胜利街绳匠

希望靠投资45岁退休回国钓鱼🎣爬山⛰️骑车🚲的东京社畜

[Serenity @aleabitoreddit]

Just some random thoughts, I do think AI is the most disruptive technology in human history.

To the level of agricultural or industrial revolution.

Since Anthropic, OpenAi, XAI, and others are racing to build superintelligence.

The amount of economic impact can't be measured if AI helps find cures for cancer or accelerates discovery for Quantum Computing.

Or if AI end up displacing the workforce, which increases profitability for companies.

The US Gov has every incentive to keep the buildout going too, as the implications from Warfare, Cybersecurity, is also immeasurable if China takes the lead.

So there's likely to be incentives and subsidies to win, even if there's not enough profit derived LLM training/inference.

As for sustainability, when you look upstream, $GOOGL is able to fund it majorly with their own cashflow, same with $AMZN, $MSFT.

More lukewarm on $META. Very iffy about $ORCL.

But I do see some bubbles forming around debt interest like $CRWV.

Maybe circular valuations that's happening with OpenAI backlog agreements or $NVDA / $AMD agreements with Neoclouds to buy their GPUs.

But as seen with $MSFT and having OpenAI be a major part of the backlog, it did correct off the information, so "bubbles" like that do pop despite the overall markets increasing.

Definitely don't see a bubble in upstream semiconductors from $LITE to Sk Hynix though since the amount of profit they get from the buildout would likely be insane to make up for capex decreasing.

OpenAI was actually my biggest fear from contagion, eg. $CRWV, $CBRS and others, but they just raised a lot.

So think it will be fine for another 1 1/2 years of capex, especially if they IPO this year.

I also don't think we'll get massive Fed tightening despite "predictions" since this will trigger a contagion since many of these players rely heavily on debt.

And although the Fed is independent, don't think Trump would have supported someone who is against his administration goals.

As for semiconductor valuations going up every day like $AMD or $MU, there's probably going to be some corrections here and there. Everything going up together is kinda unhealthy.

Can't time the capex peak but just from $AVGO and other projections, it just keeps accelerating exponentially into 2028.

Especially as everyone is starting to sign multi year agreements as well.

OpenAI contagion / hyperscaler capex decreasing / fed tightening was what I'm looking out for, and no blaring signs of any of those yet.

So I think the music will keep playing for this year at the bare minimum.

[胜利街绳匠 @GosickLin]

哈哈哈哈哈哈

[Vivian @Vivian193299]

“海内存知己，天涯若比邻”翻译:在恰当的时候，将海量的内存屯在身边，以此方法积累财富，则世界上任何一个国家都可以随便游玩。

[美研芒格君 @Kay2289123]

https://t.co/3TWZzaX5p4

[胜利街绳匠 @GosickLin]

@cherryPayment 熬夜看世界杯了

[胜利街绳匠 @GosickLin]

@IamRamenPanda 主要现在参与加密货币也有各种币股了，为何还要买币呢

[qinbafrank @qinbafrank]

成长股的核心本质是什么？就是用业绩的高速增长来消化估值。很多人看成长股，尤其是AI产业链的股票，第一反应就是“市盈率这么高，还敢买？” 正好借着早上这个回复把“EPS高速增长消化估值”的逻辑聊一聊。核心就一句话：公司赚钱速度够快，就能用时间把现在看起来贵的估值，拉到合理甚至便宜的水平。

1、先聊聊最容易混淆的点
市盈率 = 股价 ÷ 每股盈利（EPS）
市盈率高 = 你现在为每一块钱盈利付的钱多，看起来贵。
但成长股买的从来不是“现在已经赚到的钱”，而是未来几年能赚多少钱。
如果公司EPS（每股盈利）每年都在快速增长，那未来EPS的基数会越来越大。
同样的股价，除以越来越大的EPS，市盈率自然就下来了。这就是“消化”。
简单说就是增长把分母（盈利）做大了，高估值就被稀释掉了。

