Coincamps

Translation: Peggy
Editor's Note: On August 19, the U.S. Treasury Department announced an expansion of long-term bond repurchases, increasing the one-time maximum repurchase size for 10–20 year and 20–30 year treasuries from $20 billion to at least $40 billion. Previously, the 30-year bond yield had surged to around 5.34%, reaching its highest level since 2007. After the news was announced, the long-end yield quickly retreated.
This provided the market with a clear bullish signal: the Treasury Department is actively improving long bond liquidity, possibly even forming some kind of "Treasury backstop" expectation.
However, Marcus Nunes, in "The Treasury's $4 Billion Band-Aid," presented a contrarian view: while repurchases can indeed alleviate liquidity issues, if the long bond pressure stems from a larger fiscal deficit, higher bond supply, and weaker marginal demand, then a $40 billion repurchase does not address the true contradiction.
In other words, the market needs to distinguish between two things: the Treasury can make bonds trade better, but it cannot reduce the amount the U.S. government ultimately needs to finance through repurchases.
Below is the translation of the original article:
On August 19, U.S. Treasury Secretary Scott Bessent announced that the single-trade liquidity support repurchase size for 10–20 year and 20–30 year treasuries would be increased from a maximum of $20 billion to at least $40 billion. The market reacted swiftly. The 30-year Treasury yield, which had previously surged to around 5.34%, subsequently retreated significantly, with stocks, gold, and other assets rallying simultaneously.
However, the author of this article, Nunes, believes that this reaction easily leads the market to overlook a more fundamental issue: Treasury repurchases address liquidity, not the fiscal deficit.
Repurchases can improve trading but will not reduce government financing needs
Treasury repurchases are not quantitative easing.
When the Federal Reserve conducts QE, it can create base money to purchase treasuries by expanding its balance sheet; the Treasury does not have this ability. The funds used to repurchase old debt ultimately come from government cash or new debt financing.
Therefore, Treasury repurchases are fundamentally closer to debt structure management.
It can repurchase inactive old securities to increase market liquidity and, to some extent, boost demand for specific maturity bonds, but it does not change one fact: the U.S. government still needs to finance the fiscal deficit by issuing bonds.
The scale difference is particularly evident. The U.S. Treasury previously projected a need for net borrowing of $739.0 billion in the third quarter of 2026, while the size of this long-term bond repurchase has only been increased from $20.0 billion to at least $40.0 billion.
This is also why Nunes refers to it as a "Band-Aid." While $40.0 billion is enough to improve the market trading conditions for some long bonds, it is challenging to change the supply-demand dynamics of the entire U.S. bond market.
What is really weighing on long bonds is the growing fiscal supply
In Nunes's framework, the recent rise in the 30-year U.S. bond yield to above 5% cannot be simply understood as a liquidity issue. More importantly, the amount the U.S. government still needs to finance is significant.
In July 2026, the U.S. federal fiscal deficit reached $432.0 billion, a 48% year-on-year increase, hitting a record high for the month of July; the fiscal year-to-date deficit for the first ten months is around $1.8 trillion, already surpassing the full-year level of the 2025 fiscal year.
U.S. Federal Deficit—Annual Comparison
Meanwhile, the total U.S. federal debt exceeded $40.0 trillion on August 19. With the expanding debt scale and rising funding costs over the past few years, interest expenses are also increasing.
This means that the core issue the U.S. Treasury faces is not "old bonds are illiquid," but rather: who will absorb such a huge new bond supply in the future? If investors believe that future fiscal deficits will remain high, they will demand higher yields to absorb the long-term bond supply.
From this perspective, the 30-year yield breaking 5% may not be a sign of a temporary market malfunction but a repricing of U.S. fiscal and term risks.
The buying pressure issue is not something $40.0 billion can solve
Nunes also emphasizes the change in overseas demand.
According to the U.S. Treasury's TIC data, foreign holdings of U.S. Treasury securities decreased by approximately $72.1 billion month-on-month in June, with Japan, China, and the UK all experiencing varying declines. This is not enough evidence to prove that foreign investors are "massively fleeing U.S. bonds" because monthly holdings are influenced by exchange rates, custody locations, and asset allocation changes, and TIC data itself cannot fully identify the ultimate owners of securities, but it does indicate that the previously relatively stable overseas demand should not be taken for granted.
Foreign Holdings of U.S. Treasury Securities (June 2026)
Equally important is the buyer mix. If overseas official institutions become less willing to absorb U.S. debt, the U.S. will need to rely more on private investors. Private funds typically pay more attention to price and yield, meaning the market may require higher long-term rates to attract enough funds to absorb an increasingly large supply of bonds.
This is why simply increasing buybacks cannot solve the issue. While the Treasury can buy back some old debt, it cannot dictate at what price other investors will be willing to hold a significant amount of future U.S. long-term bonds.
The Real Divide: Is This a Liquidity Problem or a Fiscal Problem?
Proponents of expanding buybacks may argue that the Treasury is not attempting to address the fiscal deficit. Buybacks were originally a market liquidity tool, and as long as they can improve old bond trading and reduce market friction, they have achieved their policy objective. In this sense, criticizing buybacks by saying “$40 billion cannot solve the deficit” may itself blur the purpose of the policy tool.
However, the real issue raised by Nunes is: if the primary driver pushing up long-end yields has shifted from liquidity to fiscal supply, then continuing to use liquidity tools may inherently have limited effectiveness.
These two explanations correspond to two completely different market assessments. If recent long bond sell-offs are mainly due to insufficient market depth, deteriorating old bond liquidity, and short-term positioning impacts, then a Treasury buyback expansion may be sufficient to stabilize the market. But if the rise in long-term yields mainly reflects a persistent fiscal deficit, larger long-term bond supply, and higher term premiums, then buybacks can only smoothen the adjustment process, making it difficult to alter the ultimate yield level.
This is also the crux of this article: while the Treasury can improve the U.S. bond market's “trading problem,” it cannot buy its way out of the U.S.'s “fiscal problem.”
What truly needs to be observed next is not how much the Treasury's next buyback will increase, but whether long-term Treasury auctions will continue to receive sufficient demand, if the fiscal deficit will narrow, and if higher yields can once again attract foreign and private buying.
If these variables do not improve, then the yield retracement brought about by $40 billion is more likely to be a short-term cushion rather than a genuine reversal of pressure on U.S. long-term bonds.
[Original Article Link]

HYPE has surged from around $58.5 to $73.7 in the past two days, marking a 26% increase. It is now only about 4% away from its all-time high of $77.
As the price approaches a new high, Hyperliquid is also seeing positive developments.
pre-IPO Contract Enters SEC
The first piece of news comes from the Hyperliquid Policy Center. It has partnered with trade[XYZ] to submit a comment letter to the SEC in response to the regulatory body's public consultation on reforming the IPO process, proposing to include pre-listing perpetual contracts in the regulatory discussion.
The starting point of this comment letter is the traditional IPO pricing being trapped in a few underwriting institutions' bookbuilding inquiry and order allocation. According to HPC's materials, the number of listed companies on U.S. exchanges has decreased by about 40% since the mid-1990s. Companies stay in the private market longer, and retail investors often have to wait until the growth stage is nearing its end to have the opportunity to buy in. When companies are preparing for listing, underwriting banks privately collect orders, and the issuer and the public can only see the true market price after the stock opens for trading.
The final result often sees a significant disconnect between the offering price and the opening price. The issuer ends up with less money, and the institutions receiving allocations pocket the price difference.
The pre-IPO contract by Hyperliquid aims to introduce some early public trading. Traders can express both long and short views before the company goes public, and the order book continuously provides a public price. HPC and trade[XYZ] state that the contract's price near the listing is close to the stock's opening price and sometimes even more accurate than traditional media's pre-market indications.
The key move of this letter is to place Hyperliquid's pre-IPO contract within the IPO policy framework. HPC and trade[XYZ] hope that regulators will consider it as a public price discovery tool and establish rules around product categorization, derivative risk disclosure, listing eligibility, oracle and settlement transparency, deployer conflicts of interest, and staged opening to U.S. investors.
A contract product that originally only operated on the blockchain is now attempting to influence the stock issuance system.
Entropy & Traisa Join HIP-3
The second news story unfolds on the market supply side. Entropy has become a new HIP-3 deployer, planning to start in the Pre-IPO market before expanding into the stock market, with two contracts already live.
This eight-person team's background is almost entirely related to trading. Both co-founders dropped out of Stanford to start their entrepreneurial journey. The CEO was the first intern recruited by Polymarket, involved in designing the fee mechanism and liquidity incentive program, and later worked at Jump. Another co-founder previously worked on MEV on Solana before joining Ribbit Capital. Other team members come from Jane Street, Hudson River Trading, Jump, Radix, and Virtu.
These backgrounds align closely with the requirements of HIP-3. Deployers need to select assets, design contracts, maintain oracles, set leverage limits, and handle settlements. Entropy brings experience in prediction markets, on-chain trading, and traditional quant institutions, naturally raising market expectations.
The timing of Entropy's entry is also unique.
Early deployers of HIP-3 such as Felix, Dreamcash, Ventuals, have already exited. Early players tried to avoid trading [XYZ] by focusing on niche assets and first-mover advantage, only to find that listing new assets is far from sufficient. Without stable user distribution and liquidity, even the most unique trading pairs struggle to sustain.
Now, Paragon is rapidly rising. According to Loris Tools, Paragon has seen approximately $126 million in trading volume across 20 markets in the past 30 days, attracting over 3,400 traders. Also entering the scene almost at the same time as Entropy is Trasia, focusing on the Asian markets.
The competition for HIP-3 has entered its second phase.
Trump Mentions Hyperliquid Directly
The third piece of news comes from the White House. Trump mentioned at a cryptocurrency industry conference that the CFTC is working to bring Hyperliquid to the U.S. in a "fully compliant, lawful" manner.
For Hyperliquid, being directly mentioned by the President has shifted the discussion. Previously, it was challenging to fit a Perp DEX into the definition of traditional trading venues, and U.S. investors could not access related products. Now, the question has moved from "Will the U.S. handle Hyperliquid" to "How is the U.S. preparing to handle Hyperliquid."
This speech significantly alleviated the market's compliance concerns about Hyperliquid. The regulatory direction is shifting from excluding on-chain trading venues to seeking a legitimate entry for them.
A potential path is taking shape. Regulators are establishing a new market structure for on-chain trading venues to give them a legal identity distinct from the traditional designated contract market; U.S. brokers then distribute 24/7 perpetual contracts, spot, and prediction markets to more investors through HyperCore.
Druckenmiller Holds HYPE DAT
The fourth piece of news comes from institutional holdings. Stanley Druckenmiller's family office, Duquesne, revealed in its quarterly 13F filing an addition of approximately $23.2 million to its Hyperliquid Strategies / PURR position, a digital asset treasury company with HYPE as its core asset.
Druckenmiller wields significant weight in traditional financial markets. He founded Duquesne Capital in 1981, then went on to manage investments for Soros's Quantum Fund. Morgan Stanley's summary of his career record states that Duquesne achieved around a 30% annualized return from 1981 to 2010, with no losing years. Today, he manages his capital through Duquesne Family Office.
Druckenmiller's stature gives this transaction a more significant signaling effect. Hyperliquid has long been in the sights of traditional financial investors.
The market is reinterpreting Hyperliquid. The answer to decentralized finance is vying for the pricing power, distribution channels, and institutional position of the future financial market.

Translation: Peggy
Editor's Note: This week, the U.S. 30-year Treasury bond yield rose to around 5.34%, reaching a high not seen since 2007. Subsequently, U.S. Treasury Secretary Besent announced an expansion of long-term bond repurchases, increasing the maximum single repurchase size of 10–30 year bonds from $20 billion to at least $40 billion, with the arrangement to be implemented between September 9 and November 4. Following the announcement, long-term yields retreated, the dollar weakened, and risk assets received some support.
Superficially, this was not a significantly large bond liquidity operation. The more worthy discussion is: why has the U.S. long-term rate risen to a level that requires a more proactive Treasury response? And is the market beginning to reinterpret the Treasury's "policy reaction function" to long-term yields?
In "Beware the Bond," as explained by Trader Joe, the recent selloff in long bonds cannot simply be attributed to inflation. The fiscal deficit continues to create bond supply, demand from traditional long-term bond buyers like Japan has shifted, and AI capital expenditure is generating a significant supply of long-term bonds in the credit markets, with these various forces collectively increasing the scale of long-duration assets that the market needs to absorb.
The author further likens Besent's expansion of long bond repurchases to the Treasury's version of "Operation Twist." This analogy captures the direction of "reducing market long-duration supply," but the two are not equivalent: the 2011 Operation Twist involved the Fed selling short-term bonds and buying long-term bonds, explicitly aiming to lower long-term rates and ease financial conditions; the current Treasury repurchase plan's official position is still to enhance secondary market liquidity and cash management. Therefore, what is truly worth noting is not the $40 billion itself, but whether this tool will increasingly take on a role in managing long-end financial conditions in the future.
Below is the translated original text:
Earlier this week, the U.S. 30-year Treasury bond yield rose to its highest level since 2007, leading to a partial retracement in U.S. stocks and a weakening dollar.
Then, Besent made a move.
The U.S. Treasury announced that it would increase the single repurchase size of some 10–30 year long-term bonds from a maximum of $20 billion to at least $40 billion, to be carried out between September 9 and November 4. Following the announcement, the 30-year Treasury bond yield retreated from its previous high of around 5.34% to around 5.2%, the dollar weakened further, and the stock market also stabilized.
U.S. 30-Year Treasury Bond Yield
The question is: Is this just a temporary fix for bond market liquidity, or does it signal a shift in the U.S. policy stance towards long-term rates?
To understand this, we first need to answer another question: Why has the long-end yield risen to this level?
Why Has the Long-End Yield Risen to This Level? It's Not Just About Inflation
The most intuitive explanation is inflation.
If investors are concerned that future inflation will remain high for an extended period, they will naturally demand a higher long-term Treasury bond yield as compensation. However, the author believes that this alone is not enough to explain recent developments.
At least from consumer surveys, there is no clear sign of runaway long-term inflation expectations. The University of Michigan's preliminary survey in August showed that the one-year inflation expectation had risen slightly from 4.2% to 4.3%, but the five-year inflation expectation remained at 3.3%. In other words, short-term inflation concerns still exist, but the "deanchoring of long-term inflation expectations" is not the only, and arguably not the most important, explanation.
Data Source: University of Michigan Consumer Survey
The long-term Treasury bond yield reflects more than just future short-term policy rates and inflation. Economic growth, term premiums, regulatory environment, how much the Treasury needs to issue in bonds, and how much long-term Treasuries insurance companies, pension funds, and foreign investors are willing to hold all affect long-end pricing.
What is currently most notable, according to the author, is that the supply of long-term bonds is continuously increasing, but traditional demand has not expanded synchronously.
The U.S. fiscal deficit means the Treasury still needs continuous funding, and whether this funding is done through short-term Treasury bills, medium-term notes, or 30-year long bonds directly affects how much duration risk the market needs to absorb.
If the Treasury relies more on short-term T-bills for funding, it reduces the long-term bond supply that the market needs to absorb, putting relatively less pressure on long-end yields. Conversely, if more funding shifts towards 10-year, 20-year, and 30-year securities, the market must absorb more duration, potentially putting greater upward pressure on long-end yields.
This is also why the debt issuance structure itself has increasingly resembled a macro variable.
Why is the Treasury Acting Now? 5.3% Long End Beginning to Impact Financial Conditions
Short-Term Debt Can Alleviate Long-End Pressure, But Liquidity Cushion is Thinning
The issue is that even short-term debt cannot be issued infinitely.
In recent years, when the U.S. Treasury issued a large amount of T-bills, a significant source of funding was the money market funds' funds originally placed in the Federal Reserve's overnight reverse repurchase agreement (ON RRP) facility. When short-term debt yields become more attractive, these funds can flow from RRP to Treasury securities, absorbing new short-term debt without significantly draining bank reserves.
However, this cushion is now nearly depleted. Federal Reserve data shows that ON RRP usage is currently close to zero on most trading days. At the same time, as of mid-year, the U.S. banking system reserves were around $3.1 trillion.
In the second half of 2025, the massive rebuild of the U.S. Treasury General Account (TGA) further drained bank system liquidity. Federal Reserve data shows that following the resolution of the debt ceiling issue, the TGA balance increased by approximately $442.0 billion at one point, leading to a notable decline in reserves.
This was also one of the backgrounds for the Federal Reserve's end of Quantitative Tightening (QT) in late 2025.
In October 2025, the Federal Reserve announced the halt of balance sheet runoff starting from December 1 and began to engage in Reserve Management Purchases (RMP) in December, purchasing short-term U.S. Treasury securities to ensure the maintenance of ample bank reserves.
These operations can easily evoke QE visually, but the policy objectives are different.
QE typically involves purchasing long-term Treasuries or MBS, actively lowering long-term yields, easing overall financial conditions; RMP primarily buys short-term securities like Treasuries, with the official aim of maintaining sufficient bank reserves and controlling short-term rates, rather than providing macroeconomic stimulus. The Federal Reserve also emphasizes that RMP does not indicate a change in monetary policy stance.
The concern is that if the Treasury continues to increase the proportion of short-term financing to reduce long-term supply, then when liquidity buffers like RRP are nearing depletion, new short-term debt may ultimately compete more with bank reserves.
At that point, the Federal Reserve may have to conduct more reserve management operations to maintain systemic liquidity. This sets up a delicate policy mix: the Treasury minimizing duration released to the market, while the Federal Reserve ensures ample reserves at the short end.
Japan and AI are Both Transforming the Supply and Demand Structure of Long-Term Bonds
The issue on the long end has another side: who will buy?
Japan has long been a key foreign investor in U.S. Treasury bonds. The latest U.S. Treasury International Capital (TIC) data shows that as of June 2026, Japan held approximately $1.116 trillion in U.S. Treasury bonds, remaining the largest foreign holder, but down about 2.3% from May.
At the same time, Japan's own long-term government bond yields are rising.
For domestic institutions in Japan such as insurance companies, banks, and pension funds, if Japanese government bonds themselves can offer increasingly attractive yields, the marginal attraction of allocating to U.S. long-term bonds may naturally decrease, especially after taking into account the USD hedging costs.
This does not necessarily mean that Japan will continue to sell U.S. bonds on a large scale, but it does mean that a structural buyer of long-term bonds that has long existed in the past may no longer consistently absorb U.S. duration as stably as before.
Another competitor comes from AI.
The AI infrastructure build-out is transitioning from a stock market story to a credit market story. Goldman Sachs research estimates that from 2026 to date alone, the entire AI-related ecosystem has issued close to $500 billion in debt; of which the hyperscale cloud players themselves have issued around $194 billion. More importantly, it's the tenor. This year, in the U.S. investment-grade credit market, about 40% of new issuances with a tenor of 15 years or longer have come from AI firms or AI-related financing.
This means that traditional long-duration funds such as pension funds and insurance companies are facing more choices. They are no longer just comparing 30-year U.S. Treasury bonds and other sovereign debt, but can also purchase long-term investment-grade bonds of large tech companies like Amazon, Google, and AI-related credit assets such as data centers and infrastructure.
From the author's perspective, this makes the core issue facing U.S. long-term bonds even clearer: the Treasury needs to sell more and more debt, while the other long-term assets that global markets need investors to absorb are rapidly increasing.
Treasury's Version of Operation Twist: $4 Billion Is Not Huge, but the Real Change Lies in the Policy Response
It is also in this context that the Bizarro expands its long-term bond buybacks.
The U.S. Treasury's regular buyback program began in 2024, with the official setting two purposes: to improve secondary market liquidity and for cash management.
Notably, the liquidity support repo primarily purchases older, less liquid securities, known as off-the-run Treasuries. The Treasury Department proactively positions itself as a potential buyer of these bonds, aiming to assist dealers in depleting inventories and enhancing the trading dynamics of these older securities. (U.S. Department of the Treasury)
Therefore, from a structural perspective, this is not a QE tool designed to cap the 30-year yield.
Moreover, a one-time purchase of at least $40 billion in the vast $30 trillion U.S. Treasury market remains relatively small. Reuters also notes that the market widely believes this scale is insufficient to address structural issues such as the fiscal deficit and long-term supply expansion.
However, the author's true focus is not on the scale but on the policy intent.
In the past, the Treasury could emphasize that repos were merely market liquidity tools; now, as the 30-year yield rapidly approaches a two-decade high, the Treasury swiftly expands long-dated bond repos, prompting market participants to question: if the long end continues to spiral out of control, will the Treasury further adjust its repo and issuance structures in the future?
This is why the author refers to the current policy as the Treasury's version of "Operation Twist."
Note: Operation Twist is often referred to as "扭曲操作" or "期限延长操作" in Chinese. Its essence is not "printing more money" but adjusting the central bank's bond maturity structure: selling short-term bonds, buying long-term bonds to depress long-term rates.
The classic 2011 Operation Twist was conducted by the Federal Reserve: selling or letting short-term bonds mature while simultaneously purchasing an equivalent amount of 6-30 year bonds, elongating the asset portfolio duration without expanding the balance sheet, reducing the private sector's holdings of long-term bonds, and lowering long-term rates.
What is happening today is not an exact replica of the same operation. The Treasury is not executing a strict "sell short, buy long" like the Fed did back then, and the expanded repos are still officially defined as debt management and liquidity tools. However, from a market duration supply standpoint, both are somewhat aligned: if the Treasury continues to repurchase more long-term old bonds while leaving more net financing pressure on the short end, the net duration that the private market needs to absorb may relatively decrease.
This is what the author refers to as the "Treasury's version of Operation Twist." More precisely, it is currently a market interpretation rather than an established new policy framework.
Can This Approach Anchor the Long End? Risks May Shift to the Dollar and Inflation
So, under what circumstances would this policy framework continue to escalate? The author argues that instead of looking for an absolute 30-year yield "red line," it is better to observe the speed of the yield increase. A 30-year yield at 5.2% or 5.3% may not be sufficient on its own to trigger a policy change; but if the market begins to see consecutive rapid jumps of around 10 basis points each time, indicating a significant deterioration in market liquidity and demand, the probability of further intervention by the Treasury Department or the Federal Reserve would increase.
Meanwhile, long-dated bond yields have become more directly competitive for funds with equities. As per the data available when the author's article was published, the nominal yield on 30-year U.S. Treasuries is around 5.2%, while the real yield on long-term TIPS is close to 3%; in comparison, the S&P 500 earnings yield is around 3.8%.
While these cannot be directly compared — the earnings yield is not a risk-free rate, and corporate earnings are expected to grow or decline in the future — when the risk-free long-term real yield rises to such a high level, it is evident that the opportunity cost that stock valuations must bear is increasing.
Therefore, the key significance of Bostic's recent move may not be in temporarily pulling the 30-year yield back from above 5.3% to around 5.2%.
It lies in the market getting a new sample of observation: when U.S. long-end yields rise rapidly, will the Treasury Department become increasingly proactive in responding through repurchase sizes and debt maturity structures?
If the answer gradually shifts to "yes," then in the future, the impact on the U.S. dollar, U.S. stocks, gold, and long-term government bonds will involve not just the Fed's policy reaction function but also this additional layer of the Treasury Department.
However, this logic also has its boundaries. If the rise in long-dated yields is primarily due to a bond supply-demand imbalance, reducing the duration that the market needs to absorb may alleviate the pressure; if inflation expectations notably rise again, continuing to expand repurchases, increasing short-term debt financing may instead make market participants concerned that policies are artificially suppressing financial conditions.
Therefore, what truly needs to be observed next is not just whether the Treasury Department will increase repurchases but whether inflation expectations, the structure of long-term bond issuances, overseas demand, and the speed of long-end yield fluctuations are all changing simultaneously.
Only when these variables continue to point in the same direction will the author's proposition that the "Treasury Department is taking over a part of long-end financial conditions management" receive further validation.
[Original Article Link]

