Farewell to my Value Edge moniker. I have decided to rebrand, something I’ve thought of doing for a while. I’ll still write under “the value edge” on seeking alpha, but will explain the purpose and future direction of my account here on X.
It’s long been my dream, presumably like many of you, to run my own investment operation as my full time job. While I don’t yet have the capital required to do that, I want to start taking definitive steps to make that dream a reality. Step 1 is a rebrand to the name I ultimately will use, which is Entropy Capital.
Why Entropy? Entropy is the phenomenon that all matter tends towards randomness. It’s a constant reminder that markets are far too complex for us to predict with 100% accuracy. There is always some seemingly random variable that can blow a hole in your thesis. You must always remain vigilant, and your stocks must always earn the right to be owned by it.
The concept of entropy ties quite nicely with my fascination of nonlinear dynamics. The concept that small changes in the starting state of function can yield drastically different outputs. Beating the market is a pursuit for nonlinearity. Every day upon market open out portfolio has a starting state for that day. You control what that state is. Over time, finding the optimal state for your portfolio (what stocks you own) is the only variable that matters.
My content moving forward will remain primarily focused on my portfolio as it always has. Eventually I’ll monetize my X and Substack, but I have no plans to do that in the foreseeable future.
With that, I’m excited to continue along on this journey with you! Let’s get richer together.
Documenting the headwinds I now see for AI.
It won't seem like it, but I love AI and am long-term positive. But when "math doesn't math" I take note.
1. The core thesis for foundation model lab investment has been high upfront investment made worthwhile by significant long-term profits.
2. These are capital intensive businesses and the compute commitments are very high relative to revenue and require strong growth over long time periods. The "leverage" (commitments versus revenue) is extremely high.
3. The fundamentals are not as positive as they previously were:
• Input costs are higher (commodities, chips, power)
• Interest rates are higher
• Competition is more intense
• Scaling Laws are now problematic: exponential costs/power cannot continue
4. Forecasting compute spend is challenging and high risk due to (a) revenue uncertainty and (b) algorithm uncertainty
5. Revenue growth appears to be slowing. The technology is valuable, but ROI is proving to be more expensive and take longer than anticipated.
6. The future is likely "different models for different use cases" with the lower end of the market being highly competitive.
7. Core use cases such as agentic software engineering are likely to need approaches beyond next-token prediction. They are Σ₂ᴾ complexity problems requiring multi-objective optimization and likely a combination of Transformers and other methods.
8. Current forecasts in memory makers are built largely on quadratic attention. That will not persist: we are already seeing work from DeepSeek, Minimax and Nvidia that can cut RAM needs by 80% or more.
9. This means semiconductor valuations are substantially overinflated and will go through the traditional glut versus shortage cycle.
10. For foundation model providers: lower costs with competitive differentiation is good. However, lower costs with a lack of differentiation would mean lower revenues. This makes it harder to (a) service commitments and (b) pay back investors.
11. Leverage is substantially higher than in previous cycles, evidenced by leveraged ETFs, call option activity and margin loans. Korea is particularly susceptible.
12. 0DTE options create a profile that has stronger parallels to portfolio insurance and 1987 than any other point I can remember.
13. The combination of exponential increases in call activity coupled with the ties of semiconductors to structured products means there is a non-trivial systemic risk to the financial system.
14. Implied earnings growth rates are inconsistent with other periods in history.
15. Macroeconomically we cannot and should not fund exponential cost increases. History has shown us repeatedly that there are better ways (see Quick Sort and Simplex).
16. Significant supply is hitting the market via IPOs.
––
Taken together: costs and competition are increasing while revenue growth is likely slowing. Valuations are fragile and prone to technology disruptions that are already here. Systemic financial market risk is extremely high.
Alphabet is raising 80B to buy compute “to meet unprecedented customer demand”
Berkshire put in 10B of it
Read that again
The most patient capital on earth just underwrote a GPU bet
Jensen says compute equals revenue
Buffett just priced the collateral
$GOOGL $BRK.A $NVDA
The longer the war drags the more amplified the ripple effects will become
Oil production doesn’t turn back on overnight and the US is now stuck in a strategic rock and hard place. I am becoming moderately more bearish and that feeling is increasing at a rapid rate as this drags
Silicon Photonics - some basics…
Notes -
- “Wafer-level optical probing test for known good SiPh PIC die” — this is where $AEHR comes in w/ wafer level prober
(SiPh = silicon photonics, PIC = photonics integrated circuit)
- MCM stands for “multi-chip module”, SiPh leans us deeper into chiplets
- will likely require curvilinear masks in manufacturing. Toshiba $tosbf recently acquired NuFlare, a leader in curvilinear masks
- advantest, $ateyy, supplies metrology equipment that would be important for these masks as well
- manufacturing silicon photonics at scale remains a challenge because it’s extremely complex
- thermal management is important because temperature changes can impact optical signal quality, chip cooling becomes more important, perhaps benefits $VRT?
