衰退 · 1703

Trump's 50% tariff hits Canada, and the Carney administration accelerates the reduction of economic dependence on the US

Comparatively, US President Trump's 50% tariff on some Canadian goods came into effect this week, once again intensifying trade tension between the US and Canada, pushing the Canadian government to speed up the search for alternative markets, expand domestic trade, and promote large-scale infrastructure projects to reduce dependence on the US economy. Currently, about 70% of Canada's exports go to the US, and the economies of the two countries are highly tied. The tariff measures previously imposed by the United States on the automobile, steel, aluminum, and timber sectors have put pressure on the Canadian manufacturing industry, leading to some job losses and a slowdown in economic growth. Canada's economy even contracted for two consecutive quarters this year, falling into a technical recession. The latest round of 50% tariffs involves about 20 billion US dollars of Canadian exports to the US, accounting for about 5.5% of Canada's total exports to the US, covering products such as hockey sticks and cement. Canadian Prime Minister Mark Carney said that Canada will take equal tariff countermeasures to protect domestic enterprises and employment. The market is concerned that Trump previously refused to renew the US-Mexico-Canada Agreement (USMCA) exemption arrangement, bringing the trade agreement into the annual review stage. Analysts believe that the removal of some trade protections by the US may lay the risk of further expanding tariff measures. Faced with trade pressure, the Carney administration is promoting economic diversification. In recent years, Canada has strengthened economic and trade cooperation with China, India, Saudi Arabia and European countries, and promoted the expansion of exports to non-US markets. According to the data, Canada's exports to non-US markets increased by 11% in 2025, reaching 33% at one point, the highest level in more than 40 years. Furthermore, Canada is strengthening its domestic economy, including reducing inter-provincial trade barriers, promoting port expansion, developing critical mineral resources, and supporting energy infrastructure construction. The government plans to invest 115 billion Canadian dollars (about 83 billion US dollars) in infrastructure funds over the next few years, and a defense budget of 82 billion Canadian dollars.

10h ago

US Stock Value Investing Is Heading Into Another Trap

Source: Shenchao TechFlow Original title: (Opinion: Value investing in US stocks is not equal to fundamental investment) When “fundamentals are dead” becomes a consensus, investors who blindly organize giants will eventually experience astonishing capital destruction. Guide: When the market shouted “fundamentals are dead” and the capital frenzy formed a group of tech giants, the author used an astronomy discovery to unravel the logical loopholes behind this narrative. Starting from the composition of valuation multiples, this article reminds investors to distinguish between the true quality of an enterprise and the premium that the market is willing to pay. It is particularly cautionary about long-term allocation in the crypto and technology sector. I promise this introduction won't be as long as the last one on the weather. But please give me 90 seconds. More than 100 years ago, a woman named Henrietta Levitt was doing the tedious job of measuring the brightness of thousands of stars on photographic negatives (the way they were imaged before film appeared). She noticed one characteristic of a class of pulsating stars: the slower they pulsate, the brighter they themselves are. ¹ This might just seem a little interesting today, like “OK, that's pretty cool.” But at the time, astronomers couldn't tell the difference between a dark star very close to Earth and a very bright star far away. For them, the two left the same stain on the photographic film. Visual brightness is a messy mix of these two variables: how bright the thing itself is, and how far away it is from us. Henrietta's work decouples these two things: if you can observe the rate of pulsation, you can know its true luminosity; if you know its true luminosity, you can reverse the distance based on how dark it looks. Astronomers call it “standard candlelight.” A few years later, a man named Edwin Hubble discovered one of these pulsating stars, applied Levitt's math, and discovered what he had always thought was a cloud of gas within our galaxy; in fact, it was an entire independent galaxy, one million light years away. So in simple terms, the observable universe has grown about a trillion times larger, just because one person has figured out how to tell the difference between what things look like and what they actually look like. That in itself is obviously pretty cool. But another interesting thing is that around the same time period, two other astronomers each independently drew a scatterplot. One axis was actual luminosity, and the other axis was temperature. They discovered that stars are not randomly distributed in this space, but rather clustered into different families. The meaning behind this is: stars with the exact same visual brightness may and do belong to a completely different family, have a completely different past, and most importantly, have a completely different future... So what is written in the star? Over the past few years, there has been much discussion about markets, narratives, capital, company building, and financial nihilism. This feeling seems to have reached a feverish climax as the tech and financial world begins to face a very different future than a few decades ago. What is particularly clear is that separating progress from asset prices has become more noisy and in many ways more repulsive. But as an investor who makes a living by buying assets that (hopefully) outperform, a simple framework is: forward returns are roughly equal to growth in fundamentals multiplied by changes in valuation multiples (and multiplied by the dividends you've collected along the way). In this case, the valuation multiplier can very cleanly correspond to the smudges on the photographic film. It's an observable data point, but it entangles two things that the market can't directly see: how good the company actually is, and how far (or how long) its future cash flow is now. I think most of the money that can be made comes from investors who are most capable of unraveling these two variables earlier than others (or “perception of differences”), and we will continue to see astonishing capital ruin for investors who treat their stains as stars. Value investing is not equal to fundamental investing. I think there is a misunderstood view: fundamental investing has historically dominated the creation of excess returns. Most of these legends come from the Graham, Buffett, and Tiger Foundation lineage, as well as numerous narratives built around this group of people. It is believed that by some point in the 2000s, this approach was no longer effective, and anyone who invested in this way was overwhelmed by momentum, trends, and “direct buying tech giants.” The conclusion was (and still is?) It's “fundamentals are dead.” ² The modern version of “fundamentals don't matter” itself isn't stupid. It's rooted in a lot of ideas that many of us on the Compound team have written before. The biggest companies get the most mechanical purchases, and the software industry has a winner-take-all economic law. AI means that giants can transform scale into moats faster than challengers, and there are also reasons why the market's microstructure embeds momentum more deeply into our market infrastructure. These are all real...

