TZE-EN “FREDDY” CHEN

90% leveraged Beta + 10% equity L/S investor. TMT sector equity research analyst.

[Uber Engineering @UberEng]

https://t.co/4E91KTbzDU

[Wes Gray 🇺🇸 @alphaarchitect]

New Post: Why Momentum Investing Has Been Struggling—And What Volatility Has to Do With It https://t.co/lvdzPbqITD

[Roan @RohOnChain]

Jane Street pays $650,000 a year for quants. MIT wrote the exact bible to get there & released it for free.

51 pages. Zero to quant. Probability, stats, market making, real interview questions from Jane Street, Citadel, Two Sigma & more. Bookmark, before someone takes it down.

[Patrick OShaughnessy @patrick_oshag]

Every conversation I have with @dylan522p, I'm really just trying to understand the supply and demand of tokens.

This is a unique episode in that it's entirely dedicated to talking about both sides of that equation.

We discuss:
- The infinite demand for the newest models
- @SemiAnalysis_ going from $10K on AI spend to $7M
- Mythos and Anthropic's compute problem
- Why TSMC spending $100B on CapEx could cause a shortage
- Robotics as next demand wave
- Why memory prices will double again

This is my second conversation with Dylan and find myself needing to speak with him more and more often to make sense of it all.

Enjoy!

Timestamps:
0:00 Intro
1:00 Surging AI Spend
10:27 Token Demand
16:21 When Ideas Are Cheap and Execution is Easy
20:46 Model Hoarding
22:34 Robotics
27:03 The Compute Bottleneck
30:26 The AI Permanent Underclass
31:39 Supply Chain Reality
37:47 CPUs
42:54 Predictions: Public Backlash

[Ethan Kho @ethanrkho]

Hedge funds have always hired for modeling skills. That might be about to change:

Brett Caughran (@FundamentEdge) explains:

"Hedge funds have classically hired former investment bankers, PE investors, and sell-side analysts — because cranking a model from scratch was table stakes."

"I think that could shift. The new value of a junior analyst could be outthinking the market — creativity, imagination in tools, tenacity in going after key drivers, fluency in using these tools."

"The quantitative bar to be an investor at a large asset manager has gone down."

"The question becomes: can you understand consensus, understand why consensus is wrong, and build conviction around that?"

"Hedge funds will hire 10 investors and they can all build the models — but maybe three or four can build that variant perception engine, that expectations gap muscle."

"That learning curve used to take 3, 4, 5 years. Now it may be one, two, or three."

[Brett Caughran @FundamentEdge]

The senior analyst at a Tiger Cub who trained me on financial modeling back in '08 (shoutout Chris Laporte) walked me through the importance of deeply detailed cash flow builds. So much of the world is focused on EPS (certainly the sell-side), that you can generate a lot of insights on business performance by focusing closely on the cash flow statement.

Everyone agrees that Free Cash Flow is the purest driver of net present value, but modeling FCF is a very messy exercise whereas EPS has the benefit of accounting treatment that will smooth out the FCF lumpiness. Thus, much of the world defaults to EPS.

Great analysts spend a lot of time to see through the FCF messiness to uncover true cash flow generation capabilities. How much is operating cash flow impacted by working capital changes? How much of OCF is "fake" SBC add-backs that show up in dilution? How much of net income is actually recurring cash charges that are added back to Adj Net Income to flatter headline numbers? How much of FCF is actually distributable via dividend or buybacks?

To build all of these analyses into your financial model, there is no shortcut to having 10+ years of historical, quarterly cash flow statements. And this is a super annoying exercise to build, since companies report "cumulative" cash flows in Q2 and Q3, so it requires layering in the 9m cumulative cash flow, then subtracting Q1 and Q2, copying formulas as values. Ugg. I've never found a shortcut to doing this.

And while I completely agree that there are elements of financial modeling that help me learn the business, updating 5 years of cash flow statements isn't one of them.

I tried this exercise in 5 AI Excel co-pilots. Most failed on this exercise, but I was able to get Scout by Daloopa (not sponsored though do have free access) to do this reliably, with click through visibility.

While AI Excel still cannot one-shot a complicated model like my DHR model (not even close), AI Excel can do simple things like update my 5-year outdated BS & CF that save immense time and brain damage. I'll call that a big win.

(Will walk through this step by step on my AI Excel seminar April 30th).