Translation: Peggy
Editor's Note: On August 19, the U.S. Treasury Department announced an expansion of long-term bond repurchases, increasing the size of the single-day liquidity support repurchase for some 10–30 year bonds from $20 billion to at least $40 billion. Previously, the 30-year Treasury yield had briefly risen to 5.337%, reaching a new high since 2007; after the news was released, the long-term yield swiftly retreated.
The market immediately began to wonder: Is the Treasury Department showing a more explicit policy sensitivity to the rapid rise in long-term rates?
In his publication on August 20 titled "Hot Take: Bessent Makes His Mark," Stephen Innes discussed precisely this issue. He focused not on the $40 billion repurchase itself but on how this move could change the market's understanding of the U.S. policy "reaction function": when long-term yields rise high enough and fast enough, will the Treasury Department take action again and transition from a mere debt manager to another hand influencing financial conditions?
This development is significant because the policy constraints in the U.S. are increasingly concentrated at the long end. The Fed can directly determine short-term rates but cannot completely control term premia, fiscal supply, and the 30-year Treasury yield. If the Treasury Department starts more actively managing long-end market pressures, the framework of only focusing on the Fed to judge financial conditions will become incomplete.
Innes' key insight is not that the U.S. has entered yield curve control but that the market is starting to realize that Washington may have an undisclosed "policy pain threshold." Once traders believe that a certain yield level will trigger Treasury action, the pricing of future long-term rates will no longer depend solely on inflation, the Fed, and bond supply and demand but will also add a new variable: how high the Treasury Department can tolerate long-term yields rising.
Below is the translation of the original text:
U.S. Treasury Secretary Scott Bessent's latest move has added a new trading variable to the long-term U.S. bond market.
On August 19, the U.S. Treasury Department announced that it would at least double the size of the liquidity support repurchase for certain long-term nominal bonds. The single repurchase limit for 10–20-year and 20–30-year bond maturities will be increased from the current $20 billion to at least $40 billion. The new arrangement will take effect on September 9 and continue until the end of the current quarter's refinancing period on November 4. The Treasury Department's official explanation is to provide more liquidity support for long-term bond maturities.
In terms of scale, this is not a large enough operation to change the overall supply-demand dynamics of the U.S. Treasury market. The U.S. Treasury's bond repurchase mechanism itself is not QE: the Treasury mainly repurchases older, less liquid outstanding bonds to improve market liquidity, rather than injecting base money into the financial system through expanding the central bank's balance sheet as the Fed does with QE.
However, in the view of the author Stephen Innes, what the market is truly trading is not the $40 billion number, but the policy signal behind it.
Limited in Scale, Market Trades First and Foremost on "Why Now"
After the Treasury's announcement, long-term U.S. bond yields quickly fell.
On August 19, the 30-year U.S. bond yield briefly dropped by nearly 10 basis points to 5.187%. The day before, the yield had touched 5.337%, the highest level since 2007. At the same time, the long-end of the yield curve flattened, the U.S. dollar weakened significantly, gold broke $4,500 per ounce, Bitcoin rose, and the three major U.S. stock indexes all closed slightly higher.
These market changes coincided with the Treasury's announcement. However, a more accurate statement is: the market's expectations of the Treasury's policy response changed, rather than the Treasury directly lowering yields on that day by adding repurchase funds.
This is because the expanded repurchase size will not take effect until September 9. Therefore, what is most worthy of attention this time is the "signaling effect."
The author of this article points out that the Treasury could have announced this adjustment during the previous quarter's refunding arrangement, but did not do so at that time. Following that, there was a noticeable sell-off in long-term U.S. Treasury bonds over two weeks, pushing the 30-year yield to nearly a 19-year high before the Treasury separately announced the increase in the repurchase size.
The Treasury did not indicate that this adjustment was aimed at supporting a specific yield level; the official reason remains to enhance liquidity for long-term securities. However, in the author's view, traders will naturally wonder: if long-term yields rise rapidly again in the future, will the Treasury further adjust its policy?
This is precisely what he calls the "Bessent Makes His Mark" core.
From Yen Intervention to Expanded Repurchase, Market Begins to Test Treasury's "Threshold for Action"
This speculation arose quickly also because this was not the first recent event where the U.S. Treasury clearly intervened in market operations.
From late July to early August, the U.S. and Japan made a rare coordinated intervention in the foreign exchange market to support the yen. Less than a month later, the Treasury Department announced an expansion of long-term bond repurchases after long-term bond yields rose to multi-year highs. The two actions targeted different markets, and their policy objectives cannot be simply equated: the former directly addressed exchange rate volatility, while the latter was officially positioned as liquidity management in the government bond market.
However, Innes believes that they collectively influenced investors' assessment of the Treasury Department's reaction function — the market began to speculate on how much and how quickly the Treasury Department might act once asset prices experienced significant fluctuations.
This is also the essence of the so-called "Bessent Put." It is not a formal policy, nor does it mean that the Treasury Department has committed to buying bonds at a certain yield level, nor is it equivalent to Yield Curve Control (YCC).
More precisely, this is a market inference: if traders start to believe that the Treasury Department has an intolerable "pain threshold," whenever the 30-year yield approaches a high point in the future, the market may speculate on whether the policy will be adjusted again.
In other words, the market is looking for the Treasury Department's "intervention threshold": at what level will the long-term bond yield rise to prompt Washington to take action again?
The first intervention informed the market that the Treasury Department is monitoring pressure in the long end of the market. Only if similar actions are taken in the future, the market may further assess whether the Treasury Department truly has a relatively clear policy trigger range.
Whether the "Fed Put" is transitioning to the "Bessent Put" remains the author's judgment
Innes further discussed this change within the framework of the Federal Reserve under Kevin Warsh's leadership.
His assessment is that the Federal Reserve under Warsh aimed to reduce market reliance on central bank-induced suppression of volatility and allow more price discovery to return to the market itself. Therefore, if the Treasury Department becomes more willing to take action in case of sharp fluctuations in bonds or exchange rates, the familiar "Fed Put" from the past may not completely disappear but could show signs of shifting towards the Treasury Department.
It is important to make a clear distinction between facts and judgments.
The confirmed facts are: the Treasury Department recently participated in U.S.-Japan coordinated exchange rate intervention and announced an increase in the scale of long-term bond repurchases; the Federal Reserve still independently manages monetary policy. As for the idea that "policy support is shifting from the Federal Reserve to the Treasury Department," this is Innes' interpretation based on these two market operations and is not a new policy framework announced by the U.S. government.
Similarly, there is currently no evidence that the Treasury Department is implementing yield curve control. In fact, the scale of long-term Treasury bond buybacks remains small. A one-time $40 billion operation is limited compared to the over $30 trillion U.S. Treasury market, and buybacks have not addressed structural issues such as the fiscal deficit, inflation expectations, and long-term bond supply and demand that have led to rising yields.
Therefore, the "Bessent Put" is currently better suited as a concept to describe market expectations rather than an established policy tool.
Fed Still Discussing Rate Hike, Treasury Signals Adding Complexity to Trading Framework
Meanwhile, the signals from the Fed are not distinctly dovish.
The FOMC meeting minutes from July 28 to 29 showed that most members supported keeping the federal funds target rate at 3.50% to 3.75%, but "several" members were inclined to a 25-basis-point rate hike at the next meeting. The minutes also indicated that many members believed that further monetary policy tightening might be necessary if inflation did not continue to decline; ultimately, three members voted against keeping the rate unchanged and favored a 25-basis-point hike.
However, these minutes reflect the policy assessment at the end of July. Subsequently released inflation and employment data have been relatively moderate, leading the market to lower expectations of further rate hikes. This has made the current policy outlook more complex.
On the one hand, there are still voices within the Fed advocating for further monetary policy tightening; on the other hand, the Treasury Department's announcement of increasing long-term bond buybacks has prompted the market to reassess the upside potential of long-term yields, accompanied by a decline in yields and the U.S. dollar.
Innes therefore believes that simply trading U.S. financial conditions around "the next Fed rate hike or cut" may no longer be sufficient.
It is important to emphasize that the Treasury Department's announcement of expanding buybacks does not directly equate to monetary easing. A more accurate statement is that following the announcement, the decline in long-term yields and weakening of the U.S. dollar have had a certain marginal easing effect on financial conditions from a market pricing perspective; whether this effect can be sustained still depends on subsequent inflation, fiscal supply, and market demand.
This is the real issue to watch in the near future.
The Treasury Department has clearly stated that this increase in buybacks will only last until November 4 and will provide further information on future arrangements at the next quarterly refunding meeting. Therefore, for the long-term U.S. bond market, the key is no longer just the next set of inflation data or the next FOMC meeting.
The market is now also watching another variable that has not been so prominent before: if the 30-year Treasury bond yield approaches 5.3% again or even higher, will the Treasury Department adjust its tools again? In other words, what the market is currently testing is: how high does the long-term Treasury bond yield need to rise to trigger the Treasury Department's next move?
Currently, this is still a hypothesis that traders are testing, rather than a yield threshold that has received policy confirmation.
[Original Article Link]

According to PolyBeats News, on August 19th, Beijing time, an individual managed to achieve a 120% return in just 89 seconds by predicting "whether Russia would be able to occupy a certain area in the battlefield."
This individual invested $4,000 to purchase the prediction "Russia will capture Konstantinovka this month" on a platform called a prediction market. The probability of this event happening was only 43% at the time. 89 seconds later, this probability increased to 92%.
In this probability-price platform, if the event does occur, the probability will be locked at 100%, and the position value will increase accordingly. The mysterious individual placed the order, witnessed a sudden surge, and then exited at the take-profit in less than two minutes. In an era where various trading strategies abound, such stroke of luck in trading is not uncommon.
What makes this individual suspicious is that Konstantinovka was his 14th such operation.
14 Consecutive Successful Battlefield Predictions
Analysis of the account's transaction records by PolyBeats revealed that this individual's account had a total of 14 correct prediction trades related to the Russia-Ukraine conflict, realizing a total profit of approximately $17,500.
These predictions did not pertain to the same city or the same timeframe: from Maliyevka, Pokrovka, to Huliaipole, and Konstantinovka; some were about "whether Russia will capture," while others were about "whether Ukraine will re-enter." However, the operations were nearly identical as if copied from the same template.
Even more bizarrely, not only did this account accurately predict the outcome 14 times, but 11 of these trades saw the probability surge to nearly 100% within 5 minutes after the purchase.
It is difficult to consecutively guess the battlefield developments correctly 14 times and buy in before the market probability escalates. However, if the advance knowledge was not of the battlefield but of the map update time, the scenario becomes much simpler.
Prediction Markets: Breeding Ground for Insiders
All of Polymarket's Russian-Ukraine occupation market titles are almost a template:
“Will Russia take over a certain region by ___?”
While the question may seem straightforward, what truly determines the answer is not when the gunfire starts.
According to Polymarket's rules, only when the Russia-Ukraine battleground map produced by ISW—the Institute for the Study of War—labels a specific region as Russian-controlled and meets the duration requirements set by the rules, will the market move to a "Yes" outcome—corresponding to a 100% settlement probability.
In other words, even a soldier standing in the occupied territory cannot insider trade to stable long-term gains in such a market: even if the occupation indeed happens, as long as ISW, the source of settlement, does not update the map, this market will settle as "No."
In such a market, only one type of person can achieve perfect profitability like the aforementioned account: he doesn't need to know the frontline situation, understand Russo-Ukrainian geopolitics and military strategy, or even follow any international current events. He only needs to know in advance which area ISW is ready to mark as Russian-controlled, and when that update will take effect.
This group of people is the technical staff responsible for updating the battlefield status at ISW. They only need to predict the corresponding market long positions to buy into right before clicking the mouse to confirm the ISW map update, enabling them to make a substantial profit within a minute.
Sound like a conspiracy theory? Last year, ISW had already experienced a similar farce.
Employee Manipulates Open-Source Intelligence Data for Massive Profits
In November 2025, the prediction market had already previewed how this mechanism would spiral out of control.
At that time, the market question was, “Will Russia take over Mironohrad before November 15?” The rules were almost identical to the above—only when the ISW map shows any part of the Russian military controlling a specified street intersection, the outcome could be determined as “Yes.”
The most significant difference from the current rules was that there was no "waiting period" back then: as soon as the map changed, the market settlement condition could be met.
On the evening of the 15th, the probability of "Yes" was less than 3% as there were only a few hours left until the deadline—without any geopolitical news reporting the occupation of Mironohrad, everyone had already assumed that this market would ultimately settle as "No."
However, at this moment, the ISW map suddenly showed the area as occupied; before most people could even react, the probability of "yes" was instantly pushed to 100%.
Over the next few days, as traders questioned the lack of concrete evidence for this map marking, ISW publicly admitted that there had been an "unauthorized, unapproved" edit on the interactive map during the night of November 15 to 16; this edit was removed before the start of the normal workflow on the 16th and did not represent its official battlefield assessment.
The map was retracted, but the market did not retract, and those accounts that predicted "yes" when the probability was approaching zero profited greatly from this "unauthorized edit." Among them, 0x69A9 bought in when the probability was only 0.9% and ultimately achieved a 10,888.68% excess return.
Following the Mironohrad incident, ISW stated that its map would continue to be modified during workdays and should not be understood as real-time battlefield conditions; it later added "being edited" and "finalized" status indicators. Prediction markets later also implemented stricter persistence requirements: the map status had to span the next full update cycle to be used as a settlement basis.
As of now, the mastermind behind these 14 consecutive victories has not publicly revealed their identity and has not been accused by any institution; ISW has also not acknowledged any employees benefiting from map update arbitrage.
But the timeline of the 14 victories is clear: almost every time, it placed bets on a city considered "undetermined" by the market; almost every time, it waited until the market was close to certainty before selling; almost every time, it pocketed the difference between "no one knows yet" and "everyone knows."
In the past, a regular ISW employee responsible for updating the map might have been just a nameless screw in a vast open-source intelligence system. What he held in his hands was just a mark about to change color, an update about to be released, and a few seconds before the click of confirmation.
These pieces of information were originally untradeable, and few would have cared.
But when a map can determine the final market settlement, those few seconds before clicking the mouse now have a price. A person doesn't need to disclose top-secret military intelligence, manipulate the battlefield, or even change any facts; all he needs is to know about a mark that is about to appear before everyone else, turning the authority assigned to his position into profits close to certainty.
Innovation has opened a market for everyone to predict the future, but it has also opened another door: when the settlement source can be seen in advance, modified in advance, or traded in advance, you and I can all become insiders.