- Some research estimates the cost of packaging, assembly, and test for photonics devices is as much as 80% of the total module cost. This is in stark contrast to traditional silicon chips today where packaging is a minor cost relative to the overall chip
- “Apart from data centers, silicon photonics is trailblazing developments in other areas, such as lidar in automobiles, which along with cameras and radar is considered essential for object detection. It also is revolutionizing optical projection technology for advanced imaging systems, augmented reality (AR) displays…
But despite significant advancements and potential market opportunities, existing manufacturing processes are limiting the scalability and mass production of silicon photonics components. Manufacturing is often manual and labor-intensive due to the intricacy and precision required in fabricating optical components.”
On paper, selling something at $200 after buying it at $7 looks like a brilliant masterpiece. It feels like you nailed it, the screenshots look legendary and the percentage gain sounds absurd. But almost nobody does or often times even considers the real math. I see this mistake made over and over again.
If you bought at $7 and sold at $200, your gain is $193. After 30% long term capital gains taxes, that’s about $58 gone immediately. Now you don’t have $200 per share to redeploy, you have about $142.
If the stock drops to $131 and you buy it back, you’re not capturing a 35% decline. You’re turning $142 into $131. That gives you roughly 8% more shares than before.
After all these brilliant looking trades on paper and trying to time the markets you’re getting ONLY 8% MORE!
That’s the real edge after a “perfect” sell and a 35% pullback. This is what most investors miss. They calculate price returns, not capital returns. Once you sell, Uncle Sam immediately becomes your largest partner and gets his cut. To overcome him, you need a very big reset, not just a 30% dip because such a pullback doesn’t justify the big tax bill you paid.
The uncomfortable truth is that trading around great winners is much harder than it looks. Every time you sell, you shrink the base that compounds for you. Unless the valuation was insane or the fundamentals broke, you’re often just interrupting your own long term math.
My point is not to ridicule this person. I do not know him, and for all I know he lives in a low tax jurisdiction where the math is different. The point is simply that most people do not know how to calculate their real returns, and the gap between paper profits and actual wealth creation is often much larger than you think.
🌹
US has now invaded Venezuela.
Everyone is probably wondering the same thing:
How do you profit off the situation?
1. Heavy Sour, Ammonia, and Nitrogen Fertilizers disruption ( $CF , $CVE).
These are Venezuela's biggest exports.
Most people will buy generic oil ETFs or light sweet crude producers. This is inefficient because light oil is not a perfect substitute for heavy oil in complex refineries. If Caribbean ammonia is stranded, the global price of nitrogen spikes. The biggest beneficiary is a US-domestic producer that uses cheap US natural gas and doesn't rely on Caribbean shipping lanes
2. Dirty Crude Processing ( $VLO ) - If competitors are starved of Venezuelan oil, Valero’s ability to source heavy crude from diverse locations (and its leverage to diesel margins) makes it resilient.
3. Naval Warfare ( $LDOS) - While retail investors buy Lockheed Martin (F-35s), the operations in the Caribbean focuses on maritime surveillance, warfare, and autonomous patrolling to enforce blockades without risking US personnel. Companies like Leidos provide these tpyes of naval tech.
4. Defense and aerospace from $AVAV to $HII and $LHX also benefit.
- $AVAV recently unveiled the Red Dragon and updated Switchblade 600 variants specifically for maritime operations
- $LHX provides the sensors and communications gear that link the drones ($AVAV) to the ships ($HII) and the jets ($BA).
- A blockade requires significant maritime surveillance and naval assets, which benefits shipbuilders ( $HII )
5. Direct Suppliers of recent military operation:
- F/A-18E/F Super Hornet from $BA (Precision strikes on Caracas)
- B-1B Lancer from $BA
- UAS (Drone), MQ-9 Reaper - $RTX (MTS-B Sensors), $HON Honeywell for the Engine
- Tomahawk (TLAM), $RTX
So far:
$AVAV - 5.91%+
$BA - 4.91%
$LHX - 3.72%
$CF - 3.61%+
$CVE - 3.61%+
$HII - +2.85%
$RTX - 2.1%
$VLO - 1.55%+
$LDOS - 1.7%+
$HON - .4%+
@alanbwt Hey the issue is that if quantum breaks Bitcoin then the network is functionally pointless but if it breaks digital dollars then we can just go back to paper money hope this helps
This is so beyond retarded that I almost think he’s joking but he is indeed serious
MSTR has far higher likelihood to implode & cause the next major Bitcoin bear market than it has of returning 20x in 10 years
Bitcoin itself will yield far better returns than MSTR commons
MSTR Stock Price Modeling: 10 Years Out
MSTR seems like an amazing entry here and the amplification outweighs the premium you're paying.