[@jason @Jason]

Epic

[David Marcus @davidmarcus]

A few thoughts about PayPal, nearly 12 years after I left.

I woke up this morning to dozens of messages from former PayPal colleagues. It pushed me to finally speak up.

I never spoke publicly about the company after I left. Part of that was loyalty to John Donahoe, who gave me an unlikely opportunity, handing the reins of PayPal to a startup guy who, on paper, had no business running a then 15,000-person organization. But part of it was something else: I had left. I chose not to stay and fight for the changes I believed in. Speaking from the sidelines felt like armchair commentary. Easy opinions without the burden of execution. So I stayed quiet.

But twelve years of silence is long enough. And today's news makes it clear the pattern I've watched unfold isn't self-correcting.

I left PayPal in 2014 because I was deeply frustrated. We had executed a silent turnaround of a company that had lost its soul. We brought back engineering talent, shipped good products quickly, and acquired Braintree and Venmo. The company was on a tear. So much so that Carl Icahn felt compelled to accumulate a position in eBay and push for a PayPal spinoff. At the time, eBay decided to fight Icahn.

It was a difficult period for me, caught between what I felt was right for PayPal and my loyalty to the eBay team.

This is when Mark Zuckerberg approached me to join Facebook. The combination of his conviction that messaging would become foundational, the appeal of going back to building products at scale, and my growing exhaustion with the internal politics at PayPal and eBay eventually convinced me to leave and join one of the best teams in the world, one I had admired for a long time.

In the summer of 2014, I met John in a café in Portola Valley and told him I had decided to leave. During that conversation, he told me that Icahn had effectively won the fight, that PayPal was going to become an independent company, and he tried to convince me to stay on as CEO, but I had already said yes to Mark, and my word is my bond. There was no turning back.

After my departure, the board scrambled to find a replacement, and it took a few months for them to land on Dan Schulman. The leadership style shifted from product-led to financially-led. Over time, product conviction gave way to financial optimization.

Much of the momentum we had created still persisted and carried the company forward, mainly driven by Bill Ready, who came over in the Braintree acquisition and rose to COO. Under his leadership, Venmo grew exponentially, and total payment volume (TPV) accelerated quickly. But the shift under Schulman became more pronounced after Bill's departure at the end of 2019. With him went the product conviction that had defined the post-spinoff momentum. Then, for a period, COVID-fueled online shopping hid a lot of the company's new weaknesses.

During that period, the company made a fundamental miscalculation: it optimized for payment volume instead of margin and differentiation. It leaned into unbranded checkout, where PayPal had the least leverage, instead of branded checkout, where the margin, data, and customer relationship actually lived.

Visa masterfully structured a deal that effectively ended PayPal's ability to steer customers toward bank-funded transactions, which had been a core driver of PayPal's economics. Not long after, PayPal lost a significant portion of eBay's volume. Over time, it saw its share of checkout among its most profitable customers steadily erode as Apple Pay and others continued to execute well.

The same pattern repeated itself across lending, buy-now-pay-later (BNPL), and new rails.

On lending, PayPal missed the opportunity to turn it into a platform weapon. Products like Working Capital were conservative, short-duration, and optimized for loss minimization. Lending never became programmable, never became identity-driven, and never became a reason for merchants or consumers to choose PayPal over something else.

The missed opportunity in BNPL was even more striking. Klarna, Affirm, and Afterpay didn't just offer installment payments, they built consumer finance brands, persistent credit identities, and new shopping behaviors. PayPal saw the BNPL turn, entered the market, and had every advantage: distribution, trust, and merchant relationships. But BNPL was treated as a defensive checkout feature rather than an offensive category. There was no attempt to turn it into a core consumer relationship, no super-app behavior, and no meaningful differentiation for merchants. Others built platforms, PayPal added a feature.

The failure to lean into building and owning new rails followed the same logic. After the spinoff, PayPal had a once-in-a-generation opportunity to build a global, at scale payment network. Instead, the company focused on building on top of existing networks and third-party rails.

More recently, that mindset carried over to PYUSD. Technically, the product was sound. Strategically, it launched without a compelling transactional reason to exist. PYUSD had distribution, but no organic demand. It was not embedded deeply enough into flows to become a true settlement layer, a cross-border merchant rail, or a programmable money primitive. It sat adjacent to the product instead of inside the core of it.