Emails, chat records, project documents, work orders—these used to be just digital remnants awaiting clean-up after a company shut down. Now, they are being reassessed, packaged, sold, and fed into an AI company's training pipeline.
An undertaker preserves the deceased's final dignity. The postmortem dignity of an enterprise is to prove that what they left behind still holds value.
On August 17, at a bankruptcy asset auction, Google bid $10 million to acquire all of Spirit Airlines' corporate data. Another bidder, Mercor, bid $7.5 million, falling short by $2.5 million.
The auctioned items were divided into three parts. The first part consisted of approximately 100 million employee emails. The second part included 500 million Microsoft Teams messages, totaling 600 million. The third part comprised calendars, spreadsheets, financial databases, project files, operational records, and a batch of internal software. Passenger profiles, frequent flyer information, and the like were not included.
600 million messages—if one person speaks 100 sentences a day, they would have to speak non-stop for over 16,000 years.
Calculating, each message was sold for 1.67 cents. Americans refer to a 1-cent coin as a penny, often not bothering to pick it up if it falls on the ground. In other words, a Spirit employee's sentence in Teams was worth one and a half pennies.
Going back to 1980, Spirit Airlines was born in Detroit, born from a trucking company called Charter One, which later transitioned to aviation. In 1992, it was renamed Spirit, meaning soul. Over the following 34 years, it set the benchmark for the entire industry to replicate the model of ultra-low-cost carriers in the U.S.
It once had a solid foundation—205 all-Airbus fleet, approximately 300 flights a day, and a projected 2024 revenue of around $5 billion. However, it faced a net loss of about $1.2 billion and carried nearly $9 billion in debt when it filed for bankruptcy.
On a late night in May 2026, the company announced it was ceasing operations. The next day, around 17,000 employees found out they were unemployed through the news.
Proceedings are still ongoing, and the transactions are awaiting approval from the bankruptcy court. Spirit is undergoing a liquidation-type closure under Chapter 11 bankruptcy, with no bankruptcy trustee taking over. The company is still supervised by the court and is selling off its remaining assets piece by piece. The sensitive data involving employee emails, Teams messages, etc., must first be handed over to an independent entity for processing. This entity was selected by Google, with Google also bearing the costs.
Furthermore, scouring through public reports, the bankrupt company selling internal data to an AI company is unprecedented. This deal is most likely the first of its kind in history.
The long-standing U.S. tech publication Gizmodo titled this transaction as follows: "Spirit is Dead, But Its Data Will Haunt Google's Servers for Generations."
A New Business Venture
There have always been people who handle the assets of defunct companies. Lawyers, liquidators, auction houses—doing this for decades. Aircraft, furniture, trademarks, patents—all sellable assets have long been sold off.
What's truly new is that starting this year, even a company's internal employee data has been put on the table.
This emerging business has two underlying reasons.
First, the number of defunct companies has increased.
In the first quarter of 2024, the failure rate of U.S. startups surged by 58% year-on-year, and the number of active VC firms decreased by 62% from its peak. The money hasn't decreased; it's just flowing more concentratedly towards AI. In 2024, U.S. AI startups raised a record $97 billion in funding. The capital market still has money, but it's becoming more reluctant to spend outside of AI.
As a result, a group of companies that could have continued to survive on funding are now hitting a wall earlier. In August 2024, the fintech company Tally, backed by a16z, announced its closure. Having raised a total of $172 million, with a peak valuation of $855 million, reaching Series D, it still couldn't secure the next round of funding.
Second, data has become more expensive.
The consumption of data for large-scale model training has reached unprecedented levels. The training data for GPT-4 consists of around 130 trillion tokens. For comparison, Google Books scanned over 40 million books in over forty years, which amounts to about 40 trillion tokens. In other words, the amount of data used for one GPT-4 training is equivalent to over three times the content of Google Books.
Epoch AI ran some numbers and concluded that high-quality language data from books, news, and Wikis will be depleted around 2026. The high-quality text available on the public internet is quickly running out, with synthetic data accounting for an increasing share. Next, AI companies will have to look beyond the public internet for new data. Years-worth of internal company emails, chat records, and work documents have now come into view.
As for the AI training dataset market, research institutions predict it could reach $9.7 billion by 2030. Taking into account various licenses, the total size of the pie is estimated to reach $67.5 billion.
On one side, more and more companies are closing down, leaving behind a large amount of internally generated data that was previously not priced; on the other side, AI companies have an increasing demand for data beyond the public internet. With both sides happening simultaneously, it is the first time that internal corporate data has the conditions for scalable transactions.
What truly adds value to this type of data is the development of Enterprise Agents. Gartner predicts that by 2026, 40% of enterprise applications will embed task-specific AI Agents, a figure that was less than 5% the previous year.
The training material required for Enterprise Agents is not exactly the same as that for large-scale models. While public web pages can provide knowledge, language, and final content, it is challenging to replicate a company's actual work processes. Communication and collaboration involve many real details, such as how a requirement is proposed, how several people discuss it, how tasks are assigned, how issues are addressed, and ultimately how delivery is made.
These processes are extensively recorded in a company's internal emails, chat logs, tickets, and project documents.
When such data begins to have clear buyers and use cases, things that were previously directly deleted when a company shut down now have standalone transaction value.
Body Snatcher
In the past, this job was done by liquidation lawyers, but now three new types of people have emerged.
The first is called a dissolution service provider, represented by SimpleClosure.
This company does only one thing: helping startups die gracefully. In 2023, the company just started, raising $1.5 million in pre-seed funding, and in May 2025, it secured $15 million in Series A funding, led by TTV Capital. Even Carta, which handles equity management and corporate affairs for many US startups, shut down its own closure service, invested in SimpleClosure, and handed over this part of customer demand to it.
By October 2025, SimpleClosure had already conducted funerals for over a thousand companies. Crunchbase gave it a nickname, "A Better Way To Fail," a kind of better way of failing. While American entrepreneurs love to say "fail fast," SimpleClosure argues that fast failure is not enough; it must also be dignified. The company even has a pricing calculator on its website – enter your company's situation, and it will calculate how much it costs to die once.
A funeral is never a waste. In April 2026, SimpleClosure launched the Asset Hub, specifically designed to handle intangible assets left behind after a company shuts down. In addition to brands, software, and customer lists, for the first time, items such as Slack messages, emails, and Jira tickets – internal work data – were explicitly put on the shelf.
This indicates that before Spirit, the market had already begun to attempt to price the internal data of dead companies, although at that time it was still startups, small transactions, and private dealings.
There is a ready-made case. When transcription and captioning company cielo24 shut down, they sold off Slack messages, internal emails, and Jira tickets accumulated over the past 13 years through SimpleClosure. CEO Shanna Johnson later told Forbes that this batch of data eventually sold for hundreds of thousands of dollars.
For a company that has already decided to close its doors, this was originally a batch of data that needed to be cleaned up, but in the end, it became an asset that could be recovered during liquidation.
For the data sales stage, SimpleClosure handed it over to Protege. This is a data exchange market specializing in AI training data licensing. In January 2026, they just received a $30 million investment led by a16z, and the founder is Bobby Samuels. Protege's initial entry point was medical imaging, where within 30 days, they gathered millions of images for pre-training for buyers.
Now, Protege is starting to apply this data licensing and trading ability to internal communication data of closing companies. SimpleClosure is responsible for company closure and asset organization, while Protege is responsible for finding buyers, completing data licensing, and transactions.
The second type of participant is bankruptcy courts and liquidation lawyers. For decades, they have been counting planes, tables, chairs, trademarks, and patents. Now, the list is beginning to include emails, Slack messages, and other internal data.
According to U.S. bankruptcy law, this data can be included as intangible assets in bankruptcy estates and sold under court supervision. Relevant law firms have also begun to establish specialized teams to handle data preservation, discovery, and organization in bankruptcy cases. Redgrave LLP has such a restructuring and discovery business.
The third type is e-discovery service providers responsible for technical execution. Companies like KLDiscovery, Epiq, and Consilio are usually involved in collecting, organizing, hosting, and reviewing enterprise data. The content in emails, Teams, and SharePoint needs to be exported, archived, and organized by them before being packaged into data that can enter the transaction process.
This industry itself already has a mature set of billing methods. EDRM regularly publishes pricing surveys, with common billing units including data collection per GB, hosting per GB per month, and document review fees.
Spirit’s 600 million messages eventually turned into an auction item, relying on this type of foundational work. However, compared to court documents and auction bids, this part rarely appears in public reports. The specifics of who handles it and how it is handled are usually not visible to the outside world.
Autopsy Checklist
For a corporate Agent, what it needs to learn is not just knowledge and standard answers, but also judgment, collaboration, error correction, and execution processes in the real work environment.
The final product tells the model what it has become, while internal records tell it how it was made.
This change has already been reflected in Agent training data. In the past, a single-line of code training sample might only consist of a few hundred tokens, involving modifying a few lines of code; now, an Agent training sample often needs to include the entire process of requirement understanding, file locating, code modification, and test verification.
Training data is transitioning from a single answer to full task execution records. For the Agent, the end result is of course important, but the judgments, operations, and feedback left during task completion are more valuable for training.
Compared to companies operating normally, the data of a shutting-down business is more likely to enter the transaction process. While the company is still operating, selling internal communications would involve trade secrets, employee privacy, non-compete risks, and customer relationships, and legal and management teams are usually very cautious. After entering liquidation, the company's main goal changes to recovering as many remaining assets as possible to secure more value for creditors.
That's why the same batch of internal data, which was difficult to sell while the company was alive, may be revalued during the shutdown phase.
The value of internal corporate data has long been recognized by the industry. Salesforce has always regarded the enterprise communications accumulated in Slack as important data assets, and Microsoft CEO Satya Nadella has emphasized multiple times that when enterprises use AI, a truly valuable part is their proprietary data and work context.
In the past, this data primarily served the company itself. Now, as AI companies begin to actively seek enterprise internal data, they have, for the first time, more clearly defined external buyers.
The Art of Pricing
While this business is still in its early stages, some reference prices have emerged in the market.
SimpleClosure and Protege handle data from closing startups, with individual transactions typically ranging from $10,000 to $100,000. Mercor offers quotes based on the chat logs and emails of acquired startup employees, with the highest reaching $300,000.
Spirit has taken the pricing to the tens of millions of dollars. Mercor bid $7.5 million, and Google ultimately offered $10 million, competing for around 600 million internal communications and other corporate data. Based solely on these 600 million messages, the average price per message is approximately 1.67 cents.
This unit price is not high. In 2024, Reuters reported that Photobucket negotiated licensing deals for about 13 billion photos and videos with an AI company, with prices around 5 cents to $1 per photo and over $1 per video. In the B2B data market, a single contact's information can be sold for a few cents to a few dollars depending on completeness and accuracy.
However, these prices are not yet enough to form a unified standard. The value of internal data from closing companies is currently mainly a matter of individual negotiation. Factors such as data volume, industry, time span, completeness, uniqueness, and what the buyer intends to do with it will all affect the final price. Spirit's $10 million bid appears more like one of the few publicly visible large-scale examples at present.
When compared to established data licensing markets, the gap becomes even more apparent. Reddit licensed user posts and comments to Google for approximately $60 million annually; News Corp's content licensing agreement with OpenAI is around $250 million for five years; xAI's partnership with Telegram amounts to $300 million; and Apple's purchase of Shutterstock image licenses falls between $25 million and $50 million.
These markets already have established buyers, licensing mechanisms, and pricing experiences. Transactions of internal data from closing companies are just getting started, with no clear rules yet on which data is most valuable or whether valuation should be done per item, by capacity, or as a whole.
Looking at Spirit's $10 million within the company's own scale is a different story. In 2024, Spirit's annual revenue was close to $5 billion, averaging around $13.7 million per day. The amount Google spent to acquire this data is less than what it makes in a day during normal operations.
For a bankruptcy liquidation, this is just a small recovery from the remaining assets; for an AI company, it is acquiring a set of long-unseen data containing the real operational processes of the business.
Cleansing and Handover
After the data transaction, it cannot be handed over directly to the buyer. Before the formal handover, it usually needs to go through several steps such as export, de-identification, organizing and packaging, court approval, and final delivery.
The first step is export. Slack's corporate data is usually exported as a ZIP file, including JSON files organized by channel, member information, and attachments.
Microsoft 365, on the other hand, can export emails and Teams messages through an eDiscovery tool. The Spirit transaction involves approximately 600 million internal communications, a large amount of data that requires processing in batches in practice. The specifics of whether this is carried out by an eDiscovery service provider or the buyer's engineering team have not been disclosed in publicly available documents.
Next is de-identification, which involves removing as much information as possible that can be traced back to specific employees. Common methods include identifying and masking personal information such as names, phone numbers, and addresses, or replacing sensitive fields with identifiers that do not directly correspond to individuals. In some statistical and training scenarios, additional random perturbation is applied to further reduce the possibility of re-identifying individuals.
However, de-identification does not equate to absolute anonymity. Even if names and emails have been removed, as long as there are enough professional, temporal, locational, or behavioral features retained in the text, there is still a possibility of re-identifying individuals through other information.
Therefore, the party responsible for this step in the Spirit transaction is crucial. According to the current transaction arrangement, a third-party independent entity will handle the de-identification process, chosen by Google and at Google's expense. Google has also committed not to exploit this dataset to re-identify individuals.
Data sales by bankrupt companies are not unprecedented. Over the past two decades, from Toysmart and Borders to RadioShack and 23andMe, cases have emerged involving the handling or sale of customer data during bankruptcy. Transactions of this nature involving consumer privacy usually face stricter scrutiny from courts, regulatory bodies, and state governments.
What sets Spirit apart is that this sale does not revolve around passenger lists but rather around employee emails, Teams messages, and other internal work data. Existing bankruptcy procedures have not established mature rules for dealing with this type of data as they have for consumer information.
Controversy has already arisen. Spirit's flight attendants union has raised objections to the transaction, leading the court to postpone approval. What was initially a batch of corporate data intended to be sold as bankruptcy assets has now become entangled in employee rights and the boundaries of AI usage.
If the transaction is ultimately approved, the data will enter the final settlement stage. However, there is little public disclosure about the data's journey from the finalized dataset to Google's systems. It is currently unknown how the data is transmitted, whether further cleansing will occur, and in what form it will ultimately enter product development or model training.
At this point, the program truly completes the transformation of data from bankruptcy assets to AI assets.
Buyer
The most clear-cut buyers of this type of data at present are model companies like Google and training data service providers like Mercor.
Google's official statement regarding this Spirit transaction is that the data will be used for product improvement and AI development. For Google, the value of this dataset lies in its documentation of a large enterprise's real operational processes, such as scheduling, collaboration, internal communication, project advancement, issue resolution, and management decisions.
These details are hard to obtain from public web pages. Particularly for corporate agents, beyond just the final outcome, what is more important is how tasks are progressed and completed within a real organization. The internal records left by Spirit happen to contain a significant amount of such process data.
Another bidder, Mercor, provides further insight into where this business is heading.
Founded in 2023, Mercor's three founders—Brendan Foody, Adarsh Hiremath, and Surya Midha—have been debate team partners since high school. The company initially focused on AI recruitment, using models to help companies screen and interview candidates. By September 2024, Mercor had evaluated around 300,000 job seekers, reaching a valuation of $250 million.
Subsequently, the company's focus shifted towards AI training data. In November 2025, when the three founders were only 22 years old, as the company's valuation rose, they became some of the youngest self-made billionaires globally. In the first half of 2026, Mercor's revenue exceeded $614 million, with about 90% coming from top AI labs like OpenAI. By July, the company was seeking a valuation of around $20 billion and had acquired Deeptune, a company specialized in building training environments for AI agents.
Mercor primarily acquires training data through two main paths.
One is by directly purchasing internal company records. They have made offers to acquired or closed-down startups to buy employee chat logs and emails, with individual companies receiving offers of up to around $300,000.
Another one is hiring people with real work experience. In October 2025, TechCrunch reported that an AI lab recruited former employees through Mercor, allowing them to convert their work experience into training tasks and feedback at an hourly rate of about $200. The CEO of Mercor stated that the company pays out over $1.5 million daily to individuals participating in AI training.
On one side, acquiring the company's retained work records, and on the other, acquiring the work experience held by employees. Mercor's core assets are essentially work processes from the real world.
This also explains why it appeared at Spirit's auction. For Mercor, 6 billion pieces of internal communication were another, larger-scale source of training data.
This type of business also comes with risks. In 2025, Scale AI sued Mercor, alleging that former employees took trade secrets; subsequently, the company experienced training-related information leaks and partnership suspensions. Data is both Mercor's business and its most critical asset to defend.
Lastly, there is a numerical contrast. Spirit operated under this name for 34 years, while Mercor, bidding on its internal data, had three founders who were only 22 years old at the time.
Broken Bench
The transaction for Spirit is not yet finalized, the court has not signed off, and Google has not acquired that set of data. There are still union objections, hearings, and many procedures to go through.
But this auction has already made something that was seldom discussed before more concrete.
In the past, when a company closed, many things did indeed disappear. Financial statements remained, trademarks remained, patents remained. However, a company's day-to-day experience usually did not. How a department conducts meetings, how a manager makes decisions, how dozens of people coordinate after a delay, why a process eventually changed to its current state – these things are rarely formally documented.
As a company dissolves, people leave, email addresses deactivate, chat groups close – they also disappear.
So, a company has always been a peculiar organization.
It can exist for decades, accumulating the experiences of tens of thousands of people, but what can truly be inherited is often only a very thin slice of it. The next company will have to hire again, make mistakes again, and learn many things all over again.
The potential AI is changing is exactly this. If emails, meetings, tickets, code changes, and internal discussions can truly be organized into training data, then a company's past experiences that could only be passed down by talent have, for the first time, found another way to be preserved.
Where this will ultimately lead is still difficult to determine. Perhaps in the future, companies will proactively save this data, perhaps employee contracts will be rewritten, perhaps bankruptcy laws will add new restrictions, perhaps companies will separately value even internal work records during financing and M&A.
Spirit has raised this issue early.
The word bankruptcy has a widely circulated etymology. Medieval Italian merchants conducted business sitting behind a bench. When their debts exceeded their assets, the bench was publicly destroyed. banca rotta, broken bench.
For centuries, when the bench broke, it was all over.
Spirit's bench has already broken. The 600 million messages it left behind are being repriced.
One message at one and a half pennies.
Original Article Link