1d ago深潮TechFlow#US stocks

Millions of dollars are rushing into the market, but some are in a hurry to exit: Pharos's high-interest treasury causes a “view of time” collision

Article: Sanqing, Foresight NewsSharos Network joined forces with Vault infrastructure agreement R25 and credit asset management agency Axil to launch Axil Prime Credit Vault (APC), an institutional consumer credit RWA wealth management product issued by Pharos on July 15. The products were launched simultaneously with Binance Wallet, TopNod, OKX Wallet, Bitget Wallet, and KuCoin Wallet, with a total fundraising limit of 100 million USDC, with a target annualization of about 14.3%. As of the closing of the deposit window, a total of $45.39 million had been deposited. This year, there have been frequent security explosions in Web3 on-chain strategies. User funds are looking for new stable income sources, and project parties are also there. Binance Wallet is now offering an additional $300,000 PROS as an incentive to explore RWA Vault's market space, causing the Vault to generate a lot of discussion in the market. The launch time coincided with the redemption period of the Pharos TGE pre-deposit campaign. The previous treasury required the submission of a redemption application about half a month before the end of the lockdown period, stop accruing interest on July 20, and complete the redemption within 7 days. Users accustomed to DeFi T+0 looked back and found that they couldn't help but missed the redemption period and began to question the redemption time and asset safety. R25 and Axil then held an AMA at Binance Square. Well-known KOLs such as Haotian and Tianqing participated in discussions, detailing the differences between RWA assets and DeFi Vault, the role of fund managers (Curators), why consumer credit is worth allocating, and risk management methods from pre-investment to post-investment. In complex asset logic and mixed social media discussions, some users put in one million funds on the last day, while others sought early redemptions from the project party. On July 23, Pharos issued an announcement: Users who submitted applications on time in the previous issue have received all principal and interest, breaking the “financial security” concerns; funds that missed the window will automatically be carried forward to the next three-month cycle according to the treasury's preset rules, and interest will continue to be accrued at 14% USDC per annum. The controversy revealed more important issues than the redemption itself. Although the RWA TVL has exceeded $38 billion, non-institutional chain users are clearly dissatisfied when investing in RWA products. Institution-driven, stable, and high interest rates, but often require longer lockdown periods and complex understanding costs. From DeFi to RWA, is the market really ready? High yield, low threshold, and high liquidity. BlackRock's “impossible triangle” of RWA's BUIDL threshold is $5 million. It is only open to qualified buyers, yet it can be redeemed almost instantly through the stablecoin channel; the APC threshold is so low that ordinary users can buy it at will; instead, it must be locked for three months. Liquidity has never been determined by how high or low the threshold is, but rather how quickly the underlying assets can be realized. The bottom layer of BUIDL is US treasury bonds, and the world's deepest secondary market can take over at any time; the bottom layer of APC is hundreds of thousands of emerging market consumer loans, and few people are ready to buy large amounts of capital at any time. This has formed a triangle that RWA cannot bypass at this stage: high yield, low threshold, and high liquidity; the three can only take two. For example, Franklin Templeton's BENJI starts at $20 (low threshold) and supports daily redemption (high liquidity), and the annualization is only 3% to 5%; if you want double-digit returns, you have to accept non-standard assets and a lock-up period. This is the liquidity premium. A significant portion of the excess income is the consideration for abandoning liquidity. APC, on the other hand, is a combination of high returns and a low threshold, and the cost is liquidity. There is nothing wrong with this trade-off itself; it also explains the full source of this controversy. Retail investors have obtained assets that were originally only open to institutions, and they have also taken over the agency's time rules that focus on long-term matching. The period of use of institutional funds is scheduled before investment, and the lockdown period is a predictable cost; private equity credit and closed-end funds already have redemption restrictions. However, most ordinary users on the chain are not the same; most of the latter's first appeal is to go in and out. So the current “retail” RWA is mostly just distribution-side retailing, to be precise. Web3 wallets and low initial investment amounts have contributed to a low threshold, but the liquidity structure is still designed according to institutional logic. Having understood this triangle, the remaining questions became specific: why must the liquidity side be sacrificed, a high income of 14.3%...