Acquisitions during this period followed a similar pattern. Honey was not a strategic acquisition for PayPal. It added activity, but not leverage. It lived outside the transaction, monetized affiliate economics rather than payment economics, and never meaningfully strengthened PayPal's control of the customer or the checkout moment. Xoom solved a real problem in remittances, but it never compounded PayPal's advantage. It scaled volume without changing the underlying rails, identity graph, or settlement model, and as importantly, it didn’t cater to a high-value, high-margin customer archetype.

None of these were bad companies. They were just a wrong fit for PayPal and became unnecessary distractions.

The board eventually recognized the problem. In 2023, they brought in Alex Chriss, an Intuit veteran with a strong product background, explicitly to restore product conviction. It was the right instinct.

But Alex came from software, not payments. He understood SMB product development. He didn't have the muscle memory for transaction economics, network effects, or settlement infrastructure.

In hindsight, he also made an error: clearing out much of the leadership team that understood payments deeply. Executives with years of institutional knowledge departed within his first year.

This morning, Alex was removed as CEO. Branded checkout grew 1% last quarter. The board tapped another operator, Enrique Lores, the former HP CEO who's been on the PayPal board for five years.

I don’t know Enrique. And he might be a great leader, but on paper at least, he’s a hardware executive. For a payments company.

The common thread through all of this is incentive design. Once PayPal became independent, short/medium-term predictability beat long-term vision and ambition. Stock performance mattered more than platform risk and network opportunity. Financial optimization replaced product conviction.

I'm not claiming I would have made every call differently. Running a public company at scale involves tradeoffs I didn't have to make after I left. But the pattern, choosing predictability over platform risk, again and again, was a choice, not an inevitability.

Over time, the company that had every advantage and could’ve become the most consequential and relevant payments company of our time, lost its mojo, its product edge, and its ability to compete in a market that’s being rewired and reinvented in front of our eyes.

That's the part that's hardest to watch for a company I care so deeply about.

[Antenna @AntennaData]

Antenna observed 656k signups to Netflix in the 3-day window (Dec 24-26) for NFL Christmas Gameday. While not as big as the Paul/Tyson fight, it's a notable spike. Netflix has consistently been w/in 50-70k signups per day for the entire 1.5 years since the password crackdown.

[Evan @StockMKTNewz]

The semiconductor value chain

[Dan Rasmussen @verdadcap]

The Tokyo Stock Exchange issued a directive asking all companies with price-to-book ratios below 1x to issue a plan to get to 1x book. We did a systematic review of every plan issued by 3,247 firms to assess the impact of these reforms.

[BlueJay @BlueJay87476298]

程正樺
Investment opportunities in AI
Call Memo 20240722

1. 基本面仍樂觀，企業獲利在增加，大家的預估也在往上修，雖然近期股價走勢偏弱，但台積電4Q24營運上修機率比下修高，2024全年營收
YOY+25~30%是有可能的

2. 費半個股有些存貨高一點，都是 $AMD 和 $NVDA ，都是AI相關需求

[BlueJay @BlueJay87476298]

#好文分享

$TSM 的CoWoS先進封裝制程是一個總稱，CoWoS （chip-on-wafer-on-substrate）技術又分三種類型，分別是CoWoS-S，CoWoS-R，和CoWoS-L；

[定錨產業筆記 @investanchors]

這篇故事寫得真精彩！站長2014~2016年在投信公司負責電子下游產業，也曾多次拜訪超眾，向吳惠然董事長請益散熱產業的問題。

每次吳董聊起散熱產業的趨勢，總是能滔滔不絕，並提出非常精闢的觀點，令人佩服！

如果沒記錯的話，在2015年底Intel推出Sky Lake伺服器平台時，因功耗提升，部份客戶開始採用均熱板(VC)，超眾是國內第一個通過認證並出貨的廠商。

然而，在吳董過世後，後續在手機薄型VC、伺服器3D VC、伺服器液冷cold plate……等散熱新趨勢，雙鴻經歷多年耕耘累積技術實力，慢慢後來居上了。

[Shiuan.L @freeshiuan]

今年接連讀完Tim Ferris’s 《一週工作 4 小時後》與Morgan Housel《致富心態》，以下分享這兩本書對我的影響，以及為何促使我體驗郵輪旅行：

▌1. 計畫迷你退休 （Mini Retirement)：

Time Ferriss 認為我們應該把 60 歲以後的退休計劃，平均分散在 30 歲到 60 歲之間，這跟 《別把你的錢留到死》書中提到的「各年齡人生清單」不謀而合