Can someone who once helped Soros break the Bank of England now use the same tactics to defend the U.S. Treasury market?
Since the beginning of this year, U.S. Treasury Secretary Scott Bessent has made consecutive moves, using a series of unexpected market operations to stake his reputation on suppressing American borrowing costs. According to Bloomberg, he has become the "most proactive Treasury Secretary in decades in intervening in the financial markets".
Following the U.S.-Japan joint intervention in the yen, Bessent's latest move is to expand U.S. bond repurchases. The Treasury Department announced that it would "at least double" the scale of repurchases of 10 to 30-year Treasury bonds—and this repurchase plan was only announced just two weeks ago. On the day the news was released, the yield on the 10-year Treasury bond fell by roughly 6 basis points, the 30-year yield fell by nearly 9 basis points, and the U.S. dollar index also fell to a three-month low.
The market's reaction confirmed Bessent's judgment: he has publicly stated, "My job is to be the nation's top bond salesman, and the U.S. Treasury yield is the barometer of success."
From Shorting the Pound to Guardian of the Bond Market
To understand Bessent's strategy, we must go back to 1992.
That year, in his early twenties, Bessent worked at the Soros Fund and participated in building a short position on the pound. On "Black Wednesday," the pound was forced to exit the European Exchange Rate Mechanism, and Soros netted over $1 billion. According to media reports, a former advisor described Bessent at the time as someone who "could see market vulnerabilities that others couldn't."
Afterward, he returned to Soros as Chief Investment Officer, leading a $1 billion yen short in 2013, once again reaping substantial returns. In 2015, he founded Key Square Capital Management with $4.5 billion, betting successfully on Brexit and Trump's two election victories.
This "find the crack, then push with the trend" hunter logic has run through his entire hedge fund career.
And now, he is using the same intuition to do the exact opposite—defend a market under pressure.
This Year's Intervention Map: From Yen to U.S. Bonds
Bessent's moves this year have already formed a clear logical chain.
Step One, Yen Intervention. On July 31, the U.S. Treasury, in conjunction with Japanese authorities, intervened in the market to buy yen, marking the first direct yen intervention by the United States in nearly thirty years. According to data from the Peterson Institute for International Economics (PIIE), Japan used approximately $87 billion of its foreign exchange reserves to purchase yen in the last two days of July, with the U.S. Treasury "joining in the final stages, providing a relatively limited amount of funding but sending an important political signal of support." It is worth noting that the Treasury sold euros instead of dollars, and the European authorities were not informed in advance.
Behind this move lies an undercurrent: Japan holds around $1.1 trillion in U.S. Treasuries, making it the largest foreign holder. If Japan had intervened alone to finance the intervention, it might have been forced to sell U.S. Treasuries, further driving up long-term yields. Washington's participation allowed Japan to sell fewer U.S. Treasuries, indirectly preserving the yield curve that Secretary Benson cares most about.
Step Two, Bond-issuance Contraction Signal. Earlier this month, the Treasury hinted at a potential reduction in the issuance size of long-term bonds, signaling an expectation of supply tightening to the market.
Step Three, Enhanced Repurchase. It was announced this week that the size of long-dated bond repurchases would at least double, providing direct support to prices from the demand side.
Bloomberg cited Brad Golding, portfolio manager at Christofferson Robb & Co., as saying this is akin to "an old-school ‘clean screens’ maneuver" — a hedge fund technique involving simultaneous orders to multiple major dealers to trigger significant market volatility.
Mark Sobel, a former U.S. Treasury official now with the OMFIF think tank, told Bloomberg, "He is absolutely a radical, which harkens back to his hedge fund background." "Both he and this administration are clearly concerned about the rise in long-term yields."
Breaking "Rules and Predictability"
Benson's actions are in direct conflict with the Treasury's traditional principles.
The U.S. Treasury has long adhered to a principle of "rules-based, predictable" debt management, avoiding surprises for the market. Benson himself publicly endorsed this principle at a Treasury market conference in November of last year.
However, his recent actions have deviated from this commitment.
Gregory Faranello, Head of U.S. Rate Trading and Strategy at AmeriVet Securities, told Bloomberg, "This violates the 'rules-based, predictable' principle — but that’s the world we're in." "The signal is clear: Prevent the rise in yields."
Ironically, Bernett's predecessor Yellen adjusted the debt issuance structure in 2023 to suppress yields, with Bernett being one of the critics at the time, accusing the move of being politically motivated. Former chief economist for Trump, Stephen Miran, also co-authored a paper in 2024 criticizing the "Aggressive Treasury Issuance" (ATI).
According to Bloomberg, Miran and Nouriel Roubini wrote in the paper: "Once a party starts using ATI to stimulate the economy during the election season, all future administrations may follow suit."
Question: Can Intervention Solve Structural Issues?
The market had a short-term reaction to Bernett's actions, but economists have more fundamental questions.
As of the first ten months of the 2026 fiscal year, federal net interest payments have reached $963.0 billion, approximately $3.18 billion per day, a 14% year-on-year increase. The 10-year Treasury yield stands at 4.72%, while the 30-year yield is at 5.31%—a significant amount of old debt previously issued at under 2% is now rolling over at higher rates. The deficit for the 2026 fiscal year to date is $1.8 trillion, expanding by 5% from the previous year, with spending on Social Security, Medicare, national defense, and interest on debt all rising, while the Republican Party is still discussing further tax cuts.
Robin Brooks, Senior Fellow at the Brookings Institution, bluntly told Bloomberg: "This is not addressing the root issues—reducing debt, shrinking the fiscal deficit, but rather trying to manipulate the yield curve."
John Velis, BNY Macro Strategist, also stated: "Given current spending policies and wars, alleviating pressure at the long end will be very difficult."
The effectiveness of yen intervention is also questionable. After hitting a high of 163.98 against the dollar on July 23, the USD/JPY pair fell to 159.43 by August 17, but according to CNBC, intervention did not prevent the continuous weakening of the yen. Maurice Obstfeld of the PIIE directly stated that intervention had minimal effect, saying, "Foreign exchange intervention is not a free lunch, not even a free cake."
Guy Miller, Chief Strategist at Zurich Insurance, told Bloomberg: "This approach can only work for a while. When the Treasury clearly states its intention to continue intervening, it can indeed have a quite strong effect. But ultimately, if the profligate fiscal policy is not addressed, this is unsustainable."
Onepoint Bfg's Chief Investment Officer Peter Boockvar was more direct: "He is waging war on two giant markets at the same time - the U.S. bond market and the foreign exchange market. This is an extremely difficult battle."
The Bet on Reputation
Bridgewater's logic, as articulated in his own words, is quite clear. Referring to the Trump administration's stakes in technology and resource companies last month, he said: "What we want to do is create a market signal." Speaking on Fox Business, he said: "Essentially, it's telling investors, okay, where the puck is going to be, skate there quickly."
The problem is that in 1992, shorting the pound was about finding a systemic weakness and taking advantage of it. Now, he is facing structural pressures driven by fiscal deficits, inflation expectations, and Fed policy - things that cannot be fundamentally changed through repo operations or exchange rate interventions.
According to Bloomberg, Mark Sobel, who served in the Treasury Department for nearly 40 years, believes Bridgewater is the most radical Treasury Secretary since the early 21st century. However, he also characterized yen intervention as an unwise move, arguing that it avoided the fiscal consolidation that the U.S. truly needs.
Original Article Link

TL;DR
· The U.S. Treasury will expand its repurchase of nominal coupon securities in the 10-20 year and 20-30 year sectors, increasing the single-operation limit from $20 billion to at least $40 billion.
· This operation is aimed at temporarily improving liquidity for longer-dated securities, reducing marginal term premiums, but is not part of the Fed's quantitative easing.
· Related Instruments: TLT, QQQ, Gold, BTC, and growth stocks sensitive to long-term yields.
On August 19, the U.S. Treasury announced an expansion of liquidity support operations for long-dated bonds, increasing the single-operation limit for nominal coupon securities in the 10-20 year and 20-30 year sectors from $20 billion to at least $40 billion.
This adjustment will take effect on September 9 and will continue until the end of the quarter refinancing on November 4. The Treasury stated that the scale of subsequent arrangements will be explained in the November 4 quarterly refinancing.
The market initially reacted positively to the news. According to an AP report, the 10-year Treasury yield dropped from 4.71% the previous day to 4.64%, while the 30-year yield decreased from 5.28% to 5.18%. A Reuters report indicated that the 30-year yield briefly fell by nearly 10 basis points to around 5.188%.
For investors holding technology stocks, long-duration bonds, gold, and crypto assets, this move primarily impacts discount rates. As long-term yields retreat, risk assets receive an initial valuation cushion. However, transforming it directly into "Treasury's version of QE" is still proceeding too quickly.
Treasury Buys Non-On-The-Runs
This operation does not involve purchasing all long-term government bonds, but rather focuses on less actively traded old securities, known as off-the-run securities. New issuance bonds have the best liquidity, and as trading in old securities diminishes, bid-ask spreads tend to widen, prompting holders to demand higher compensation.
When the liquidity of off-the-run securities deteriorates, pressure manifests in long-term yields. Market makers and institutions are reluctant to take on risk, necessitating higher yields to attract buyers. By increasing the repurchase limit, the Treasury is essentially proactively buying some illiquid securities when there is significant pressure in the long end of the market, facilitating a smoother trading system.
This is crucial for risk assets, as the 30-year yield serves as a valuation anchor. The higher the yield, the heavier the discount on future cash flows, putting pressure on growth sectors such as tech, AI, high-valuation stocks, and long-duration bonds. While gold and BTC do not have the same cash flow models, investors often include them in the trading framework based on real interest rates and global liquidity.
The boundary is also clear. The Fed's quantitative easing is the central bank expanding its balance sheet through bond purchases, creating reserves in the banking system. The Treasury Department's bond buybacks are debt management operations, with the funds still needing to be arranged within the fiscal accounts and debt issuance structure. It can improve trading conditions for certain maturities or types of bonds, but it will not automatically reduce the U.S. government's financing needs.
The Market Is Buying a Softening at the Long End
The market reacted quickly because this move targeted investors' most sensitive area. With the 10-year yield above 4.6% and the 30-year yield above 5%, any signal that can lower term premiums is seen as a valuation pressure relief and is traded as such.
Bond prices rise, corresponding to a decline in yields. Stocks rise, corresponding to a softening of discount rates. If gold is traded based on real interest rate fallback logic, it will also benefit. The response of crypto assets depends more on risk appetite and liquidity expectations, but in macro trading, they may still be linked to the same chain.
According to Axios, TD Securities' Gennadiy Goldberg characterized this operation as "not QE." Reuters quoted BCA's Ryan Swift, who stated that this move is more of a signal, and the impact may be temporary.
This is the core of the current rebound. What the market bought into first was the Treasury's unwillingness to allow a deterioration of liquidity at the long end of the market, rather than the fact that the Treasury is already capable of keeping rates low in the long term. The former is enough to trigger short-covering, while the latter still requires actual purchase volume and issuance structure to validate.
Raising Beardson's Tools Faces Supply Constraints
The first variable limiting imagination in this trade is scale. In the Treasury Department's August 5 quarterly refunding statement, the liquidity support buyback cap for this quarter was set at a maximum of $38 billion. With the increase in the long-end operation limit, calculated based on the current schedule and single cap, the additional cap is at most about $14 billion.
This number is not insignificant in a single-day price move, but in the context of the U.S. fiscal deficit, long-term bond stock, and quarterly funding needs, it is not enough to change the overall direction. It is more like adding a cushion at the most congested point in the market rather than removing long-end supply pressure.
The second variable is a funding source. The Treasury's buyback of old bonds cannot create funds out of thin air. If buybacks need to be supported by more short-term or mid-term bond issuances, the pressure may simply shift from the long end to other maturities, altering the yield curve's shape, but the financing needs persist.
The third variable is inflation and the Fed. As long as inflation expectations are not stable, or if the Fed maintains a somewhat tight stance, long-term yields will eventually return to fiscal supply, real rates, term premiums, and buyer demand. While the Treasury can enhance market microstructure, it is challenging to unilaterally rewrite macro pricing.
Therefore, a more prudent assessment is that this operation marginally benefits long-end assets, especially when the market was previously heavily positioned for rising yields, making it prone to a rebound. However, it does not prove that the upward pressure on long-term rates has ended.
November Refinancing Tests the Rebound's Strength
The extent of this rebound will depend on whether the Treasury turns temporary liquidity support into a more systemic issuance structure adjustment. The quarterly refinancing statement on November 4th will provide information on the next phase of buyback size and bond issuance arrangements.
If the actual buyback amount approaches the raised ceiling and, at the same time, net issuance of long-term new bonds slows down, the market will be more willing to believe that the Treasury is proactively reducing upward pressure on long-term supply. The repricing of long-dated bonds, growth stocks, gold, and BTC will also have a smoother continuation.
If buybacks mainly serve as a signaling tool, and long-term issuance pressure does not decrease, possibly requiring more short-term debt in addition to financing, this operation will resemble more of a tactical move to stabilize the market. It may dampen short-term volatility but will struggle to alter investors' long-term demands regarding deficits, inflation, and term premiums.
For risk assets, this is not a scenario that can unconditionally lead to a dovish narrative. It serves as a cushion in long-end rate trading, with the short-term direction clear but the strength determined by actual execution and long-term net supply.

Google Ties Stock Options to Chip Supply, Clinical Results and Leveraged Short Squeeze are Turning Long-Term Expectations into Price. The latest developments in Homsud indicate that whether the supply can stably reach the market remains a hard constraint.
1｜Google Ties Stock Options to Marvell, Procures with Capital Incentive Embedded in Same Contract
Marvell disclosed that it has issued warrants to Google to subscribe to up to 58.97 million shares of common stock, with an exercise price of $206.58 per share, exercisable no later than August 2033. If all are exercised, approximately $12.2 billion would be calculated at the exercise price. The warrants are tied to Google's revenue target for custom chip procurement.
This does not mean Google has already paid $12.2 billion, nor has it locked in all future orders. The procurement scale and vendor equity incentives are written into the same arrangement, which may strengthen long-term cooperation between the two parties and increase the opportunity cost of exiting the partnership. Major cloud providers are using capital tools to increase supply chain certainty in key design stages.
(Source: Marvell / CNBC)
2｜Bitcoin's Sharp Rise Triggers Massive Short Squeeze, Leveraging Amplifies Short-Term Market
Bitcoin broke through $68,000 during trading on August 19, approaching $69,000 at one point. CoinDesk cited CoinGlass data indicating that around $1.4 billion worth of short positions were liquidated in the previous four hours. Ethereum rose nearly 9%. News of long-term Treasury bond repurchases concurrently suppressed US bond yields, but this cannot be construed as the direct cause of the rise.
After surpassing the short squeeze level, additional buying continued to drive the market higher. What the market needs to observe is not $69,000 itself, but whether leverage is accumulating again, if spot funds can support, in order to determine whether this trend is a short squeeze or a longer trend. Short-term fluctuations could still be further amplified.
(Source: CoinDesk / CoinGlass / CNBC)
3｜Moderna and Meruson's Personalized mRNA Vaccine Phase III Trial Meets Criteria
Meruson and Moderna announced on August 19 that the personalized mRNA candidate vaccine intismetran autogene combined with Pembrolizumab's III phase INTerpath-001 trial achieved the primary and key secondary endpoints. This global randomized, double-blind trial included 1,137 fully resected stage IIB to IV melanoma patients, with registration number NCT05933577.
This is not regulatory approval. Full efficacy, long-term survival, and safety data are still pending disclosure and review. For the mRNA platform, Phase III clinical endpoints have provided a validation milestone for the oncology pipeline, but the outcome for one indication does not equate to widespread commercialization.
(Source: Merck / Moderna / ClinicalTrials.gov)
4｜UAE Cuts Trade with Iran, Hormuz Sees U.S.-Led Oil Shipping Lane
The UAE announced on August 19 a halt to trade, commercial links, and financial transactions with Iran. AP reported that the UAE had been targeted by Iran again. According to Axios citing U.S. officials, the U.S. military organized a shipping lane in the Strait of Hormuz near Oman, through which about 10 million barrels of oil pass daily, roughly half of pre-war levels.
While trade settlement channels are tightening, physical crude flows are being attempted to be maintained. The shipping route has yet to normalize. Reuters data on August 14 showed only 9 ships transited the strait in a day, averaging about 12 ships in August, far lower than the pre-conflict level of around 130 ships. Oil price risks depend on security, insurance costs, and continuity. (Continuation of yesterday's report)
(Source: AP / Axios / Reuters)
Also Worth Knowing ↓
Cognition CEO Scott Wu denies SpaceX sought acquisition. Bloomberg reported that SpaceX had considered acquiring Devin developer Cognition at around a $40 billion valuation, but Wu stated the company is not for sale. The parties are still discussing a computing power collaboration with no agreement yet. (Continuation of yesterday's report) (Source: Bloomberg / TechCrunch / Reuters)
The U.S. Treasury raises the single-day limit for some long-term bond repurchases to at least $4 billion. Reuters stated the operation covers 10- to 30-year bonds, causing the 30-year yield to subsequently decline. Repurchases are not equivalent to Fed rate adjustments. (Source: U.S. Treasury / Reuters / CNBC)
The U.S. pauses 50% tariffs on Canadian goods for three days. Trump claims an agreement, while Reuters noted key terms are still undisclosed. The pause does not mean trade conditions have been finalized. (Continuation of yesterday's report) (Source: White House / Reuters / BBC)
Samsung Electronics reportedly raises new orders' prices by 5% to 15% for some advanced processes. The SF4 price increase for Chinese and American customers is said to be 10% to 15%, with AI chip demand boosting capacity utilization. (Source: Reuters / Tom's Hardware)
The U.S. Securities and Exchange Commission (SEC) has proposed a draft of the "Cryptocurrency Asset Regulation Act," which includes two types of cryptocurrency issuance exemptions. The SEC stated that one type is applicable to early-stage projects that raise up to $5 million within four years, while the other type can raise up to $75 million within 12 months. The proposal is not yet in effect. (Source: SEC)
Sarah Friar, CFO of OpenAI, announced that the company plans to go public in 2027 or earlier. On the same day, OpenAI pledged not to retain data from corporate clients using its models. The Wall Street Journal reported that this arrangement is aimed at attracting corporate clients unhappy with Anthropic's data retention policy. The exact timing of the IPO is still an internal expectation. (Source: CNBC / The Wall Street Journal / TechCrunch)