2d agoForesight News#WEB3

Opinion: Bitcoin may welcome a historic upward environment, and the US dollar index is in a structural decline

Comparing the news, Strive CEO Matt Cole wrote on the X platform that he has been believing that the US Dollar Index (DXY) is in a structural downward trend for more than 10 years, and it may currently be approaching a larger downward phase, which will have a significant impact on Bitcoin. If this judgment holds true, the next 5 to 7 years could be one of the most favorable macro-environments in Bitcoin's history. He pointed out that the long-term downward trend in the US dollar index since the late 1960s is not only reflected in “lower highs and lower lows” in technical form, but is also supported by US fiscal fundamentals. Matt Cole pointed out that Bitcoin's major bull markets have been accompanied by the weakening of the US dollar. During the 2017 market, the DXY fell from about 103 to 88; in the 2020-2021 cycle, the US dollar index fell from about 103 to around 89; while Bitcoin reached a record high in 2025, the US dollar also weakened from about 108. The dollar's decline has remained limited in the past few rounds, and the dollar may now be approaching a multi-year downward cycle similar to the mid-1980s and early 2000s to the global financial crisis. Its benchmark judgment is that the dollar index is likely to continue to decline for the next 3 to 7 years, even challenging the low of around 70 in 2008. Matt Cole believes that if the US dollar experiences a real long-term structural breakdown, Bitcoin will usher in a macro environment that has never been experienced before. He said that most current Bitcoin predictions in the market are still based on past performance, but Bitcoin has yet to experience continued impetus from the “long-term decline cycle of the US dollar.” At the same time, he mentioned that the US Treasury recently announced that it will at least double the scale of long-term treasury bond repurchases, while long-term US bond yields are under pressure and the US dollar weakens at the same time, which further strengthens its long-term judgment. Matt Cole concluded, “People may still not be bullish enough about Bitcoin for the next 5 to 7 years.” He believes that if the long-term trend of the US dollar, which has been formed over 45 years, finally breaks downward, Bitcoin may usher in a macroeconomic downturn that far exceeds the historical cycle.

3d ago#Market topics

Legendary investor Cooperman is betting on the US recession next year: rising inflation may hit US stock valuations hard