Current BTC price: $87,829
BTC CAGR: 30%
Time horizon: 10 years
MSTR amplification: 27%
Current MSTR price: $165.27
1. Bitcoin price in 10 years
30% CAGR over 10 years:
Growth multiple: 1.30¹⁰ ≈ 13.79
Future BTC price: $87,829 × 13.79 ≈ $1.21 million
2. Amplified Bitcoin exposure (MSTR)
27% amplification means MSTR compounds at:
BTC return × 1.27
So effective growth multiple:
13.79 × 1.27 ≈ 17.5×
3. Implied MSTR stock price
Apply the amplified multiple to today’s price:
$165.27 × 17.5 ≈ $2,890 per share of MSTR
✅ Final Answer
Bitcoin (10Y): ~$1.21M
MSTR multiple: ~17.5×
Implied MSTR price: ~$2,900 per share
This assumes:
No multiple expansion
No contraction, stays at 1.1x
They maintain 27% amplification
Pure Bitcoin CAGR + structural amplification only
But.... remember MSTR has a BTC Yield this year of 24.9% this year.
What if we model in a conservative 10% BTC Yield per year AND an mNAV rerating to 1.5x?
Bitcoin per share exposure increases 10% per year, compounding:
BTC/share multiple: 1.1010≈2.59×1.10^{10} ≈ 2.59×1.1010 ≈ 2.59×
This is independent of BTC price appreciation. It stacks on top.
mNAV re-rating from 1.11 → 1.50...
Total MSTR multiple:
Now multiply all three effects:
13.79×2.59×1.35≈48.2×13.79 \times 2.59 \times 1.35 ≈ 48.2×13.79×2.59×1.35 ...
≈ 48.2×
Apply that multiple to today’s price:
Implied MSTR price: ~$8,000 per share
BULLISH MSTR.
Remember OP said assuming 30% CAGR and consistent outperformance of MSTR over BTC means a 27x return in 10 years
And said MSTR has outperformed BTC over past 5 years therefore outperformance will continue
Meaning he’s simply applying past performance for future predictions (time tested way to blow your whole portfolio), and you want to say I’m using a flawed argument? Haha
Like I said you all can have fun in MSTR or any of the other shitty synthetic BTC vehicles Saylor created but I can almost guarantee both BTC and XYZ will outperform MSTR in next 10 yrs
He also doesn’t understand how math works apparently
And this guy has a following?
Inordinate amounts of wealth to be destroyed my this type of content
Literally just buy bitcoin and chill. Stop trying to amplify returns with synthetic structures. You will go broke
21 million total supply.
8 billion people.
That's 0.002625 BTC per person maximum.
Your financial advisor: 'Put 5% in Bitcoin'
Math: That's literally impossible for everyone lmao
Friendly reminder banking has existed basically since the birth of farming and widespread settlement
Through both hard and soft money regimes
Neither blockchain nor Bitcoin destroy banking, they just disrupt & revolutionize it
But banking IS NOT hoarding hard money & creating synthetic yield atop that horde
$MSTR is decidedly not a bitcoin bank & saylor branding it as such is folly & a misunderstanding of millennia of financial history
No, I cannot accurately predict the future. And neither can Adam.
But I can say with 100% certainty that the far more likely outcome is a MSTR implosion than a 30x return in 10 years
Again, the shareholder lawsuits themselves will be enough to bankrupt the company when it starts selling Bitcoin bc saylor has been shouting the never sell / hodl mantra from the rooftops
Entropy - a lack of order or predictability, or the tendency toward randomness - and a constant reminder that chaotic market conditions can always appear when we least expect them. A reminder to stay vigilant & build a durable, all weather portfolio
Thanks for having my back naum 😁
Adam
Study any banking crisis in the history of civilization and tell me again how leverage works
Strategy is functionally a synthetic finance product built atop the most volatile asset ever created. Volatility goes both ways. Synthetic products blow up when volatility hits unexpectedly. Volatility always hits unexpectedly.
When MSTR has to start selling BTC the shareholder lawsuits themselves will bankrupt the company and the vicious cycle that is set off will be violent & quick.
Have fun! I’ll stay happily in BTC and BTC alone — and when Saylor tanks the fuck out of bitcoin I’ll be the one buying it up.
yes. Banking and trading should be moved fully to the blockchain within 10 years
Banking itself is undergoing two foundational shifts - 1) AI disruption, 2) blockchain disruption
Note that bitcoin itself doesn’t disrupt banking but blockchain technology. Banks have existed in some capacity since the dawn of civilization when currency was first created. Through millennia of hard money and soft money regimes. Banking is currency agnostic - Bitcoiners that tell you otherwise are coping
SEC CHAIR Paul Atkins U.S. markets could move on-chain "within a couple years"
Bro just said the quiet part loud
$68T equity market
$35.8B currently tokenized
Nasdaq filing for blockchain trading
We're so fucking early it's insane
Mr financelot doesn’t know about step up in basis (actual tax avoidance strategy for heirs) just wants clicks
Also a $6.25b donation that benefits the donor is still a $6.25b donation. Not really a scam!
What a scam this is..
Michael Dell gets to write off 74% of his $6.25B "donation" right away because it's a fed gov program for public purposes
It shrinks his estate, avoiding 40% tax on his heirs while maintaining family control
The investment accounts are funneled into $DELL