Bitcoin surged from $65,000 to $70,000 overnight, while Ethereum saw a nearly 20% increase, approaching an all-time high. The hype is real.
The cryptocurrency market was booming overnight, possibly influenced by developments in the United States.
On July 20, President Trump convened a roundtable discussion and delivered a public speech at the White House in Washington, D.C., with top executives from American finance, cryptocurrency, and technology companies, as well as regulatory agency officials.
The attendees included prominent figures such as CFTC (Commodity Futures Trading Commission) Chairman Mike Selig, SEC (Securities and Exchange Commission) Chairman Paul Atkins, President's Digital Asset Advisor Council Executive Director Patrick Witt, and top leaders from the cryptocurrency industry such as Coinbase CEO Brian Armstrong, Intercontinental Exchange (ICE/New York Stock Exchange) CEO Jeff Sprecher, Nasdaq CEO Adena Friedman, Robinhood CEO Vlad Tenev, Kraken CEO Arjun Sethi, Ripple CEO Brad Garlinghouse, Chainlink Co-founder Sergey Nazarov, Winklevoss brothers, among others.
The key focus of this meeting was President Trump emphasizing that the U.S. is competing with other countries globally for dominance in the financial markets and AI field, and he pledged to ensure that the future of global financial technology is established and perfected within the United States.
However, from the list of attendees, it was evident that the cryptocurrency industry played a significant role in this event.
Crypto Legislation
President Trump first highlighted his accomplishments in the cryptocurrency industry over the past two years, focusing on Bitcoin reserves and other less critical topics. The crucial aspect was his discussion of crypto legislation.
- The Genius Act: Trump mentioned that he signed this landmark bill a year ago. The act significantly paved the way for the widespread adoption of compliance-oriented stablecoins pegged to the U.S. dollar, reinforcing the dollar's global dominance and driving substantial global investment in U.S. Treasury bonds.
- The Clarity Act: Currently in a critical stage of Congressional progress, this act aims to legislatively clarify the distinction between "crypto securities" and "crypto commodities."
Trump urged Congress to expedite the passage of The Clarity Act to establish a clear legal framework for digital assets. Coinbase CEO Brian Armstrong revealed during his speech that Congress is planning to vote on the bill on September 15. If successfully passed, it will solidify the regulatory gains of the past year in a long-lasting legal form.
Introduction of Hyperliquid and Proposal of New Cryptocurrency Financing Regulations
Next is the statement from regulatory agencies, which is equally important after all, as they are the regulatory bodies.
CFTC (Commodity Futures Trading Commission) Chairman Mike Selig and SEC (Securities and Exchange Commission) Chairman Paul Atkins provided detailed updates on their respective agencies' specific projects regarding deregulation and embracing innovation.
Regarding the CFTC:
- First Compliant Bitcoin Perpetual Futures: CFTC Chairman Mike Selig confirmed that the United States' first true "Bitcoin perpetual futures contract" was launched by an exchange registered with the CFTC in May 2026.
- Introduction of the decentralized protocol Hyperliquid: The CFTC is actively advancing a compliance framework aimed at introducing the decentralized trading protocol Hyperliquid into the U.S. in a fully legal and compliant manner.

This is also a core reason for HYPE's overnight surge.

- Safeguarding Prediction Markets: Federal regulators are actively intervening to prevent local state officials (such as New York Attorney General Letitia James) from improperly interfering in compliant prediction markets, to avoid such financial innovations from being forced overseas.

Regarding the SEC:
- Proposal of "Crypto Asset Rule": SEC Chairman Paul Atkins announced that the SEC has just proposed a brand-new crypto asset rule to definitively address the issue of crypto startups legally conducting equity and capital financing in the U.S. through digital assets.
- Capital Market Recovery and "Trump Accounts": Benefiting from the rationalization of IPO thresholds, there have been 583 companies listed since the new administration took office (a 75% increase year-on-year), raising $28 billion; while promoting "Trump Accounts" to allow the younger generation of investors to better participate in the capital market boom.
The new regulations for cryptocurrency asset financing are also quite significant. Legal ICOs are making a comeback. For more details, you can read this article 《The Biggest Bull Run in the Crypto Circle, Is Compliant Token Financing Coming Back?》
Bitcoin Reserve
During the final Q&A session, there was an interesting question about whether the US government would further expand its Bitcoin reserve.
Trump expressed openness and stated that he would listen to the regulatory team's advice.
Empty promises are seen as positive news.
Another part of the discussion was about AI; however, not much useful information was provided. In response to the significant power consumption of AI, Trump proposed a fast-track approval policy that would allow tech companies to build their own dedicated power plants (approved within two to three weeks). This approach aims to not strain the public grid while enabling the excess power to be fed back into the traditional grid.