In comparison, billionaire investor and Omega Advisors CEO Leon Cooperman warned this week that the US economy could fall into recession within the next year and drag down the stock market. He pointed out that the current market is similar to the collapse of the Pretty 50 in the 70s of the last century, and expressed concern about cooling AI optimism. In an interview with CNBC, Cooperman said: I think we will experience a recession sometime next year, which may cause the market to fall. At the same time, he believes that the market's expectations for S&P 500 earnings growth are biased (FactSet data shows that this quarter's year-on-year increase is expected to exceed 50%). Currently, he clearly deviates from mainstream Wall Street bullish views. In particular, he avoids technology stocks, and has a negative view of the overall market. He reminded investors not to underestimate the risk of inflation rebounding. Brent crude oil remained high after the Iran war (about $90 per barrel, more than 20% higher than before the war), and retail sales fell 0.6% month-on-month in July (far lower than the 0.1% increase expected). Higher inflation or a blow to stock valuations is similar to the sharp decline in growth stocks after the rise in oil prices in the 70s. One of the most dangerous words in the field of investment is: “This time is different.” Cooperman said that the current market is almost generally bullish, and once a negative catalyst appears, investors may sell off quickly. At the same time, fluctuations in the bond market have intensified the pressure. The US 30-year Treasury yield hit 5.33% on Tuesday, the highest since June 2007, and broke through a three-year trading range. Analysts warned that if yields rise rapidly to 6%, the stock market may face further pressure on valuations. Historically, after a similar trend in 1999, the S&P 500 then adjusted and the Internet bubble burst.

3d ago

Revenue is cut! Korean crypto exchanges can't handle it anymore

Source: Shenchao TechFlow Article: Cookie Original title: Shortage of revenue from the Korean Crypto Exchange: The most profitable business can't escape the decline in liquidity, the business most like traditional finance, and is also most constrained by cycles like traditional finance. Key points: Dunamu, the parent company of Upbit and Bithumb, the two largest crypto exchanges in Korea, released financial reports for the first half of 2026 on the same day. Revenue was almost down (down about 49% year on year), but profit performance was extremely uneven: Dunamu's net profit was 108.4 billion won (down 74.1% year on year), while Bithumb had a net loss of 108.7 billion won (profit of 55 billion won in the same period last year). The main reason for the decline: The total trading volume of South Korea's licensed Korean won exchanges fell 49.5% year-on-year in the second quarter, and fee revenue declined simultaneously with the overall contraction of the market. Profit difference: Dunamu has better cost control and remains profitable; Bithumb's losses include digital asset impairment and regulatory penalties, and the operating profit margin is less than 9%. Capital flow: South Korea's retail capital is shifting from the crypto market to AI and semiconductor concept stocks (Samsung Electronics, SK Hynix), and a 22% crypto profits tax will be introduced in 2027, curbing the will to trade. IPO process: Dunamu received an investment of about 1.5 trillion won from Samsung affiliates and others, and cooperated with Naver Financial to advance the KRX listing; Bithumb plans a three-phase IPO, targeting 2028, but current financial performance is under pressure. Industry reflection: The business model, which accounts for nearly 100% of transaction fees, showed strong cyclical characteristics. The profit margin fell from 88% in 2021 to the current 14%. Exchange valuation logic faced open market torture and transformed into a key issue. South Korea's two largest crypto exchanges simultaneously handed over a nearly symmetrical recession report card. On August 14, Upbit's parent company Dunamu submitted its report for the first half of 2026 to the Korea Financial Supervisory Service (FSS) electronic disclosure system. Bithumb's semi-annual report also surfaced on the same day. Looking at the two financial reports together, it's like two perspectives on the same recession. Dunamu's consolidated revenue for the first half of the year was 408.1 billion won, down 49.1% year on year; operating profit was 111.5 billion won, down 79.7% year on year; net profit was 108.4 billion won, down 74.1% year on year. Bithumb's revenue for the first half of the year was 168.8 billion won, down 48.7% year on year; operating profit was 14.9 billion won, down 83.4% year on year; net loss was 108.7 billion won, compared to net profit 55 billion won for the same period last year. Revenue declines were almost the same, all around 49%. However, there is a huge gap on the profit side. Despite a sharp drop in profits, Dunamu still earned 108.4 billion won. Bithumb directly turned into losses, and the amount of losses even exceeded Dunamu's net profit. At the same ebb, the revenue of the two companies at different levels fell at the same time. The reason is simple: the total trading volume of the five licensed Korean won exchanges (Upbit, Bithumb, Coinone, Korbit, Gopax) in the second quarter fell 49.5% year over year to about US$146.4 billion. The overall market has shrunk in half, and handling fee revenue has naturally shrunk in half. But why is Dunamu still profitable and Bithumb losing money? The difference is revenue structure and cost control. Upbit's trading platform revenue for the first half of the year was approximately 395.5 billion won, accounting for 97% of total revenue. Bithumb has a higher percentage, and almost 100% comes from transaction fees. Both are highly dependent on transaction fees, but Dunamu has better control on the cost side. Bithumb's losses include digital asset impairment losses and administrative expenses associated with regulatory penalties. One more number explains the problem. At its peak in 2021, Dunamu left an operating profit of 88 won for every 100 won of revenue. By the second quarter of 2026, this figure became 14 won. The operating profit margin dropped from 88% to 14%. In five years, same company, same business model. Bithumb's situation is more extreme. The operating profit for the first quarter was only 2.8 billion won, and the net loss was 86.9 billion won, including significant digital asset impairment and compliance rectification expenses. Although the business level recovered in the second quarter, the first half of the year as a whole remained a net loss. Where did the money go? The decline in South Korea's crypto trading volume is directly linked to a structural shift in local capital flows. 2026...

