stock price. There’s no need to panic over short-term declines unless the answers to those three questions change.

This solves a problem: price movements aren't based on faith, but on the supply chain map in your hands.

PE, ROE, earnings growth, northbound funds, dragon and tiger list. When you open any stock trading app, everyone sees the same interface. All this information is already reflected in the stock price.

What does Serenity look at? Patent databases, supplier directories, customs export data, developer discussion volumes on industry forums, and technology pathway comparisons in academic papers.

These things are free and public, but most retail investors have never opened them in their lives.

This solves a problem: when your sources of information differ from others', your judgments may also differ.

This method also has limitations it cannot solve.

Of course, this method isn't foolproof—it also has a few things it can't solve.

First, Serenity has experienced losses herself: UPWK -35%, HIMS -50%, CRCL -45%. Even with the right approach, not every trade will succeed. No matter how accurately you map the supply chain, issues with a company’s operations, sudden shifts in industry direction, or changes in macroeconomic policy can all lead to setbacks.

Second, he is anonymous. All his claimed titles—former AI scientist, Nature paper author, rejecter of an NVIDIA offer—are self-reported and unverifiable. He buys micro-cap stocks, and a single tweet from him can pump the price; his followers buying in can further drive it up. He has never publicly disclosed when he sells.

Third, his entire position is based on two assumptions: that CPO will become the sole technological pathway for data centers, and that humanoid robots will be deployed at a scale of billions. If either assumption is proven wrong, the logic behind many of his investments would collapse.

His method tells you that this position is choking, but whether the neck itself remains there is something you need to determine for yourself.

What if you use it to check out Crypto?

I tried using this method to look at the Crypto space.

Start by breaking down from the meme launch platform. Platforms like Pump.fun → what do they rely on? Market-making protocols → where does the liquidity for these market-making protocols come from? Keep tracing downward.

Here’s what this approach actually gives you in plain terms: When you get used to digging from the top down, you won’t rush in just because something’s going up. You’ll naturally ask: Which layer is it in? Who’s upstream from it? Who’s upstream from that? And where’s the single step that only one or two players control—everyone has to go through it?

I thought deeply and reflected extensively, and suddenly it all became clear.

I’m not saying I found some secret to wealth; I just suddenly realized that most people, when buying anything—whether stocks or crypto—are stuck at the first layer of the supply chain. Whatever’s trending, they buy it; their entire decision-making radius doesn’t extend beyond the watchlist page of their trading app.

So, the strategy of the stock guru Serenity isn't about directly telling you what to buy, nor is it about getting you to FOMO.

What we need to do is something else: pull you out of the first floor where everyone is crowded, and show you that the pricing on the fifth floor hasn't yet been discovered by the market.

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