In mid-August, major funds successively released their 13F quarterly reports, disclosing the static holdings of the funds as of June 30.
· Odaily Note: The so-called 13F is a quarterly disclosure document that the U.S. Securities and Exchange Commission (SEC) mandates for funds with assets under management exceeding $100 million. The SEC requires that funds meeting the disclosure requirements must submit this document within 45 days after the end of each calendar quarter. Funds are required to focus on disclosing their holdings of U.S. listed stocks, call/put options, convertible bonds, and specific ETF positions held at the end of the previous quarter in the document.
Although there is a certain lag in the disclosure timing of 13F, making it unsuitable for simple copying, as a direct window into the top funds' layouts and movements, 13F still holds significant importance for exploring the ideas of on-chain high-level players. The consensus and discrepancies among different funds may well hide clues to future market trends.
In the following sections, we will analyze the 13F reports of seven top funds, including Berkshire Hathaway (Buffett, Abel), Duquesne Family Office (Stanley Druckenmiller), H&H International Investment (Duan Yongping), Himalaya Capital (Li Lu), ARK Investment (Cathie Wood), Oriental Harbor Overseas Fund (Dan Bin), Situational Awareness LP (Leopold Aschenbrenner), focusing on core holdings and major trends, hoping to add value to your investment strategy.
Berkshire Hathaway (Buffett, Abel)
Report Summary
As of June 30, Berkshire Hathaway disclosed a total of 29 holdings in its 13F report (13F only covers U.S. listed securities subject to disclosure and does not equate to the fund's total asset size), including 1 new position, 7 increases, 6 reductions, and 1 exit, with a nominal holding market value of approximately $299.3 billion.
It is worth noting that this is Berkshire Hathaway's second 13F filing under CEO Greg Abel's formal leadership. This filing marks Berkshire's first significant net buying quarter after ending the previous streak of 14 consecutive quarters of net selling, with net stock purchases amounting to nearly $20 billion.
Top Holdings
Berkshire's portfolio remains highly concentrated, with the top ten holdings accounting for about 88.47% of the total:
· Apple (AAPL): Approximately $65.95 billion, holding the top position with a 22.0% allocation;
· American Express (AXP): Approximately $51.28 billion, representing 17.1% of the portfolio;
· Alphabet (Google, GOOGL + GOOG): Approximately $37.76 billion, including around $28.16 billion of GOOGL (Class A common stock with voting rights) and $9.61 billion of GOOG (Class C common stock with no voting rights), making it the third-largest holding;
· Coca-Cola (KO): Approximately $32.51 billion, accounting for 10.9% of the portfolio;
· Bank of America (BAC): Approximately $27.54 billion, with a 9.2% allocation;
· Chevron (CVX), Occidental Petroleum (OXY), Chubb (CB), Moody's (MCO), Kraft Heinz (KHC) round out the sixth to tenth positions.
Structurally, Berkshire Hathaway has not significantly altered its core positions in the consumer, financial, and energy sectors. However, the addition of Alphabet has notably increased the weighting of the technology sector in the portfolio.
Quarterly Changes
In the second quarter, Berkshire's most significant move was undeniably a major bet on Alphabet—increasing its holdings of Alphabet's Class A shares (GOOGL) by approximately 24.54 million shares, a 45.2% increase, and also boosting its holdings of Class C shares (GOOG) by about 23.60 million shares, a staggering 658.3% surge. The combined increase of about 48.10 million shares has propelled Google into the fund's top three holdings. Apart from Alphabet, Berkshire notably increased its stakes in Delta Air Lines (DAL), Lennar Corporation (LEN), Macy's (M), among others.
On the other hand, reductions were mainly concentrated in the financial, consumer, and cyclical sectors. Bank of America (BAC) reduced its holdings by about 30.23 million shares, a 5.9% decrease, being reduced for two consecutive quarters; Capital One (COF) reduced its holdings by about 58%, Kroger (KR) by about 22%, Ally Financial (ALLY), DaVita (DVA), and Nucor (NUE) also saw declines.
Summary Analysis
Under the Abel era, Berkshire Hathaway is undergoing a subtle style shift, with the clearest signal in the second quarter being a tilt from traditional finance and consumer stocks towards tech growth. The heavy position in Google not only further breaks Buffett's stereotype of "avoiding tech stocks," but also reflects the new management's deep recognition of Google's moat in AI and search—essentially still a typical "value confirmation" rather than trend chasing.
However, Berkshire's core holdings remain unchanged: stake in "anchor" companies such as Apple, American Express, Coca-Cola are basically unchanged, and the energy sector's Chevron and Exxon Mobil have not been sold off (the decrease in percentage is mainly due to dilution from new holdings).
Overall, this quarter Berkshire Hathaway is showing a rebalancing logic of "heavily increasing positions in tech leaders, structurally reducing financial and consumer stocks, holding onto core energy positions, and tentatively positioning in real estate and aviation." While quietly pushing the portfolio towards a digital future while maintaining extremely high concentration, Abel's Buffett-esque nature of "long-term commitment" and "big bets" is still clearly visible.
Duquesne Family Office (Stanley Druckenmiller)
Although not as famous as Buffett and Berkshire, Stanley Druckenmiller may be the most noteworthy fund manager on Wall Street today.
Who is Druckenmiller? He is a legendary American macro hedge fund manager who served as the Chief Investment Officer of Soros Fund Management from 1988 to 2000, becoming Soros's most successful trader... And today, his most critical role is that both Treasury Secretary Scott Bennett and Fed Chair Kevin Wash have been his disciples (having either studied under him or had a long-term working relationship with him).
Therefore, compared to Berkshire's more long-term focused 13F, Duquesne Family Office's quarterly report is more like a macro trading map—especially in a time when AI, interest rates, and the U.S. economic outlook are all rapidly changing.
Report Summary
As of June 30, the Duquesne Family Office disclosed a total of 95 positions in its 13F filing, with 48 new stocks added during the quarter, 16 increased positions, 11 decreased positions, and 23 stocks completely sold off. The nominal value of the holdings is approximately $52.1 billion, a significant increase from the previous quarter's $33.8 billion.
Core Holdings
The 13F filing reveals that the Duquesne Family Office's top ten holdings account for approximately 45.8% of the portfolio:
· Genetic testing company Natera (NTRA) remains the largest stock holding of the Duquesne Family Office, with approximately 3.19 million shares at the end of the second quarter, valued at around $865 million, representing about 16.6% of the portfolio;
· The second and third largest holdings have shifted to TSMC (TSM) and STMicroelectronics (STM), accounting for approximately 5.4% and 4.4% of the portfolio, respectively;
· Additionally, biopharmaceutical company Insmed (INSM, held in both stock and options), Argentinean national oil company YPF Sociedad Anónima (REPYY), and Amazon (AMZN) are among the top ten holdings.
Quarterly Changes
In the second quarter, the most notable change by the Duquesne Family Office was a shift within the AI industry supply chain.
The Duquesne Family Office completely sold off Micron (MU), Broadcom (AVGO), and Intel (INTC), with Broadcom having been a new addition in the first quarter. However, this does not mean that Druckenmiller has abandoned semiconductors; instead, he continued to increase positions in TSMC (TSM) and STMicroelectronics (STM), and initiated a new position in AMD. Furthermore, the fund has begun to expand its reach into the periphery of AI infrastructure, buying into Hut 8 (HUT), Bitdeer (BTDR), Riot Blockchain (RIOT), and other Bitcoin mining companies that are transitioning towards data center operations.
It appears that Druckenmiller has chosen to cash out some of the previously highly appreciated positions, while reallocating the funds to assets he believes offer a superior risk-return profile.
Furthermore, in the second quarter, the Duquesne Family Office also reestablished its position in Alphabet (GOOGL), which it had just exited in the first quarter, and significantly increased its holdings in Amazon (AMZN) that were reduced in the first quarter—this move may be a bet that the large tech companies that had previously borne significant AI capital expenditures will gradually transition from being the "payers for AI infrastructure" to being the "beneficiaries of AI commercialization."
In addition to the aforementioned AI-related portfolio changes, the Duquesne Family Office, like Berkshire Hathaway, also expressed bullish views on the aviation sector, initiating a new position in Delta Air Lines (DAL) and increasing its stake in United Airlines (UAL); notably, in the second quarter, the Duquesne Family Office also initiated a new position in Baidu ADR (BIDU) of approximately 88,000 shares, marking its first holding of U.S.-listed Chinese stocks in two and a half years since liquidating Alibaba at the end of 2023.
Summary Analysis
If we were to condense this 13F into a single sentence, Druckenmiller has not departed from AI but is instead repositioning for the next phase of AI winners. At least based on the end of the second quarter holdings, Druckenmiller has still maintained a significant AI exposure, but has reallocated from parts of the highly crowded hardware sector to areas like cloud platforms, data centers, and AI applications.
Simultaneously, Baidu's reappearance is another signal worth noting. While the 88,000-share position is not large, the tentative reentry into Chinese tech assets after long avoidance at least indicates a renewed interest.
It is worth reiterating that due to Druckenmiller's relatively high-frequency reshuffling, the Duquesne Family Office's 13F report is more challenging to simply "copy," making it more suitable for observing directional shifts.
H&H International Investment (Neil Shen)
Turning our attention to H&H International Investment managed by the Chinese legendary investor Neil Shen. From this 13F report, it can be seen that Shen's holdings remain highly concentrated, but there are signs in the second quarter of a rotation from some highly valued tech stocks towards Chinese internet companies.
Report Summary
As of June 30, H&H International Investment disclosed a total of 18 positions in its 13F filing, with a nominal value of approximately $19.101 billion (equivalent to about RMB 130 billion), down from around $20 billion at the end of the first quarter.
It is worth noting that 13F filings only disclose long positions in US stocks, so assets held by Duan Yongping such as Tencent, Pinduoduo, Moutai, and a large number of put-option premium-selling operations are not included in this table.
Top Holdings
H&H International Investment's portfolio remains highly concentrated, with the top five largest positions accounting for over 88% of the total.
· Apple (AAPL): Approximately $7.841 billion, representing 41.05% of the portfolio, maintaining its position as the largest holding;
· Berkshire Hathaway (BRK.B): Approximately $4.618 billion, representing 24.18%, forming the "ballast" together with Apple;
· Pinduoduo (PDD): Approximately $1.91 billion, accounting for 9.99%, rising to the third-largest position, signaling a significant increase in the weight of Chinese internet companies in Duan Yongping's system;
· Tesla (TSLA): Approximately $1.42 billion, accounting for 7.44%;
· NVIDIA (NVDA): Approximately $1.26 billion, accounting for 6.58%.
Quarterly Changes
In the second quarter, the most significant move by H&H International Investment was a substantial increase in its Pinduoduo (PDD) position—adding 5.2738 million shares, a 26.71% increase, propelling it to the third-largest position; meanwhile, there was a slight increase in Berkshire Hathaway Class B shares (BRK-B), which can be interpreted as a long-term endorsement of the value investing framework. Additionally, Alibaba (BABA), which was completely sold off by Duan Yongping in the first quarter, saw a repurchase of 301.4 thousand shares (approximately $28.93 million) in the second quarter.
As for the reduction of holdings, AI and tech leaders were the main targets for profit-taking by H&H International Investment in the second quarter. NVIDIA (NVDA) saw a divestment of 7.5631 million shares, a significant 54.63% reduction; Google (GOOG) sold over 1.7 million shares, a 46.88% decrease; Microsoft reduced its holdings by 25.78%; Apple also trimmed its position by 1.8469 million shares—marking the second consecutive quarter of selling (after selling 3.4129 million shares in the first quarter); additionally, TSMC and CrowdStrike (CRWD) were completely liquidated.
It is worth mentioning that Duan Yongping is not simply bearish on the tech stocks he sold. In late July, he publicly stated, "I will add more Google," while also expressing his intention to continue seeking opportunities to buy NVIDIA at lower prices through selling Put options. In other words, the reduction in positions is more a reflection of price and margin of safety considerations rather than a complete rejection of the companies themselves.
Summary Analysis
If we were to summarize this 13F filing in one sentence—sell a bit on the way up, buy a bit on the dip, and hold onto good companies.
Overall, the second-quarter repositioning strategy of H&H International Investment appears relatively clear—slight adjustments to core holdings, increased exposure to Chinese internet companies, and profit-taking on high-growth AI assets. Apple and Berkshire Hathaway remain core holdings, but after continuous reductions, Apple's position has decreased for two consecutive quarters; meanwhile, Pinduoduo has become a new top three holding, and Alibaba has reentered the portfolio; although NVIDIA, Google, and others were reduced, it was not a bearish move but rather a realization of gains, with Duan Yongping expressing a desire to reacquire them at lower prices in the future.
This indicates that Duan Yongping's actions in the second quarter were not a full pivot towards a new theme but rather a reassessment of margin of safety amidst valuation changes, with a partial realization of gains on high-growth AI and tech leaders and a re-up in exposure to Chinese internet companies, which he is more familiar with after a long period of adjustment.
Himalaya Capital (Li Lu)
Similar to Duan Yongping, another legendary Chinese investor, Li Lu, who heads Himalaya Capital, also significantly increased his holdings in Pinduoduo (PDD) in the second quarter.
Report Summary
As of June 30, 2026, Himalaya Capital disclosed a total of 8 positions in its 13F filing, increasing holdings in 2 companies and liquidating 6, significantly reducing the number of holdings from 14 in the first quarter. However, the nominal value of total holdings increased from $3.201 billion in the first quarter to $3.703 billion, further shrinking and concentrating its positions, with the top five holdings now accounting for a high 94.77% of the portfolio.
Core Holdings
The 13F filing shows that Himalaya Capital's current 8 positions reflect a "Google Anchoring, Pinduoduo Surging, Financial Foundation" pattern.
· Google (GOOGL + GOOG): Approximately $1.775 billion, accounting for 47.64% of the portfolio, held long-term since 2020, serving as the unwavering "anchor" in Li Lu's portfolio;
· Pinduoduo (PDD): Approximately $0.821 billion, accounting for 22.17%, surged to the second largest position after a significant increase in holdings;
· Berkshire Hathaway (BRK.B): Approximately $0.555 billion, accounting for 14.98%, continues to accumulate holdings;
· East West Bancorp (EWBC): Approximately $0.358 billion, accounting for 9.68%, position unchanged.
· In addition, Crocs (CROX, 2.90%) and Tencent Music (TME, 1.50%) remained unchanged, while Apple (AAPL) is left with a mere 0.88% as a minimal observation position.
Quarterly Changes
In the second quarter, Himalaya Capital only added two new positions, liquidating the other six existing positions in one go, a resolute decision rarely seen among top funds.
Pinduoduo (PDD) was the most significant addition by Himalaya Capital in the second quarter — adding 6.1531 million shares, a staggering 133.53% increase, with holdings soaring from 4.608 million shares to 10.7611 million shares, ending the quarter with a market value of approximately $0.821 billion, becoming the second largest position. Furthermore, Berkshire Hathaway (BRK.B) saw an increase of 23.46%, effectively entrusting more funds to Buffett and Abel's management.
Meanwhile, Himalaya Capital completely exited 6 positions in one go—Bank of America (BAC), Occidental Petroleum (OXY), S&P Global (SPGI), Moody's (MCO), MSCI (MSCI), H&R Block (HRB). This signifies Li Lu's decisive withdrawal from traditional finance, index data services, and the oil and gas sector. Particularly noteworthy is Bank of America, which was once one of its core anchors, aligning with Berkshire Hathaway's "bank reduction" this quarter, but Li Lu chose a complete exit instead of a slight reduction.
Summary Analysis
If the second quarter of Li Lu's operations were to be condensed into a sentence, it might be — a significant reduction in positions outside the Circle of Competence, further concentrating limited funds on a few truly understandable companies.
On one hand, there is the maintaining of a heavy position in Google (GOOGL, GOOG) and at the same time increasing the position in Pinduoduo (PDD), with the former representing Li Lu's long-term view on the U.S. tech leader and the latter on Chinese internet assets; meanwhile, the liquidation of holdings in financial, energy, and index service-related assets also implies that Li Lu is further shrinking his investment portfolio, with the current concentration of positions being very close to his classic value investment style.
Of course, similar to the situation with Duan Yongping, the 13F will only disclose securities in the U.S. market that meet the criteria, so this document cannot represent Li Lu's entire investment portfolio; assets in the Hong Kong stock market such as BYD, Postal Savings Bank of China, CRRC Corporation, etc., will not appear in this 13F.
ARK Investment (Cathie Wood)
Report Summary
As of June 30th, ARK Investment managed by the "female Buffett," "WoodSis" Cathie Wood, disclosed a total of 191 positions in the 13F, including 15 new holdings, 78 additions, 96 reductions, and 6 liquidations, with a nominal holding market value of approximately $15.4 billion, a significant increase of over $2 billion compared to the previous quarter.
In the second quarter, ARK Investment's repositioning was more aggressive, showing Wood's typical high turnover style.
Core Holdings
The 13F report shows that ARK Investment's top ten core holdings account for a total of 39.45% of the portfolio, with a relatively moderate level of concentration, displaying a relatively high risk preference in the core asset portfolio.
· Tesla (TSLA): About $11.61 billion, holding percentage 7.5%, still the largest core position but has been reduced for the third consecutive quarter;
· AMD (AMD): About $8.2 billion, holding percentage 5.3%, a core holding in the AI computing power sector;
· SpaceX (SPCX): About $7.65 billion, holding percentage 5%, a new entry this quarter directly into the core position;
· Tempus AI (TEM): Approximately $5.8 billion, position weight 3.8%, focused on precision medicine + AI diagnostic benchmark;
· Robinhood (HOOD): Approximately $5.25 billion, position weight 3.4%, fintech and retail investor ecosystem.
Quarterly Changes
In the second quarter, ARK Investment's most significant move was the "rush funding" of SpaceX (SPCX). On the first day of SpaceX's listing on June 12, ARK's various ETFs collectively bought approximately 3.29 million shares, which had increased to 4.478 million shares by the end of the quarter, with SPCX's weight in the fund's portfolio reaching nearly 7% at one point.
Aside from SPCX, in the second quarter, ARK Investment's investment landscape also showed a clear trend of deepening its industry chain. Cerebras Systems (CBRS) was newly included, representing its bet on AI computing architecture; Google (GOOG) saw an increase, strengthening the exposure to platform AI; the purchase of X-Energy (XE) signaled the fund's early layout of nuclear energy as a baseload power source in the AI era; and the additional position in Eli Lilly (LLY) reinforced the focus on life sciences...
Regarding reductions, the most noteworthy action was the continuous reduction in Tesla (TSLA) for three consecutive quarters, indicating ARK's assessment of Tesla's diminished relative position in the AI narrative.
Summary Analysis
Overall, ARK Investment's actions in the second quarter demonstrated a restructuring logic of "actively embracing SpaceX's listing, expanding AI and energy boundaries, reducing traditional core holdings, and maintaining high turnover innovation hunting."
ARK Investment still maintains a relatively high risk appetite among the top funds, focusing more on finding technologies that can transform industry structure—from AI computing power to aerospace, nuclear energy, and life sciences, "disruptive innovation" remains the fund's most enthusiastic theme.
Oriental Harbor Overseas Fund (Bin Du)
Compared to previous funds, the latest 13F report of the Oriental Harbor Investment Master Fund managed by Chinese renowned investor Dan Bin can be considered quite "aggressive" — instead of simply adjusting a few stocks, it almost completely revamped its AI holdings.
Report Summary
As of June 30, the Oriental Harbor Investment Master Fund disclosed a total of 13 positions in its 13F report, including initiating 7 new positions, increasing 1 position, decreasing 5 positions, and fully exiting 6 positions, with a total nominal value of approximately $1.65 billion, representing a growth of about 45.6% from around $1.133 billion in the previous quarter.
Core Holdings
The 13F report indicates that by the end of the second quarter, the top five core holdings of the Oriental Harbor Investment Master Fund accounted for approximately 73% of the total portfolio, further increasing the portfolio concentration, with AI hardware and semiconductor industry-related targets comprising over 70% of the portfolio weight, signaling a significant shift in the portfolio style.
· Google (GOOG): Approximately $371 million, with a roughly 23% allocation, maintaining its position as the largest core holding;
· Intel (INTC): Approximately $258 million, with a 16% allocation, making a new entry and landing as the second-largest position in the second quarter;
· NVIDIA (NVDA): Approximately $217 million, with a 13% allocation, slipping from first to third in holdings percentage;
· SanDisk (SNDK): Approximately $176 million, with an 11% allocation, entering as the fourth-largest position;
· Micron (MU): Approximately $170 million, with an approximately 10% allocation, witnessing a doubled-up increase;
· Positioned sixth to tenth are AMD (8.9%), MRVL (7.9%), TSM (4%), ARM (3.2%), and AVGO (1.5%).
Except for Google, nine out of the top ten core holdings belong to AI computing infrastructure or the semiconductor industry chain, as the "shovel-selling" hardware logic has completely replaced the previous focus on core software platform holdings.
Quarterly Changes
This quarter, Oriental Harbor Overseas Fund launched a "saturation attack" on the AI hardware industry chain, newly acquiring 7 related targets in one go—Intel (INTC), SanDisk (SNDK), AMD, Marvell Technology (MRVL), ARM, Broadcom (AVGO), Lumentum (LITE), all focusing on computing chips, storage, optical communication, and semiconductor upstream. Among them, Intel directly became the second largest position, SanDisk and AMD entered the top six holdings, with a clear intention to increase exposure to the storage sector.
While fully embracing hardware, Ben has also "cut ties" with existing holdings. Nvidia (NVDA), TSMC (TSM), Amazon (AMZN) have all been reduced; although Google remains the top holding, compared to the first quarter, 155,200 shares have been sold, and the 2x long Google ETF has also been completely liquidated, significantly reducing its overall weight in the portfolio.
In addition, the Oriental Harbor Overseas Fund has also completely sold off Apple (AAPL) and Tesla (TSLA), the two leading consumer electronics companies, in the second quarter, perhaps indicating that Ben is not optimistic about the short-term recovery of the consumer end. At the same time, the fund has also liquidated its position in stablecoin issuer Circle (CRCL).
Summary Analysis
Overall, the most crucial information in this 13F report from Oriental Harbor Overseas Fund is that Ben is still betting that AI CapEx will continue to flow to the hardware side. While the market is still debating whether there is an AI bubble, Ben believes that the hardware segment, the "selling shovels" part, is still the most certain direction.
This is also in line with Ben's recent public statements—he still believes that AI is the super trend of the next decade and has stated that the market still does not fully grasp AI's long-term potential. During the storage market's major correction at the end of July, Ben even made a high-profile statement that "you must dare to buy when there is a big drop and have already used up all remaining ammunition."
Situational Awareness LP (Leopold Aschenbrenner)
For the story of the "AI Stock God" Leopold Aschenbrenner and his fund Situational Awareness LP, we have provided a detailed interpretation in the article "Today, the world finally understands why the 'AI Stock God' has fallen."
Due to its outstanding performance in the past few quarters, the 13F of Situational Awareness LP was highly anticipated by the market. However, it is regrettable that the fund experienced a dark moment at the end of July—due to a significant pullback in AI-related stocks combined with high leverage, the fund suffered major losses, was forced to liquidate large-scale public market positions, and has already packaged most of its stock portfolio at a discount for sale to Citadel, managed by Ken Griffin.
Breaking down Situational Awareness LP's 13F filing reveals an even more regrettable story. The fund had built a bearish options position on chip and storage industry leaders with a nominal value of over $8 billion by the end of the first quarter, intending to effectively hedge against the current market downturn. However, due to an early shift to an overall bullish outlook, Leopold Aschenbrenner himself dismantled this insurance wall, ultimately leading to the fund's once glorious performance being discounted and taken by Ken Griffin.
The AI Narrative Remains Unchanged; What's Changing is Where the Money Flows
Putting together the 13Fs of these seven funds seems to point to a relatively clear consensus — AI remains at the center of top investors' vision, with funds significantly repricing around the AI industry chain. The growth of AI seems undisputed, but the real question is, in the next phase, who can truly turn investment into profit?
Berkshire Hathaway has begun a major stake in Google, Druckenmiller is rotating within the semiconductor sector and recommitting to cloud computing and AI infrastructure; Bin, on the other hand, is more aggressive, significantly shifting the overseas portfolio towards chips, storage, and optical communication; ARK continues to explore next-generation growth assets in AI, SpaceX, energy, and life sciences. Meanwhile, Duan Yongping and Li Lu are not simply chasing the AI trend but, after reducing holdings in tech stocks with significant gains, are reallocating funds to assets they are more familiar with and consider to have a higher margin of safety.
Mere observation of each fund's 13F makes it difficult to deduce a clear "next big stock," but the capital movements of different funds are themselves a rotation game regarding AI investment logic — from GPUs, chips, storage, networking, optical communication, data centers, power, cloud computing, commercialization... From selling shovels to providing computing power, and finally sharing in the commercialization dividend of AI, funds are continuously seeking the next profit realization point on the AI value chain.
It is worth emphasizing once again that all these positions are as of June 30, 2026. The 13F itself has a disclosure lag of up to 45 days, especially pertinent for investors like Druckenmiller and Bin who reposition quickly. Thus, rather than treating it as a "homework copying list," it is better to view it as a snapshot of how different funds are interpreting the market in the next phase.
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TL;DR
· Part of the daily transit capacity through the Strait of Hormuz has dropped to extremely low levels, but Brent has not consistently risen above $100.
· The market is temporarily betting that inventory releases, transshipment, alternative exports, and buyer detours can absorb some of the impact.
· Related assets: Brent/WTI crude oil, Energy ETF, Oil tanker companies, Chinese independent refineries, Diesel supply chain, Gold.
Since August, shipping tracking and media reports have shown that part of the daily transit capacity through the Strait of Hormuz has dropped to extremely low levels, with statistics showing little to no tankers passing through. However, Brent crude has not consistently risen above $100. After a brief spike in late July, it has recently spent more time around $90.
This is precisely the point that needs explaining in the current energy market. Around 20 million barrels per day of oil products are transited through the Strait of Hormuz by 2024, accounting for about 27% of global seaborne oil and roughly a fifth of global LNG trade. Under the traditional pricing framework, this area has long been under threat, and oil prices should quickly reflect a supply disruption premium.
Strait of Hormuz Impacting Oil and Gas Trade
The market's current answer is more restrained. The risk has not disappeared, but investors currently believe that inventory releases, transshipment outside the Gulf, alternative exports, and shipping arrangements can mitigate the impact. Oil price trading is not about "Strait security" but about "Costlier strait transit."
The US-Iran standoff provides the political backdrop for this reassessment. Reportedly, the two sides are in dispute over the conditions for implementing the June interim memorandum, with the US maintaining blockade and sanction pressure, while Iran insists on normalizing transit only after conditions are met. The dispute has spilled over to the market, which is essentially a cost allocation issue: who bears higher insurance, financing, voyage, and sanction risks.
Oil Prices Have Not Traded the Worst-Case Scenario Yet
Current prices indicate that the market is not currently pricing in the Strait of Hormuz as a long-term comprehensive supply disruption.
If investors believe that around 20 million barrels per day of seaborne oil products will permanently disappear, Brent is unlikely to remain only around $90. The fact that prices have not consistently risen above $100 suggests that traders are more inclined to interpret it as blocked passage, rising costs, and delivery delays, rather than a supply chain breakdown.
Brent Retreats After Spiking
There is still statistical noise here. Part of the daily traffic volume has plummeted, possibly due to vessels turning off AIS tracking, short-term waiting by ship owners, differences in data sources, or it could also indicate commercial ship owners' reluctance to enter high-risk waters. The former is closer to data distortion, while the latter would create a sustained supply shock.
Therefore, the fact that oil prices have not stabilized above $100 is not because the Strait of Hormuz is insignificant, but because the market is still awaiting further confirmation. Whether Iran can continue to escalate attacks, whether the U.S. will escalate the blockade to more direct action, and whether Asian buyers can still bypass transportation and sanction constraints will all impact this pricing dynamic.
Buffer Mechanisms Break Down the Shock
The oil price did not immediately spiral out of control, and a key reason is that the shock did not hit the end supply chain all at once but was broken down into inventory, shipping, trade, and financial segments.
The most direct buffering comes from inventory and expected alternative supplies. Strategic petroleum reserves, international coordinated releases, OPEC+ spare capacity, and the export capabilities of Saudi Arabia and the UAE outside the strait could all mitigate the impact of a single channel disruption on spot prices. These measures are not unlimited, but they are sufficient to temporarily prevent the market from pricing in a doomsday scenario.
Detour Capacity Can Only Cover Some
The second layer of buffering comes from ship-to-ship transfers. Some cargoes can be transferred near Fujairah or the Gulf of Oman, then rerouted. This will increase insurance, waiting time, and operational costs but will allow the flow of goods to maintain some elasticity.
The third layer of buffering comes from the choices of buyers and ship owners. Some Asian buyers and ship owners may switch to loading outside the Gulf, transshipment, or delay port calls, and similar risk-averse actions may be taken in LNG transportation. As a result, the decrease in traffic through the Strait of Hormuz does not necessarily mean a synchronous global decrease in oil and gas availability.
This is the essence of the current pricing. The physical risk is still present, but it has been spread out through financial inventories, shipping engineering, and trade arrangements. The oil price has not skyrocketed because the system is still functioning. The oil price has not dropped because the system is operating at a higher cost.
The Shock is Absorbed in Segments
Long-Term Costs Enter the Supply Chain
The more effective the short-term buffering, the clearer the investment case for long-term restructuring becomes.
Efforts by Saudi Arabia and the UAE to promote reserves outside the strait, transshipment near Fujairah, and alternative export capabilities, as well as discussions around regional pipeline and port investments to bypass the Strait of Hormuz, all point in the same direction: the energy supply chain is reducing its reliance on a single chokepoint.
This type of restructuring will not immediately change the global supply-demand balance. The new pipeline needs financing, construction, and security conditions, and strategic reserve expansion also takes time. But it will change the long-term cost structure. Port facilities, reserves, insurance, tanker scheduling, and offshore loading capacity are shifting from contingency plans to necessary costs.
For Asian buyers, another cost comes from secondary sanctions, where the U.S. extends pressure to third-party refineries, banks, and shipping insurance. If sanctions more explicitly target the transaction chain for purchasing Iranian oil, the cost advantage that Chinese independent refineries have relied on in the past will be eroded by U.S. dollar clearing, financing, and insurance risks.
This is why the energy market cannot only focus on the Brent front-month contract. Diesel, freight rates, insurance costs, refinery margins, and regional price differentials may reflect the true transmission of the Hormuz risk earlier than the crude oil price.
Inventory days and sanction enforcement will rewrite pricing
The current low volatility is based on one assumption: that the cushion mechanisms can still operate, and military escalation has not crossed the market's red line.
Inventories can buy time but cannot replace long-term supply. Re-routing can bypass some risk-prone areas but will bring higher insurance costs and longer voyages. Alternative export capacities can provide pricing buffers but are difficult to fully absorb the main flows in the short term. As these cushion margins weaken, oil prices will reassess the probability of supply disruption.
Sanction enforcement intensity will also alter the price path. If the U.S. primarily sends a deterrent signal, Asian buyers may still be able to absorb the impact through trade structures and financial arrangements. If sanctions truly target refineries, banks, and shipping insurance, Iran's export discounts may become ineffective, and costs will transmit from the shipping end to the refining end.
The signal Hormuz is sending to the market now is not risk reduction but rather risk absorption in segments. Whether Brent can retest and sustain above $100 depends on how long inventories, re-routing, and buyer detours can bear the burden. The next price validation may first appear in freight rates, insurance costs, and diesel crack spreads.