2. 举个最直白的数字例子
假设现在有一只股票：股价100块
今年EPS只有2块
市盈率50倍（很多人一看就说“太贵了”）
情况A：每年EPS增长30%（比较稳健的成长）第1年：EPS变成2.6块 → 市盈率降到约38倍
第2年：EPS变成3.4块 → 市盈率降到约29倍
第3年：EPS变成4.4块 → 市盈率降到约23倍
第5年：EPS变成7.4块 → 市盈率只剩约13.5倍

情况B：每年EPS增长50%（很多AI供应链公司努力的方向）第1年：市盈率约33倍
第2年：约22倍
第3年：约15倍
第5年：只剩6-7倍

你看，股价没怎么变，只是因为公司赚钱越来越猛，市盈率自己就掉下来了。这就叫用增长消化估值。增长越快，消化得越彻底。2-3年时间就能看到明显效果，5年基本就完全消化了。

3.、为什么有些高市盈率的股票还能买？
因为市场给的不是“当前盈利”的价格，而是对未来盈利增长的定价。在AI基础设施这个阶段，很多公司现在还在重投入、盈利还没完全释放出来，市盈率自然高。但只要后面有真实订单落地，EPS就会加速增长。这时候你买的不是“故事”，而是能看得见的业绩兑现节奏。

增长一旦兑现，高估值就逐步被消化，股价反而有空间。反过来，如果只靠讲远期故事，没有订单、没有验证、没有业绩增速，那高估值就消化不了，反而是风险。

所以大家会看前瞻市盈率、前瞻市销率，本质就是这个逻辑。核心是看未来一年，或者两年业务增长能把估值消化到什么地步。

4、怎么判断增长够不够“消化”估值？
最早是彼得.林奇提出来的简单的一个指标叫PEG（把增长考虑进去的市盈率）：
PEG = 市盈率 ÷ 预期年增长率（%）
PEG接近1 → 价格和增长基本匹配，比较合理
PEG明显小于1 → 增长很快，相对来说不算贵
PEG明显大于1 → 增长一般，价格偏贵

举例：一只股票市盈率50倍，但预期每年增长50% → PEG=1（可以接受）
同样市盈率50倍，但只增长20% → PEG=2.5（贵）
市盈率20倍，但只增长10% → PEG=2（也贵）
所以不能只看市盈率高低，要看增长能不能跟得上。

5、实际投资里怎么用这个逻辑？
投资节奏很重要。纯讲“未来AI会怎么牛”的故事股，容易被高估值反噬。
真正有订单、能看到2026-2027年EPS明显增长的公司，才是增长在真实消化估值。
核心判断三条：
增长是不是有真实驱动（订单、客户验证、产能爬坡）？
增长速度能不能覆盖当前估值？（看PEG、看未来2-3年EPS复合增速）
万一增长没达预期，安全边际在哪儿？

6、也说说风险
增长消化估值不是自动的，它的前提是增长真的发生了。如果公司出了很多问题：
订单没落地
竞争太激烈导致价格战
宏观或者行业周期反转
公司自己执行力出问题
那高估值不仅消化不了，还会因为失望而进一步杀估值，这时候最惨。

所以真正明知的做法是：买那些增长路径清晰、已经开始兑现、而不是还在画饼的公司。这样即使短期波动，也能用时间和真实增长把估值消化掉。

上面聊了这么多，其实最核心还是看增长，特别是增长的速度，高市盈率不可怕，可怕的是增长跟不上。
只要EPS能保持高速增长，用2-5年时间，就能把现在看起来贵的估值，消化成合理的、甚至低估的水平。这不是理论，是过去很多成长股走过的真实路径。

所以成长股投资关键永远是两件事：
增长的确定性和兑现的节奏。

对一只成长股我们需要清楚：它到底是在用增长消化估值，还是在用故事透支估值。

[胜利街绳匠 @GosickLin]