3d ago22#Bithumb

Fireworks that came out of Meta to talk about open source and closed source. Who will win?

Author: Silicon Valley Vector Silicon Valley Coordinates Editor: Peggy, BlockBeats Original title: Silicon Valley Coordinates x Fireworks Co-Founder Benny Chen: Open Source Models, Token Growth, Inference Optimization, and Model Customization Editor's Note: In the context of open source models speeding up and approaching cutting-edge closed-source models, industry discussions are shifting from “who has the most capable model” to “who can put models into production at a lower cost”. However, when model capabilities converged and token consumption increased, a lower-level question began to emerge: are companies really willing to pay a cheaper model call, or exclusive intelligence that can perform specific tasks in a stable manner? Recently, Cao Qingyun, host of “Silicon Valley Coordinates”, had a conversation with Chen Yufei, co-founder of Fireworks AI. Located between models and enterprise applications, Fireworks mainly provides customers with open source model inference, performance optimization, and customization services. Rather than simply discussing whether open source can catch up with closed sources, Chen Yufei's observations are closer to actual workloads: where tokens flow, why companies pay, and what is still missing from the model from proof of concept to production. In this conversation, Chen Yufei disassembled “who wins between open source and closed source” into a set of lower level structural questions: can token growth be converted into revenue, can generic capabilities replace vertical accumulation, can the low price model pass corporate evaluation, and how the inference platform can gain value between cloud vendors and application companies. First, the scale of use and commercial value of the open source model are diverging. In the past, the ability to catch up and call price were the main indicators for judging the competitiveness of open source; today, the Fireworks platform processes about 40 trillion to 50 trillion tokens every day, and the actual usage of the open source model has rapidly expanded. However, free traffic, promotional subsidies, and model price differences will cause Token statistics to overestimate some demand. Customers may heavily use lower-cost models and still hand over the highest budget to the best-performing closed source model. This means that the next phase of open source is not just expanding traffic, but proving that it can meet or even surpass cutting-edge models for high-value tasks, and turn cost advantages into willingness to pay. Second, the general model and the vertical model are beginning to evolve in different directions. In the past, every time a cutting-edge model was upgraded, it was possible to directly eliminate a number of fine-tuned models; now, vertical applications such as law, medical care, and programming are accumulating more detailed evaluations, data, and workflows, and their optimization goals are gradually separated from cutting-edge laboratories. Generic models need to increase the upper limit of capabilities, while vertical models require stable delivery of results in limited scenarios. The former can solve a wider range of problems, while the latter has a better understanding of how users define “right.” This means that the barrier for vertical companies is not just having a customized model, but being able to continuously transform industry needs into an evaluation system and migrate over and over again as the basic model is updated. Third, the bottleneck in enterprise AI implementation is shifting from model supply to evaluation capabilities. In the past, enterprise proof of concept often relied on trial experience and subjective judgment; now, when AI enters production processes such as call centers, legal searches, and medical assistance, it is no longer possible to support procurement decisions simply by “looking good.” Businesses must know what tasks the model works for, when it fails, and how much the cost and quality of switching from closed source to open source changes. Assessment is therefore no longer an ancillary tool, but an infrastructure connecting procurement, training, and production deployment. Who can define tasks, establish test distributions, and continuously update standards can truly control model choices. Fourth, the value of inference platforms is shifting from “selling cheap computing power” to organizational models, hardware, and workflows. In the past, inference optimization was mainly understood to reduce the cost of a single token; now, caching, task splitting, model routing, and context management can all directly change the task completion rate. Different models don't have to compete for the same position; they can act as performers and advisors separately. Fireworks' business logic is also based on this: instead of building asset-heavy hardware, revenue is tied to actual use of customer models through training, customization, and continuous reasoning. But the main rival in this path is not a single new cloud company, but a large cloud vendor that can simultaneously control computing power, software, and customer portals. Fifth, the rise of the open source model may not reduce infrastructure requirements; on the contrary, it may reduce model layer premiums and further push value towards reasoning and computing power. Tech giants continue to increase capital spending, not just calculating short-term returns, but measuring missed AI cycles...