On June 30, HYPE Treasury company Hyperliquid Strategies (PURR) was officially included in the Russell 3000 Index and Russell 2000 Index. Earlier, PURR had been included in the S&P Global BMI Index. Following the listing of HYPE-related ETFs, this milestone achievement is also seen as further evidence of Wall Street institutions positioning themselves in HYPE tokens and the Hyperliquid ecosystem.
Recently, with the latest 13F filing disclosures, more investment institutions have either initiated a position or increased their holdings in PURR, with news of such actions coming to light. Taking this as a clue, Odaily Planet Daily explores the industry's representative institutions indirectly increasing their HYPE exposure. (Note: The following holdings' total value is based on the June 30 PURR stock price calculation.)
Wall Street Institutions and Family Offices Actively Buying In: Duquesne Family Office, Renaissance Technologies Among the Ranks
Let's first talk about hedge funds and family offices that have actively bought in or increased their holdings of PURR shares.
Duquesne Family Office: Holding $23 million in PURR Company Stock
The Duquesne Family Office submitted its 13F holding report for the second quarter of 2026 to the U.S. Securities and Exchange Commission (SEC), revealing that as of June 30, Duquesne disclosed for the first time holdings worth $23 million in HYPE Treasury company Hyperliquid Strategies Inc (Nasdaq: PURR). The institution currently manages assets of approximately $5.2 billion.
Founded by Stanley Druckenmiller, one of Wall Street's most renowned macro investors, the institution has a 30-year track record without consecutive losses. Druckenmiller, with a background at Soros's Quantum Fund, served as Chief Investment Officer and gained fame for his classic trade "breaking the Bank of England" in 1992.
Additionally, current Fed Chair Powell previously worked at the Duquesne Family Office, with significant assets exceeding $100 million before his tenure, including two investments related to the Duquesne Family Office each exceeding $50 million, possibly in connection with providing advisory work for the family office.
Renaissance Technologies: Holds $18.7 Million of PURR Stock
Founded by the late mathematician Jim Simons and currently led by Peter Brown, the firm manages assets worth over $96 billion. Its renowned flagship fund, Medallion, is one of the most successful hedge funds in history. According to its latest 13F filing, the firm increased its stake by about 2.4 million shares of PURR stock, valued at approximately $18.7 million.
As the world's most famous quantitative hedge fund, Renaissance Technologies' quantitative algorithms and investment models have always been praised by numerous market investors. Holding PURR stock indicates that the stock has met its algorithmic screening standards in terms of quantitative factors and pricing efficiency.
Slate Path Capital: Holds $21 Million of PURR Stock
Founded by David Greenspan, who previously served as a partner and managing director at the well-known "Tiger Cub" hedge fund Blue Ridge Capital. This fund is a typical fundamentally driven "Tiger Cub" fund, focusing on global equities and macro structural opportunities. Currently, the AUM is approximately $12 billion.
According to its latest 13F filing, the firm holds about 2.7 million shares of PURR, valued at around $21.4 million.
Discovery Capital Management: Holds $10.3 Million of PURR Stock
Founded by Robert Citrone, also from a Tiger fund background, Discovery was formally established in 1999 and currently manages assets of around $3.5 billion. It is known for its focus on emerging markets, forex, fixed income, and global macro hedging trades.
Its investment style falls into the "aggressive opportunistic" category, excelling in seeking alpha in high-volatility assets. Currently, the firm holds about 1.3 million shares of PURR, valued at approximately $10.3 million.
Balyasny Asset Management: Holds $3 Million of PURR Stock
Founded by Dmitry Balyasny, Scott Schroeder, and Taylor O'Malley, the asset management firm has around 2,700 employees globally across 24 offices. It is one of the world's top multi-strategy hedge funds. As of August 2026, the firm's AUM is approximately $38 billion.
The latest data shows that the institution holds about 386,000 shares of PURR stock, worth approximately $3 million.
Wealth High Governance Capital: Holds about $17.1 million worth of PURR stock
The institution is a Brazilian independent wealth management and asset management firm based in São Paulo. It is not a traditional bank-owned asset management institution but a boutique asset management platform set up by former senior executives of the Brazilian private bank Credit Suisse around 2020. The key figures driving global asset investment are the institution's founding partner and CIO, Andrew Reider, who previously worked at the Moreira Salles family office and Verde Asset Management. Currently, the institution's total assets under management are approximately $940 million, with its U.S. 13F filing stock portfolio size around $640 million.
The latest data shows that about 1.82% of the institution's total holdings are in PURR stock, valued at around $17.1 million.
In addition to the above institution, other institutions actively buying PURR stock include Tudor Investment Corporation, Point72, D.E. Shaw, etc., but due to their smaller holdings, they are not detailed here.
Passive Holding Giants: Vanguard Group and Nuveen
As mentioned earlier, in addition to actively increasing positions by hedge funds and other institutions, Vanguard Group and TIAA's asset management platform Nuveen, benefiting from PURR's addition to the Russell Index, passively increased their holdings of PURR stock.
Among them, global asset management giant Vanguard Group, with assets under management exceeding $10 trillion, increased its PURR stock holdings by about 843,000 shares in Q2, worth around $6.6 million; TIAA's asset management platform Nuveen, with assets under management currently around $1.4 trillion, tracing back to as early as 1898, increased its holdings by about 1.07 million shares of PURR stock in Q2, worth approximately $8.4 million.
According to Marketbeat data, institutional purchases of PURR in Q2 2026 totaled approximately $142 million.
Recently disclosed institutions holding PURR stock include well-known names such as Paradigm and Bank of America, with positions typically ranging from tens of thousands to millions of dollars.
Of course, the disclosure date for the 13F filing is June 30, and the size of PURR holdings by major investment institutions may have experienced varying degrees of change. However, looking at the overall trend, PURR's institutional investors have gradually shifted from early-stage crypto arbitrage companies to quantitative funds, hedge funds, and even Wall Street traditional financial institutions. Institutions such as BlackRock, Jane Street, Geode, and Invesco have also seen passive buying through index funds. In other words, the exposure to HYPE tokens and the Hyperliquid ecosystem has attracted more and more attention, experimentation, and position allocation from the traditional financial industry. Even the state of Ohio, USA, indirectly holds PURR stock to achieve this goal. In the pursuit of the "next generation of global financial infrastructure," traditional financial institutions will never sit idly by.
However, the future is bright but the road is winding. Before the Hyperliquid welcomes a future with more global capital liquidity, the price performance of the HYPE token and the continued development of the Hyperliquid ecosystem still have a long way to go.
Recently, Hyperliquid's "AQAv2 Revenue Sharing Mechanism," set to launch on August 26, is expected to contribute $200 million in annual HYPE buyback funds, a mechanism also supported by Circle and Coinbase. With this favorable stimulus and the ongoing development of the Hyperliquid HIP-3 and HIP-4 markets, the HYPE token price is expected to see a new round of rebound.
Once, ETH was seen as the "global financial asset taken over by Wall Street institutions." Now, this expectation rests on HYPE, and whether it can live up to this expectation may be revealed in Q4 of this year.
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Music plays, a row of silver humanoid robots and martial arts school children throw punches, kick, and spin simultaneously, with precise moves. This is the CCTV Studio 1 on New Year's Eve.
As the performance enters the second half, the robots start somersaulting one after another—front flips, backflips, aerial 360-degree spins, landing steadily every time. Midway through, one robot stumbles and falls, then quickly gets up and continues the routine. 600 million people watched the entire show through their screens.
The man who created them is called Wang Xingxing. He doesn't like to talk.
Butterfly
Over thirty years ago, at a kindergarten in Yuyao, Zhejiang, Wang Xingxing drew his first painting in life.
A butterfly.
He had never learned to paint. He copied the butterfly from an illustration book. A child in kindergarten, who had never taken a single art class, drew with such steady lines that everyone said it didn't look like the work of someone his age. The teacher showed it to other teachers, who then showed it to parents. Many years later, Wang Xingxing still remembered this incident.
During a later interview, he voluntarily mentioned this butterfly. There was no tale of genius behind this story, just a concern, an excessive sensitivity to details.
In everyday objects, whether the lines are straight, whether the glue is evenly applied, he could notice it all, always wanting to erase the imperfections.
This acute sensitivity to specific things stayed with him later on.
Wang Xingxing is from Yuyao. Yuyao is the hometown of Wang Yangming, a Zhejiang Eastern County known for scholarship. At the age of five or six, Wang Xingxing, too short to reach the stove, found fault with how the meals were cooked at home. He brought a stool, stood on it, and started cooking by himself. When he recalls these past events, his choice of words is "overly sensitive"—"much of the time was spent in mental struggles." He couldn't find a more accurate description than "OCD."
But when it comes to language, everything is turned upside down. English words couldn't be memorized. Some Chinese characters, when he picked up the pen, he suddenly couldn't write. In hundreds of high school English exams, he only passed three times. He applied for a postgraduate program at Zhejiang University, failed English, and was reassigned to Shanghai University.
Wang Xingxing has extremely strong hands-on abilities. In elementary school, he tinkered with a small wind-powered car. In junior high, he handmade a miniature turbojet engine. At the age of ten, he saw Boston Dynamics' robot for the first time on TV, a four-legged metal thing taking steps. At that time, no one knew that many years later, his robots would take the same stage.
In 2009, he was admitted to Zhejiang University of Technology, majoring in mechatronics. He said that he felt inferior because it was just an ordinary university. During his university years, he became interested in artificial intelligence and neural networks, turning everything he learned in textbooks into reality.
He enjoys eating alone because he believes eating with others is a waste of time. He doesn't read biographies or much science fiction. Many tech professionals use science fiction as a prophecy, but he doesn't. He reads "The Feynman Lectures on Physics," a book that directly discusses how the world operates. The author's quote on the book's title page says, "What I cannot create, I do not understand." In his spare time, he loves watching anime.
Until just over a year ago, his phone number was still publicly available online. When asked about socializing, his response was straightforward: "I don't like socializing; it's meaningless."
In one interview, he talked about himself.
When he was young, he thought he was somewhat clever, but he rarely received attention or recognition and often felt suppressed. For a long time, his inner self was in constant struggle, always looking for a way out and an opportunity, wanting to "break out of the cocoon."
He said that the world didn't give him many real opportunities.
Pausing for a moment, he added:
"But it's okay; I'm having a lot of fun."
$200
During his freshman year winter break, Wang Xingxing created his first humanoid robot in life. The cost was $200.
A handmade robot. With two legs, it could take a few steps, that's all. After completion, he was not satisfied. In his own words, "It was far from what I expected." At that time, the global humanoid robot control technology was not ideal, and the performance was not there to see the possibility of robots replacing humans in work. He temporarily set aside this obsession.
The machine itself, he did not let go.
While pursuing his master's degree, he joined the research group of Jia Wenchuan at Shanghai University. Jia Wenchuan had just taken charge of a National Natural Science Foundation youth project, and the topic sounded like something out of a science fiction novel: using a non-invasive brain-machine interface to control the high-performance motion of a quadruped robot.
With limited project funding and a shortage of manpower, after the postgraduate entrance exam, the two met for the first time. Wang Xingxing showcased several mechatronics projects he had worked on during his undergraduate years and discussed his views on robots. His GPA was not high, and he did not have any noteworthy award certificates. However, Jia Wenchuan still nodded and let him join the group.
"His presentation and expression were a bit nervous, but very sincere," later recalled Jia Wenchuan.
After joining the team, Wang Xingxing almost always sat in front of the lab bench, even on holidays. He put a blue icon of a little dog on the lab bench, which was the name he gave to the robot he was going to build - XDog, an infinitely possible robot dog.
He didn't use the expensive hydraulic drive like Boston Dynamics, but chose an electric motor drive, the cheapest option. The entire robot, the research and development cost only amounted to twenty to thirty thousand yuan. In fact, he had thought of this solution when he had just started his postgraduate studies, and even considered dropping out to start a business like Bill Gates and Steve Jobs. It was just a thought back then, without even a developed plan.
In 2015, XDog participated in a competition in Shanghai and won the second prize, with a prize of 80,000 yuan. This was the first time in his life that he exchanged something he created for money.
"The first pot of gold." That's how he later referred to it.
A journalist who reported on the competition that year captured his small, equipment-packed lab with a camera, with the caption "Compared to the research environment of Google and MIT and the financial support of millions or even tens of millions of dollars, the difference is huge." Google supports Boston Dynamics with billions of dollars. Wang Xingxing's dog was pieced together bit by bit with parts worth only a few thousand yuan and countless nights in front of the lab bench.
Jia Wenchuan always remembered two moments. One was when XDog was featured in the IEEE Spectrum after, this student who almost never showed weakness said:
"Teacher Jia, I really have done my best."
The other was his later casual remark, "Those top university people are not much better."
As it turned out, the robot dog developed by Wang Xingxing was even better than what top professors in overseas labs had done.
There was once a question on Zhihu: "How do you view the XDog made by Wang Xingxing of Shanghai University?" Wang Xingxing himself replied underneath: "I am quite lucky." After a while, he added, "I am really lucky."
After graduating with a master's degree, he went to Shenzhen and joined DJI. Two months later, he resigned. In 2016, he founded Universe Robotics. All the chips were XDog, plus 2 million yuan from an angel investor. Calculated based on this amount, Universe's valuation at that time was 13.33 million yuan.
"In 2016 when we just started the business, the robotics industry was very niche, which is completely different from now. At that time, Universe Robotics was only valued at just over 10 million yuan, and we raised 2 million yuan. This amount of money was almost spent over a year and a half, and in the end, we could barely pay salaries. But by 2018, when we started shipping officially, fundraising became somewhat smoother."
During the early days of the startup, an investor asked him, "What's the use of a robotic dog?"
He responded, "First, build the product, and research institutions will definitely buy it."
When unable to explain clearly, just create the thing first. For Wang Xingxing, the product needed real-world validation, and an individual's thinking also needed to be evaluated through specific problems.
According to Elsewhere's compilation, Yushu in its early days had a set of unusual interview questions. Every applicant had to answer 12 questions in writing, including the receptionist. The questions included: Over the past few hundred years, significant technological advancements in human history have mostly originated from the West. What do you think is the reason for this? How do you view and evaluate traditional Chinese medicine? And finally, there was a picture puzzle of "spot the difference."
The questions were personally set by Wang Xingxing. There were no standard answers. He validated the product with the market and also used these questions to assess the people who were about to join him in creating the product.
Sleeper Berth
In 2018, Yushu found itself on the edge of a cliff.
With early-stage funding running out and the next planned investment facing complications, the company had less than two hundred thousand yuan left in its account. Wang Xingxing stopped his own salary, used his savings, and maintained the staff's salaries. The technical roadmap remained unchanged.
That year, DJI briefly entered the scene. Two years after leaving DJI to start his own business, his former employer acquired around 10.1286 million yuan to buy approximately 17% of Yushu, becoming the largest external shareholder at the time. The following year, DJI reduced its stake and exited.
Also during this phase, Variant Capital, under Geek Park, provided Yushu with its first institutional investment of 2 million yuan.
A year later, Sequoia Capital came knocking. Li Yannan, a seed fund analyst at Sequoia China, heard about Yushu from his senior fellow alumnus at Zhejiang University. He visited the Yushu website but only found a QQ email address. By tracing back through the email, he found a WeChat ID and sent a friend request. Three days later, he made his first visit.
A month later, Yushu was presented to Sequoia's investment committee. Prior to the investment decision meeting, Wang Xingxing voluntarily suggested bringing a robotic dog to Beijing for an on-site demonstration — A1, with four legs, fitting into a 20-inch suitcase. The battery was oversized, unable to board a flight or a high-speed train. He endured over ten hours on a sleeper berth from Hangzhou to Beijing. After the demonstration, he returned via a sleeper berth.
Before setting off, he asked Li Yannan, "Is it okay to bring a little dog over?"
The day before the investment decision meeting, he wrote on his Moments (social media), feeling that he couldn't continue with the entrepreneurship journey; if it didn't work out, he would go back to Shenzhen to work.
The next day, he stood in the conference room. He presented the product, answered questions, and did not look like a person ready to give up from start to finish. Partner Cao Xi gave him a score of 8, the highest among the audience. According to Sequoia's rule, a score of 8 means a definite investment. The investment memo still contained a sentence: "Really like this person."
Later, Li Yannan found that whenever there was an opportunity to showcase the product, Wang Xingxing was very enthusiastic. For several years in a row, he took the initiative to suggest bringing the robot dog to the Sequoia CEO Summit and LP Conference. One year, when there was no booth on-site, he waited outside the venue with the dog.
On the day of the investment decision meeting, he also expressed a wish. He wanted to create a robot larger than Ultraman, even bigger than a mountain. He hoped that one day, robots could manufacture robots.
At that time, no one knew where these imaginations would lead. In December 2019, Sequoia subscribed for 15 million yuan for about 10% of the shares of Yushu. The company survived.
Spring Festival Yangko Dance
Yushu's first commercialized robot dog is called Laikago, the Laika dog.
Laika was the dog sent into space by the Soviet Union in 1957, the first living being to orbit the Earth. A stray dog from the streets of Moscow, it was captured, trained, stuffed into a satellite, and launched. Hours later, it died in the overheated spacecraft.
Wang Xingxing gave this name to his robot dog, "Space Dog," symbolizing humanity's aspiration to explore the unknown. The real dog never came back. The dog he created fell time and time again, was helped up, reprogrammed, and ran again.
In 2017, a journalist from The Paper ran to Hangzhou Binjiang to interview him. 27-year-old Wang Xingxing stood in front of the camera, looking a bit shy and at a loss. He was originally wearing a hoodie and sneakers, but to show respect for the camera, he temporarily put on a shirt he had bought online and had not opened for a long time.
The journalist asked him: Given the opportunity to work at Boston Dynamics or start his own business, how would you choose?
He smiled, "I wouldn't have this dilemma because my English is poor, and it may not be easy for me to go abroad, so this situation won't happen, and I don't need to consider this issue."
Laikago weighs 22 kilograms, with a peak power of 18 kilowatts, and a power density higher than that of a typical supercar. Its four legs can fold up and fit into a suitcase.
In 2020, Yushu had a total of 18 employees, with seventy percent in technical positions. The customer list is divided into two columns: 30 domestic companies, mostly university and research institute labs; and 12 overseas companies, including Google, Nvidia, Apple, and the father of Android, Andy Rubin.
In 2019, UTree's annual revenue was $11.83 million, with a net profit margin of 26.5%. At that time, Boston Dynamics' similar products were available for monthly rent at nearly $10,000. UTree's Laika robot dog was sold for about $20,000 to $30,000 RMB.
Next was the Spring Festival Gala.
In 2025, robots performed a yangko dance. The program, titled "YANGKO BOT," was directed by Zhang Yimou. 16 units of H1, UTree's first full-size humanoid robot with two legs, dressed in a red floral padded jacket, performed handkerchief-twirling moves alongside 16 dancers from Xinjiang Arts College, engaging in a man-machine dance.
The idea for the floral padded jacket came from Zhang Yimou. For the performance effect, the team removed all the robot's outer shells, exposing the mechanical skeleton, and then covered it with the padded jacket, a process called "losing weight." They were given a stage name, "Fu Xi," a homophone for Fuxi.
The rehearsal took nearly three months. The night the program aired, the "dancing robot" became one of the hottest topics in China. Handkerchiefs were tossed in the air, spinning, falling, and being caught again. From the audience's perspective, it looked like a group of red butterflies swirling around. Prior to this, there had never been such a large-scale AI-driven cluster of humanoid robots on live television.
Going back four years, UTree's robots had appeared on the Spring Festival Gala once before. At that time, they were four-legged robotic cows named "Ben Ben," performing "Rise of the Cows" with Andy Lau and Wang Yibo. That robotic cow was based on model A1, the same model as the dog that was packed into a 20-inch suitcase and sent to Beijing in 2019.
On New Year's Eve 2026, the scene changed. The model was upgraded to H2, standing at 1.82 meters tall, silver-gray all over, facing a row of students from Ta Gou Wushu School, engaging in a man-machine fight with perfectly synchronized movements.
During a halfway point in the Drunken Fist performance, one robot fell to the ground, sparking online discussions. Wang Xingxing came out to explain that the fall was scripted as part of the performance.
After the release of G1, a video started circulating. A robot jumped high into the air, had its legs swept by a person, stumbled, and then regained its balance. Zhao Zihao, an engineer involved in the development of Mobile ALOHA, warned his peers on his own page, "Silicon Valley can continue to believe it is the best in software and artificial intelligence until a Chinese hardware startup achieves the best AI-driven motion control on mass-producible humanoid robots."
The robots became increasingly powerful. In early 2026, a training video of H2 showed the robot performing a mid-air sidekick, shattering a hanging watermelon with a single kick. In the footage, Wang Xingxing, standing nearby, instinctively stepped back to avoid it.
Outside the frame, the advancement of robots has left its mark in another way.
The training ground for USC's robotic dog is on the rooftop. The robotic dog climbs the stairs from the office every day. With repeated climbs and falls, the edges of the steps on those few floors of stairs have been stepped on and pieces are missing. While the debris is cleaned up, the stairs have not been renovated and are simply swept clean and used again.
USC has an internal requirement: R&D colleagues must write documents and manuals that can be understood by at least a college freshman; for consumer products, they must be user-friendly for middle-aged and elderly users to pick up directly. Wang Xingxing criticizes many engineers' writing as "not for ordinary people."
Over the years, the price of robots has been continuously decreasing. The robotic dog is now sold for just over 9,000 yuan. The humanoid robot G1 has dropped to 99,000 yuan. The R1 has dropped even further to 39,900 yuan. Some call him the "Price Butcher."
He doesn't quite like this label, saying, "Actually, I don't think we have reached the level of a 'butcher'."
In July 2026, Wang Xingxing appeared on the cover of Time magazine. The cover headline had a few big words, "The Era of Robots is Coming."
In the image, the manned mech GD01 created by him is nearly 2.7 meters tall, almost filling the entire page. He stands on the right side of the mech, thin, wearing glasses, his figure resembling a footnote. The idea for this mech partly came from a movie he watched in his youth, and he admits he referenced the machine in "Avatar." Initially, he even thought about building a larger robot to compete in boxing matches.
Time described him as slim, wearing glasses, without the ostentatious arrogance of many tech founders; when discussing robotic technology, he exudes a quiet yet firm belief.
The last Chinese entrepreneur to appear on the cover of this magazine was Li Yanhong eight years ago.
Trending
During the private enterprise symposium, he was the only post-90s entrepreneur among the speakers.
The list of shareholders is getting longer: Meituan, Xiaomi, Tencent, Alibaba, ByteDance. Sequoia Capital, Matrix Partners, Innovation Works. On the list of strategic placements is DeepSeek.
Li Feng offered 180 million yuan for the new shares, with a first-day gain of over 1.1 billion. Lei Jun made 15.2 billion. Meituan's affiliated companies gained 33.3 billion.
If DJI hadn't exited that year, that stake would be worth 25 billion. The earliest angel investor, Yin Fangming, who gave 2 million initially, still has 280 million left at the issue price, an increase of about 140 times.
Foreign dignitaries also came. German Chancellor Merkel brought 30 German business leaders to visit, watched the same New Year's Eve Gala featuring the "Wu BOT." Several months later, Burmese President Min Aung Hlaing made his final stop of the China visit at Yushu. In the exhibition hall, a robot picked up a brush and wrote a calligraphy piece, while Wang Xingxing stood beside explaining.
Machines have also begun to enter the lives of investors. Sequoia's Cao Xi placed two Yushu products at the office entrance, one being the receptionist G1 wearing a Monolith uniform and a tie, and the other being the robotic cow "Cow Benben," a gift from Wang Xingxing after the 2021 Spring Festival Gala. Jia Zhu from photosynthesis venture ordered an R1 and waited for nearly half a year. On the day of its arrival, the person and the machine shook hands. In the spring of 2025, G1 and the Snow King from Milk Tea Ice City stood together at the Meituan Dragon Ball investor conference to welcome guests.
People lined up to see Wang Xingxing. He said:
"It's too hot, too hot. So many people have come, I can't even reply to all the messages."
In an interview with TIME, when asked about the other side of his fame, he replied:
"Because the hype has been too intense, it has brought considerable pressure to the company and the entire industry. Everyone expects your technology to make a leap at an extremely fast pace. But the reality is, breakthroughs in hardcore technology take time."
Six Hours
On the day of the IPO online roadshow, in less than 2 minutes, over 20 questions flooded into the interactive area. For three hours, the questions kept coming.
Someone asked, what if someone pumps up your stock price, how will the company deal with it?
Someone compared them to Tesla's Optimus and asked about the strategic differences.
Someone said "the robot looks handsome," and he replied, "Thank you for the compliment."
Someone applied for a job online, asking if the company's logo needed to be redesigned.
In the live broadcast, he seemed a bit nervous. Like during the entrance exams many years ago. The opening speech was very short, less than five minutes.
Three hours passed. The roadshow ended. Wang Xingxing didn't leave.
He carefully read through each unanswered question, considered his words, and then responded word by word. He stayed for nearly three more hours.
This was the longest output in his life.
He said, "I hope investors buy our stock because they believe in the company's value, not for speculation."
He also said that the embodied intelligence industry is still in the early stages of development, similar to the early days of home computers.
August 19, 2026, STAR Market. Yushu's market value at the time of issuance was 61 billion yuan. The issuance price was 150.8 yuan. The P/E ratio was 219 times. It opened with a 629% gain.
With just one sign-up, he earned 470,000 yuan.
Wang Xingxing's net worth exceeded 130 billion yuan.
He likened the IPO to taking the college entrance examination. A person who has only passed high school English three times is about to enter the exam room again. During the preparation days, he was not only coordinating with investors and regulatory agencies but also developing new products. His way of reviewing is still the same, creating things.
In an interview on the eve of the IPO, when asked what he saw now.
"At least I see the 'light of dawn' right in front of me."
In February 1988, physicist Feynman passed away at the California Institute of Technology. On the blackboard in his office, there was a line written in chalk:
What I cannot create, I do not understand.
What I cannot create, I do not understand.
In a kindergarten in Yuyao, a child finished drawing a butterfly and held up the drawing for the teacher to see. The drawing was right there for everyone to see.
On the laboratory table in college, he placed the robot in front of everyone and made it walk two steps by itself.
And it walked.
Later, it learned to run, jump, go up and down stairs. It could also write calligraphy, do somersaults, and perform Drunken Fist kung fu.
It fell down, but then stood up again.
Original Article Link