@BabybusFL 醍醐灌顶

[Babybus @BabybusFL]

半导体 光 存储 基建类 材料供应 存储需求要爆到28年机器人。光会贯穿全部 基建现在速度远远落后 需求排产有的企业预算都开到29年了。29-30年以前 基建为王半导体就是神 到了29-30基建泡沫破裂 全部暴跌 你就要看如此规模暴力基建支出 烧出来的ai是谁。当年移动烧到头 都给腾讯做了嫁衣 到了后面崩盘 等待腾讯出现 然后梭哈。几十倍上百倍涨幅会在未来。特朗普周期债市是超级大熊市 等他差不多嗝屁了 债市会是超级大牛市 股市就是超级大熊市。周期有大有小。

[胜利街绳匠 @GosickLin]

哈哈哈哈哈

[Serenity @aleabitoreddit]

If you want a TLDR of today:

> be $NVDA, $5T company. Force shift to 800V DC and CPO

> analyst: I don’t think u can do it in time!

> market: “I don’t trust Nvidia, time to sell everything”

> Nvidia and Lumentum executives after: Bullish on CPO, timelines accelerating.

???

[ReoNaStaff @ReoNaStaff]

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#ReoNa

[胜利街绳匠 @GosickLin]

是的

[徐冲浪 @cyrilxuq]

我认为大多数技术分析是很扯淡的，因为趋势是用来延续或者打破，都是对的，本质上确实是投骰子的概率，只是有人能长期以一种稳健的心态执行某种定式。

但是技术分析很难知道怎么止盈，那就很难有高回报率。

最后市场定价定的还是基本面，供需关系，企业利润，所以巴菲特才能驾驭那么多钱，钱越多是越难管理的，大公司的股票是很多力量一起抬着的，跟币圈个体户体验是完全不同的，如果基本面不存在了，那这些资管公司如何给一家企业定价，都跟币圈一样当盘子玩么。

高的盈亏比代表着：

1、要么用时间去换取更高的上限，容纳的本金上限大，但是整体资金利用率低

2、要么用杠杆，杠杆会带来更高风险，高杠杆必须追求高爆发性，所以给你提供杠杆的要收取高额的资金成本，你必须很短时间内完成操作

所以最后都是期权游戏，富人有时间有现金流，所以可以不加杠杆，穷人不行，穷人必须赌，所以这个游戏对穷人本就不公平，时间都站在穷人的对面

[胜利街绳匠 @GosickLin]

@gabriel030811 @_FORAB @grok 确实住在日本，还在学日语

[胜利街绳匠 @GosickLin]

说的很对，X上面高质量内容还是很多的

[Frenchie @Frenchie_]

Nos amis coréens sont les experts de la mémoire et ils écrivent vraiment des choses fascinantes

50% de mon Feed est actuellement asiatique, c’est la où il y a le plus d’alpha sur les semi actuellement

[Serenity @aleabitoreddit]

On top: $NVDA CEO also called out Silicon Photonics (optical networking) with memory.

Stating that Nvidia would require “supply volumes beyond imagination”.

What a bullish read through on the SiPH supply chain from $SIVE (now upstream Nvidia ecosystem) to $SOI

[Serenity @aleabitoreddit]

I think my personal style of investing is a bit different, just some reflection:

It's inherently discretionary, based on stuff markets don't know yet. And a culmination of life experiences?

If you look at $AXTI, $RPI, $SIVE, $IQE and others.

Lot of it is guessing on unstructured relationships then seeing if it's right or not down the line.

$RPI is the perfect example:

1. Nobody really thought of Raspberry Pis for AI growth. Mainly people bought one or two just for class + education + hobbyist.
2. After OpenClaw, just noticed all my friends and people just buying Apple Mac Minis / RPIs for AI applications.
3. Found validation of that trend online with lot of people sharing video tutorials on AI orchestration with RPI.
4. AI was their ideal perfect growth vector, did some modeling, and thought it was compelling.