4d ago律动BlockBeats#AI

Bank of America chief: US debt is approaching 40 trillion US dollars. Going long on gold is the best solution right now. AI bonds have become an counterintuitive target for shorting

Comparing the news, Bank of America's chief investment strategist Michael Hartnett identified the upcoming US Treasury bond breaking through $40 trillion as the core narrative line of the current market, and expressed his views on the topic of worries beginning at 40. Interest expenses on US debt have reached 1.4 trillion US dollars in the past 12 months, and are about to surpass social security as the federal government's largest single expense, while the 30-year US bond issue hit a 25-year high with a yield of 5.126% last week. Hartnett pointed out that unless the 5-year US Treasury yield falls below 3.25%, the worsening trend in interest spending will not be reversed, and it is almost impossible for this to happen without a major deflationary shock or recession. He summed up the absurdity of reality in one sentence: US stocks hit a record high on the same day, and US bonds were issued at the highest yield in 25 years on the same day. Under an asset allocation framework that is far from bonds, away from the US dollar, and fully encumbered AI, Hartnett clearly listed going long on gold as the best solution to combat the depreciation of the US dollar, the collapse of bonds, and asset inflation. At the same time, a counterintuitive transaction was presented — shorting AI bonds. The logic is that capital expenditure of more than 1 trillion US dollars is compounded by negative free cash flow. AI companies must continue to issue bonds on a large scale for financing. This transaction will be much more profitable than going long on AI stocks. Data from Nomura Strategist confirms the pressure on the bond market: AI and data center related bond issuance has reached about 12 times the average annual level in 2015-2024, and $269 billion since the beginning of the year, which is double the full year of 2025. The positive structural influx of corporate bonds pushes the yield curve on US bonds and crowds out buyers of long-term treasury bonds. Hartnett also noticed that long-standing cold assets such as REITs, biotech, regional banks, and small-cap stocks are quietly outperforming, and the market is peaking in pricing yields. Key future market points include the Federal Reserve Chairman's speech in Jackson Hole on August 28, the September FOMC meeting, and the Bank of Japan meeting. The final judgment is that if the Republican Party holds the Senate and the Texas governor, the stock market, especially the AI sector, will rise further to the level of bubble in 2027; if the Democratic Party wins on November 3, the stock market, dollar, and bond yields will face a sharp drop of more than 10% before the end of the year.

5d ago

The Q2 earnings growth rate of US stocks far exceeded expectations, and Wall Street raised the S&P 500 year-end average target to 7894 points

Comparative news, according to Bloomberg, the second-quarter earnings of the S&P 500 index constituent stocks increased 31% year-on-year, higher than the previous 23% forecast, making it the strongest increase since Bloomberg Industry Research had data in 1992, excluding the recovery phase after a major recession. More than 90% of the S&P 500 constituents have announced financial reports, and the overall profit performance for the first half of the year is expected to be the best in the same period since 2021. Analysts believe that on the one hand, profits exceeded expectations due to the resilience of the US economy, and on the other hand, from the increase in profit margins brought about by AI. The net profit margin of the S&P 500 constituent stocks has risen to close to 16% from 14%, where it was previously difficult to break through. Nationwide's chief market strategist Mark Hackett said that AI has mainly been a cost center in the past few years, but this year it has reached an inflection point and has begun to transform into a profit center. As earnings grew faster than the index, the price-earnings ratio of the S&P 500 for the next 12 months fell from about 26 times at the beginning of the year to just under 22 times. Wall Street strategists also continued to raise their expectations. Currently, the S&P 500 target point average has risen to 7894 points at the end of the year, and there is still room for about 1% increase from the historical high set this week; the profit growth forecast for the whole year was raised from 15% to 27% at the beginning of the year. This round of profit growth is no longer limited to big tech companies. As of August 12, about three-quarters of the 1,500 US listed companies that have disclosed results have simultaneously exceeded expectations in terms of earnings per share and revenue. Healthcare was the only sector in the S&P 500 where profits contracted in the second quarter.

