Quantchemist

19 | Macro → Bottlenecks → Quant → Sentiment Extracting alpha from the physical layers of AI infrastructure.

[Quantchemist @riceeyfn]

March 31: $6,200 
Net deposits: $8,800 
Today: $100,000+ 

I’ve seen many users on X tracking the "all-in challenge" to turn 10k into 100k. While I didn't use that specific strategy, I thought I should use this opportunity to introduce myself & spread some knowledge on how investors should go about turning a small amount into a large amount.

1. Portfolio Concentration: This is the single most important factor for rapid scaling. Pick your highest-conviction trades and limit yourself strictly to those. Ideally, hold fewer than 5 tickers at any given time.

2. Micro/Mid-Cap Focus: With low starting capital, you need asymmetry. Target companies under a $50B market cap that possess explosive structural drivers where you can afford meaningful share sizes or multiple options contracts. (The only exception is trading credit/debit spreads).

3. Execution & De-risking Rules: Knowing when to harvest profit or cut losses is the hardest part of the journey. Most of this comes with experience and is dependent on the trade. To systematically de-risk, I frequently sell half of a position at a 100% gain to let the remaining house money ride for free, or roll up contracts on my highest-confidence winners. Because of this rule, I never start a position with fewer than 2 contracts or 2 shares. Use this newly extracted cash to search for more alpha or add to smaller positions. As you build the value in your account, you can begin to trade higher MC companies and diversify slightly more. 

4. Misconception: Most retail traders see a 1000%+ return in 2.5 months and assume it requires gambling on short-term weekly options. The truth is I executed this almost entirely via common shares and LEAPs stretching from a few months out as far as 2028. I only allocate a fraction of capital to short-term momentum. The goal is to maximize dollar returns while taking on the absolute minimum amount of mathematical risk. Consistent 50%+ gains and some big winners will move the needle a lot faster than you think.  

Since this is my first formal post, here is a bit about my background. I am 19, based in Canada. I completed one year of Chemical Engineering where I was at the top of my program (100% physics 1, 90% exam weighting) . I am deeply interested in  STEM  topics which I incorporate into my stock analysis. Currently, I am working at a biotech company. At 12, I made my first few thousand from buying broken iPhones, fixing them and flipping for a profit. I also made a few thousand from Fortnite. Other than that I built my net worth from working and investing. 

Anyways, if you found these tips on how I scaled this account helpful drop a follow. I will start to post investment theses, analysis and ideas here on X.

[Elon Musk @elonmusk]

@PeterDiamandis For now

[Quantchemist @riceeyfn]

$VPG $AMBA $OUST $TSLA

[Quantchemist @riceeyfn]

$TXN $STM looking forward to earnings 🚀

[Quantchemist @riceeyfn]

So happy increased my $PENG position to my biggest holding after their earnings report still trading at $67 🐧 🚀

[Sean trades @SRxTrades]

$PENG

Starting to breakout of a massive daily base on tons of volume

Blowout earnings and full year guidance raise

Partnership with $NVDA

Integrated memory and infrastructure demand is only speeding up

Targeting: $100+

[Quantchemist @riceeyfn]

I guess penguins can fly 🐧 $PENG
$100 next

[Quantchemist @riceeyfn]

How is $PENG not $100 after this ER?
$PENG $MXL $ALAB directly optimize memory. not $MRVL when jensen says 1T he means ASICs .

The MAGs will do anything to reduce the AI memory tax I mean look at $AAPL

Imo the next biggest bottleneck will be who solves this $PENG $MXL $ALAB are in truly asymmetric positions

$MRVL is a great long but doesn’t carry the torque as these.

[Quantchemist @riceeyfn]

@TW_trades_ $QCOM $200 calls at $130-140 pre earnings, $poet $11 calls at around $6-7. both over 10x

[Jukan @ ICML @jukan05]

DJT: THE U.S. WILL ACCOUNT FOR 50% OF THE GLOBAL SEMICONDUCTOR MARKET BEFORE I LEAVE OFFICE.

$INTC

[Quantchemist @riceeyfn]

Got invited to early access wealthsimple predict beta as a tester. excited to see what can come.

[Quantchemist @riceeyfn]

@ParadisLabs it actually is now idk what happened

[Quantchemist @riceeyfn]

if $160 breaks on $AAOI then the $AMD deal comes out its going to rip faces. Insane gains from here.
$400 comes $AAOI $AAOX

[Quantchemist @riceeyfn]

Buy Samsung

[Jukan @ ICML @jukan05]

Yes, MU is not Nvidia.

But going forward, it may become even more important than Nvidia.

Think about it. Inference is now directly tied to money. But inference does not get better simply by adding more Nvidia GPUs. In fact, GPUs are often underutilized in inference, sitting idle due to memory bottlenecks.

For inference, adding more memory is far more valuable.

Ultimately, the ROI of inference depends less on GPUs and more on memory. So why are people still looking at Micron through Nvidia’s framework?

Think bigger.

Inference is memory.

[Feroce Research @FeroceResearch]

Apple realized they’ve been price hiking consumers for years even when it wasn’t necessary, and now they can’t hike it further without genuinely losing consumers

The angle in which they are supposedly leaning towards CXMT is only going to strengthen the case for the big 3 memory names, especially Micron $MU as it remains the only true domestic manufacturer

The ability for CXMT to meet demand is just physically not there

Even if in the rare case Apple does get the green light on this, it’s only going to end up back firing on their own quality control moving forward

This is a lose-lose on Apple’s end here, not the other way around for Memory

One of the only true solutions for the memory shortage and prices are CXL Switches. But even those are a direct byproduct of memory. The more memory being shipped out, the more need for pooling. Memory is a genuine monopoly and that’s just something we have to come to terms with the past year and upcoming year

[Kalshi @Kalshi]

JUST IN: Elon Musk says deflation is "inevitable"

[M @nyse_min]

$MU CEO, 실질적으로:

"10년 이상 동안 $AAPL은 우리 칩을 $5에 사서 금속 상자 안에 붙여넣고, 소비자에게 $99 업그레이드 가격으로 팔면서 우리가 $7을 받으려는 시도를 비웃었어요.
이제 우리는 그들에게 $50을 청구하고 있는데, 그들은 돌아서서 고객들에게 $250 가격 인상을 했네요."

[Jukan @ ICML @jukan05]

>> Lenovo: Rising memory prices are the “new normal”; elevated DRAM and NAND pricing to persist beyond 2030

• The era of cheap digital devices is coming to an end. Lenovo warned that DRAM and NAND flash prices have already entered a structural upcycle, and that even if major suppliers continue to expand capacity, prices are unlikely to return to early-2025 levels.

Higher costs are being passed through across the entire industry. Going forward, all types of electronic devices, including PCs and smartphones, are expected to face sustained price-increase pressure, with higher prices becoming the “new normal” beyond 2030.

[Quantchemist @riceeyfn]

rip of ages $MU $INTC $DRAM $CRDO $SMTC $NBIS

[Paradis Labs @ParadisLabs]

Pretty funny seeing Michael Burry charge $450 in annual sub fees for shitco stock picks like $LULU and $ADBE.

When $SNDK is up 87% in less than two months.

Which is 15% more than the 5-year returns of the S&P 500.

And if you're wondering: it's still not late to join the memory trade on names like $SNDK, $MU, SK hynix, and Kioxia.