Earnings comes out and I was right.

Everyone in media was calling it a meme stock because there's nothing online that shows revenue growth from AI (was 14% forecasted revenue growth, turned out to be 58%, my projection was around 55%).

So it was a mix of guessing next industry trend (AI using lightweight hardware instead of GPU clusters), real life trends, then revenue forecasting off my guess.

For stuff like $AXTI:

1. Everyone called it a joke when I bought at ~$12. LLMs would hallucinate and say "hyperscalers/govs would have known about this by now and fixed this vulnerability with InP substrates"
2. Or would conflate very nuanced parts of InP substrate stack, where there's multiple different chokepoints in upstream processing.
3. So part of this was just discretionary based on what I've seen over InP substrate breakdowns, industry trends, etc.
4. Then also guessing the major supercycle was photonics (this was before everyone caught onto $LITE, and others). Or before you saw the $141B TAM projections from GS.
5. AXT owned 40% of InP supply chain, without them the supply chain just gets cripped).
6. All the "analysts" were forecasting steady InP substrate growth, few hundred million TAM, etc. or export controls.
7. Everyone kept trying to say $AXTI was overvalued based on TAM estimates. But if it's a few hundred million TAM you just think that's a joke and go into game theory over allocations.
8. Then I just had to guess, how much would this be worth if it were a NAND style bottleneck, what MC could it reach based on control, how much would hyperscalers price it as, etc.

A lot of the current research outputs from Goldman Sachs, or earnings reports from the Epiwafer companies, were confirmed after I published my piece on AXT. If you did research back then, lot of the same material /framing wouldn't have come up.

With stuff like $XFAB as you're seeing now, a lot of it is just pure guessing:

1. Not really any CPO materials, how much their MTP process makes in revenue, etc. Everyone online keeps saying they're not a photonics player.
2. But if you go through ASE docs or Gov websites, they all kinda cite XFAB as a major emerging player here.
3. $NVDA also evaluating them right now (maybe it's successful who knows).
4. No clear revenue around this area because their main silicon photonics process is still precommercial, but if you guess it's trying to create a EU supply chain to compete with $TSEM, once pre-commercial shifts to commercial, maybe similar but less volume contracts?
5. Then just seeing updates over the next few months to see if anything confirms this thesis guess.

_

I think a lot of information discovery still can be done with LLMs I'm seeing online. But it's also really hard to make a bunch of unstructured inferences based on unrelated material or even just trends you're seeing in real life.

So probably better to just do what's standard, eg. do valuation forecasting based on current numbers

Stuff like $AAOI, if they're projecting $471m/M h1 2027 and you see MC at $12B, probably undervalued might be a good idea to go long for next years.

Stuff like Samsung Electronics is easier, see what people are modeling for operating profits for 2027, 2028 then just seeing if it's undervalued or not at current levels.

Maybe something harder is $JBL. I haven't really seen any great volume numbers around 1.6T LRO, but you can just make a guess on how popular that might be then project how that might impact current MCs.

Or picking just good names everyone kinda agrees like $TSM, $INTC, $MRVL is also solid.

So a lot of things is just building up your life skills then applying that to markets. I don't think it's that can be taught with courses and stuff.

Of course, much of what I'm doing is just high conviction inference based on unconnected parts. Could always be wrong.

[胜利街绳匠 @GosickLin]

@aleabitoreddit 学到了

[Serenity @aleabitoreddit]

Oh look… $NVDA CEO warned memory shortage is expected to persist for many years, due to massive scaling demand of AI infrastructure.

With further announcements tomorrow.

$MU and $EWY (Samsung/SK Hynix) operating profit projections aren’t looking too crazy anymore?

[Innomad 一挪迈 @innomad_io]

https://t.co/S4tkBGsp1i

[168X @168X_Fortune]

https://t.co/nkQXticExk

[胜利街绳匠 @GosickLin]

@cherryPayment 我会继续买 gogogo