6d ago

Use the xRev valuation method to lurk in the next doubling market

Source: Delphi Digital Author: @that1618guy编译及整理: BitPushNews When sifting through agreements, I've been thinking about the question: If a business relies on its revenue to help you recoup all of your investment in less than 2 years, what exactly is stopping you from buying it? The answer is almost never the revenue itself, but whether you believe it's sustainable. This is what the XRev multiple (market capitalization divided by annualized revenue) really measures. It's not cheap or not, it's durable (durable). Two real-life cases illustrate this very well. The trailing multiples currently selected by PUMP and AERO are in the low single-digit range, 2.3 times and 3.5 times, respectively. Over the past 30 days, PUMP has risen 87%, while AERO has declined 14.5%. The same screening metrics, but the exact opposite results. In June of this year, the market priced PUMP 1.3 times — meaning the market doubts that the agreement won't even be able to sustain current revenue for 16 months. This doubt was dispelled in July, and the subsequent revaluation (re-rate) completed all the upward drive. AERO is like a mirror: it has tripled since its high price in December 2024, not because some people are more optimistic about it, but because its revenue is declining faster than the market is repricing. If this framework is established, then the trading logic would not be “buy the lowest multiple”, but “buy the multiple that doubt will soon disappear.” When a suspected revenue stream is proven to be durable, even if revenue is overtaken, the revaluation will take on the burden of driving the rise. What exactly does xRev measure xRev is simple: market capitalization divided by annualized revenue. At 1.0 times, the revenue from the agreement can pay back its entire market value within a year. Less than 1.0 times, the payback is faster. The most immediate instinctive interpretation of such numbers is a “pricing error.” But the correct interpretation is: the market is putting huge “durability discounts” on it. The market is telling you that it thinks this kind of revenue is just a fleeting thing, and once it falls, it will never come back. So a compressed XRev itself isn't a buying signal... it's more of a “statement of no confidence.” The alpha (excess revenue) of these is figuring out whether this distrust is right or wrong. Before entering the case study, we also need to make a distinction, because the initial multiplier position of the token determines what kind of transaction it can evolve into. We can split it into two buckets. Bucket A (Bucket A) tokens are “cheap at birth”: A new protocol found product-market matches (PMF) in areas with extremely high rates, and revenue exploded before anyone believed it would last, so XRev launched at around 1x or less. High income, small market capitalization, and great doubt. The market capitalization is low for only one reason: the market hasn't bought up its revenue story, making them candidates for “belief revaluation.” Bucket B (Bucket B) tokens are “expensive at birth”: the market has been pricing them as future revenue giants since day one, so XRev was initially very high, and the belief was already pre-paid. There are no doubts that can be purchased; only expectations need to be defended. AERO's release belongs entirely to bucket A. The release of PUMP belongs entirely to barrel B. The next sections let's take a look at what happened to each of them. PUMP: Barrel B buys PUMP at its premium is typical of barrel B. The token stemmed from a $1 billion round of financing, and the ICO gave a fully diluted valuation (FDV) of $4 billion, equivalent to more than 9 years of annualized revenue generated by the agreement at the time, and opened at 4.5 times the circulating supply. Faith has already been paid for in advance. Since then, it has taken the market a whole year to reclaim these prepaid beliefs. This was reasonable at the time: Memecoin's trading volume was cyclical, competitors were actively absorbing order flows, and no one was sure if the platform could maintain market share. You can see that the belief in prepayment is being lost from the XRev chart. While the agreement recorded gross revenue of more than $200 million for four consecutive quarters, the multiples continued to shrink for almost a full 11 months. Figure 1: XRev, 30-day revenue window since PUMP was launched. At this...

7d agoBitpushNews#pump #token #valuations