TL;DR
Goldman Sachs maintains a "Buy" rating on Broadcom with a $525 price target, representing about 34% upside from the report's referenced stock price of $392.43.
Goldman Sachs expects Broadcom's FY27 AI semiconductor revenue to reach $133 billion, more than double FY26, and about 12% higher than the market consensus.
Custom ASICs and data center network chips form Broadcom's core moat, but competitors such as MediaTek and AMD are increasing uncertainty in gaining customer share.
The $133 billion revenue forecast is heavily reliant on cloud customer capital expenditure and deployment acceleration, but the report does not break down the specific contributions of shipments, pricing, and new customers.
The $525 price target is based on a 30x normalized EPS, but the report does not disclose the exact normalization EPS calculation, which cannot directly correspond to adjusted EPS in financial forecasts.
AI spending slowdown, ASIC share loss, non-AI chip inventory adjustments, and VMware competition are the key risks to this high valuation thesis.
In a performance preview report released on August 18, Goldman Sachs maintained a "Buy" rating on Broadcom (NASDAQ: AVGO) with a 12-month target price of $525. With the referenced stock price at $392.43 in the report, this implies a potential upside of about 34%.
Goldman Sachs anticipates that Broadcom's next quarter performance may exceed expectations, although its AI semiconductor revenue is still in an accelerating phase. Broadcom's FY27 AI semiconductor revenue is projected to reach $133 billion, more than double the approximately $57 billion in FY26 and about 12% higher than market consensus expectations.
However, as MediaTek, AMD, and other companies intensify their entry into the custom ASIC market, the key to Broadcom's valuation sustainability has shifted from whether AI demand is growing to whether the company can retain key customers and project share.
AI Revenue Outlook at $133 Billion, Goldman Sachs More Bullish Than Market
Goldman Sachs forecasts that Broadcom's FY26 AI semiconductor revenue was about $57 billion, and it will further rise to $133 billion in FY27, representing an increase of over 130%. In comparison, the market's FY27 estimate is around $118.8 billion, with Goldman Sachs surpassing by approximately $14.2 billion.
This indicates that Goldman Sachs is not only optimistic about continued AI capital expenditure growth but is also betting on large cloud customers' custom chips and data center network deployment speed surpassing market expectations.
Broadcom's role in AI infrastructure is mainly divided into two parts: first, providing custom ASICs for hyperscale cloud customers, which are dedicated chips designed for specific computing tasks; second, providing high-speed network connectivity for large AI clusters through products like Tomahawk. As cluster sizes grow, both the computing chips and network equipment need to be upgraded simultaneously, allowing Broadcom to benefit from both the expansion of computing power and network upgrades.
Goldman Sachs believes that Tomahawk 6 is entering a volume ramp cycle and is expected to become another growth driver beyond AI revenue. Compared to only offering a single chip product, Broadcom's product portfolio covering computing, switching, and interconnectivity has also strengthened its competitive position in large data center projects.
However, $133 billion is still a rather aggressive forecast. The report does not further break down how much of the revenue growth comes from increased shipments, price improvements, or customer expansion but primarily attributes the growth to customer capital expenditure and deployment progress. Therefore, this number is first and foremost Goldman Sachs' assessment of the pace of demand fulfillment and not an official revenue guidance from Broadcom's management.
Goldman Sachs' comparison of AI semiconductor revenue versus market expectations. Goldman Sachs's forecasts for Broadcom's FY26 and FY27 AI semiconductor revenue are about 1% and 12% higher than market consensus, reflecting its more optimistic view on cloud customer capital expenditure and deployment speed. The related figures are all analyst forecasts and not company guidance.
MediaTek and AMD Enter, Customer Share Becomes the Biggest Suspense
The main controversy Broadcom faces comes from custom ASIC competition.
As cloud providers continue to increase their AI investments, the custom chip market is attracting more participants. In the report, Goldman Sachs discussed the competition pressure that MediaTek and AMD could bring, with market concerns that these manufacturers would participate in new-generation ASIC projects for hyperscale cloud customers, potentially affecting Broadcom's orders and market share.
Goldman Sachs believes that some of these concerns are already reflected in the stock price, but the competitive risks have not been fully validated yet.
Custom ASICs, unlike standardized chips, require suppliers to be deeply involved in customers' architecture design, chip development, validation, and mass production. The longer project cycles and higher migration costs provide barriers for Broadcom; however, cloud providers also have an incentive to introduce a second supplier to lower costs, enhance bargaining power, and diversify the supply chain's risk.
Therefore, MediaTek or AMD announcing entry into the market does not immediately mean that Broadcom's revenue will be impacted. What truly needs to be observed is whether the competitors can pass customer validation, secure mass production projects, and ultimately translate these into actual revenue.
For Broadcom, whether FY27 AI revenue can meet Goldman Sachs' forecast depends on both the continued expansion of the overall market and how much market share the company can capture. If AI infrastructure investment grows but major customers begin to diversify their orders, Broadcom's revenue may still fall below Goldman Sachs' optimistic forecast.
AI Semiconductor Becomes the Absolute Main Driver, Software Ensures Stable Cash Flow
In addition to AI chips, infrastructure software remains a key pillar of Broadcom's performance.
Goldman Sachs expects Broadcom's infrastructure software revenue to increase from around $32.1 billion in FY26 to around $35 billion in FY27. Compared to the more than doubling growth rate of AI semiconductor revenue, the growth of the software business is relatively moderate but can provide more stable revenue, profit, and cash flow.
This structure enables Broadcom to have a two-tier growth structure: AI semiconductors are responsible for driving revenue and profit growth, while infrastructure software is responsible for mitigating the impact of the traditional chip cycle on overall performance.
Goldman Sachs predicts that Broadcom's total revenue will rise from $107.2 billion in FY26 to $187 billion in FY27; during the same period, the proportion of AI semiconductor revenue will increase from around 53% to about 71%. The adjusted EPS is expected to increase from $11.95 to $21.40.
If this forecast materializes, Broadcom will further transition from a diversified semiconductor and software company to a company highly driven by AI infrastructure investment. This can bring higher growth but also means that its revenue, profit, and valuation will increasingly rely on the capital expenditures and deployment pace of a few large customers.
Broadcom Financial Forecast Table. Goldman Sachs expects Broadcom's total revenue to increase from $107.2 billion in FY26 to $187 billion in FY27, with a significant increase in the proportion of AI semiconductor revenue; at the same time, the adjusted EPS is expected to rise from $11.95 to $21.40. All data are Goldman Sachs' forecasts.
What Does a 30x Valuation Bet On?
Goldman Sachs has given Broadcom a $525 price target, based on a valuation of 30 times normalized earnings per share of $17.5.
The calculation itself can be directly recalculated, but the report did not specify which adjustment items are included in the $17.5 normalized EPS, and which specific forecast period it corresponds to. This number falls between the FY26 adjusted EPS forecast of $11.95 and the FY27 forecast of $21.40, so it cannot be directly equated to any EPS data in the financial forecast table.
This also means that simply multiplying the FY27 adjusted EPS by 30 and then assessing whether the $525 target price is conservative is not possible. Both the selection of normalized EPS and the 30x valuation multiple are part of Goldman Sachs' analyst judgment, not Broadcom's guidance.
The 30x valuation reflects the market's AI growth premium for Broadcom and also implies two key assumptions: that AI semiconductor revenue can sustain rapid growth and that the company's competitive position in the custom ASIC market will not significantly deteriorate.
If there are customer deployment delays or if Broadcom loses project share, the impact may be felt on two fronts simultaneously: on one hand, revenue and EPS forecasts will be cut, and on the other hand, the valuation multiple given to the AI business may also contract.
Goldman Sachs has identified key downside risks, including a slowdown in AI infrastructure spending, loss of ASIC market share, non-AI semiconductor inventory adjustments, and intensified competition in the infrastructure software market. However, the report does not quantify the likelihood of these risks occurring or their potential impact.
Looking at the target price history, Goldman Sachs has raised Broadcom's target price multiple times since 2024. Following the company's stock split adjustment, the target price has gradually increased from $240 in December 2024 to $525 in June 2026. It is worth noting that the $525 target price is not a new upward revision in this report but has been maintained by Goldman Sachs since June 4.
Goldman Sachs' history of target price adjustments for Broadcom. Goldman Sachs has raised Broadcom's target price multiple times in recent years, reflecting continuous growth expectations in AI revenue and profitability; the latest $525 target price has remained unchanged since June 4, 2026.
Going forward, what investors most need to focus on is not whether AI demand remains strong, but how much of this demand can ultimately translate into Broadcom's orders and revenue.
Goldman Sachs' forecast for FY27 AI semiconductor revenue is 12% above the market average, leaving room for further upside in Broadcom's stock price and raising the bar for performance realization. Customer deployment progress, custom ASIC share, and competitors' actual production capacity will collectively determine whether the $133 billion revenue forecast and $525 target price can be achieved.

On August 19, Yushu Technology (688836.SH) officially listed on the SSE Star Market. As the A-share "first humanoid robot stock" moved from concept to reality, the opening price at listing was ¥1100, a 629.44% increase from the ¥150.80 issuance price. This surge far exceeded the average first-day gain of 466.61% for new Star Market listings this year, and at one point, its market value soared to ¥445 billion. This year's A-share wealth creation feast, which took only 73 days from the approval process, involved nearly 9.8 million subscription accounts and had an online lottery winning rate of only 0.018%. Those allocated 500 shares saw profits far surpassing previous estimates, reaching approximately ¥475,000—about 6.3 times the initial investment.