理想上，最好每年都可以有一個月的 Mini retirement ，讓我們打破生活慣性，體驗新的機會

這讓我想到我爸，他是一位教授，而他工作最迷人之處就是每 6 年可以 1 年Sabbatical Year，是我所知最能執行 Mini Retirement 的工作。

▌2. 理解人性貪得無厭 (Never enough)

Morgan Housel 書中這一章提到兩個富翁，他們都已經無比富有，卻仍然冒更大的風險、想賺更多錢，最終落入萬丈深淵

這讓我意識到：我們要注意自己的目標，是否因為得到了更多的金錢、權力或名聲就不斷地往上移動？

.

回到 2個月前，當時的女友（現在的太太）問了一個很天真的問題：「要不要去郵輪環遊世界？」

我當下開啟 Autopilot 回復，好啊，要是這輪牛市賺了 N 倍，我就辭職帶妳環遊世界。
原本只是應付了事，哄哄女友，但想起《致富心態》這一章的案例：人性只會驅使你賺更多的錢，尤其當你賺得愈來愈多、愈來愈快的時候

在人生30 - 50歲這段期間，薪資是以一個可以預見的速度線性增長，20 年穩定投資複利也很可觀

我很可能會一路賺錢直到不能賺錢的那天，賺超過我餘生需要的錢

這何嘗不是一種貪得無厭？

.

綜合上述兩本書的Key takeaways ，我給自己這 3 年設了一個 Mini Retirement Goal 目標數字$x,xxx,xxx。

7位數，不是一個很誇張的數字，但 “enough” 支持我迷你退休一段時間。

設好這個Mini Retirement Goal，讓自己心中有一個警鐘：

▌當我達成目標的那天，回來看這篇文章「我已經賺到當初設的目標了，賺這些錢的目的是什麼？我去達成了嗎？」

.

最後-「為什麼 Mini Retirement 考慮郵輪旅行呢？」

1. 今年2月臺大同學會，我們事前問卷調查大家「財富自由後要做的事」

80%的人都答「環遊世界」，於是我也就默默在心裡複製貼上了。

但我希望在年輕還能工作的時候，就小規模實驗一次這樣的旅行，看看「環遊世界」這個夢想值不值得我工作到退休？

2. 郵輪應該是目前最 affordable 的環遊世界機會

我查了下和平號，100 天只要 66 萬台幣，蠻適合作為Mini retirement 的長度與預算

3. 郵輪給我 Work from anywhere 的可能

感謝馬斯克，現在郵輪大多配備 Starlink ，讓我不至於長時間與社會脫節，也能同時做我最喜歡的工作-寫作分享。

.

而這次三天兩夜的奮進號郵輪旅行的初衷，便是驗證下述假說：

1. 我是否能長時間活在郵輪上？

2. 郵輪上是否能工作？

3. 郵輪旅遊是否比飛機旅遊更讓我喜歡？

這次體驗下來，上述三點都蠻樂觀的

明年初預計會再來一段中程郵輪旅行，二度確認自己的感受。

接著，就是在市場耐心等待了。

[Wes Gray 🇺🇸 @alphaarchitect]

The ultimate "Out of sample factors" paper via our friends from @Robeco @paradoxinvestor is an excellent confidence builder (maybe even a "confirmation bias" builder🤣) .

The bottom line:
--focus on value
--focus on momentum
--focus on low-risk/quality
--size doesn't really matter (as @jvogs02, AQR, and Robeco have shown!)

[TZE-EN “FREDDY” CHEN @freddy_chen]

上面三個理由，加上評價和獲利近期都有顯著下修， 整個是一盤超低預期的 setup，下檔風險被消除不少。

[TZE-EN “FREDDY” CHEN @freddy_chen]

很高興過去 3 個月對 $AAPL 的判斷收到良好回報，其實更感謝的是半年前有陣子密集跟香港新加坡的 hedge fund managers 聊天的時候，談到 $AAPL = undervalued AI play 的想法

[TZE-EN “FREDDY” CHEN @freddy_chen]

也因為 Apple Intelligence，App 生態系的美好時光（對 $AAPL 來說）應該有很高的機會維持下去，尤其現在美國不論 YC, a16z 都在加緊投消費性 AI 應用的時刻，Apple Intelligence 的出現無疑是讓 iOS 這個平台繼續成為開發者的花園。