私人信贷 · 176

Franklin Templeton completes $1.5 billion CFO financing to lay out private market asset allocation

In comparison, asset management giant Franklin Templeton announced that its first mortgage fund obligation (CFO) product, Franklin Templeton Structured Solutions 2026, has successfully raised US$1.5 billion to provide investors with diversified and more efficient private equity investment channels. The asset portfolio covers strategies such as the private equity secondary market, continuing funds (continuing vehicles), and direct loans to medium-sized US enterprises. By the end of July 2026, Franklin Templeton's alternative asset management scale reached US$295 billion. Its alternative investment platforms covered various fields such as the secondary private equity market, private real estate, private credit, venture capital, hedging strategies, and digital assets. This article is sponsored by GENG, Build Your Fortune on GENG (https://geng.one)

2d agoburnking

BIS warns of the risk of an AI bubble: core company valuations are high, risk premiums are clearly compressed, and revolving financing conceals hidden dangers

Comparing news, the Bank for International Settlements (BIS) said in its annual economic report that AI optimism has supported global growth and risky assets over the past year, accelerated semiconductor procurement, data center construction, and power infrastructure investment, and kept financial conditions relaxed. But as AI investments scale up, risks are extending from stock market valuations to corporate bonds, private credit, and supply chain finance. BIS warns that the valuation of AI core companies is already high, and the market's implied long-term profit growth rate is significantly higher than historical benchmarks. At the same time, risk premiums for large US stocks have been significantly reduced, indicating that risk compensation received by investors is being reduced. If the return on AI investment falls short of expectations, or if inflation forces interest rates back up again, the stock market will face more intense revaluation pressure. BIS also specifically mentioned that lack of transparency in AI financing amplifies risk. Some chip vendors and cloud vendors form revolving financing through equity investments, long-term procurement commitments, computing power leases, and data center leaseback arrangements, and some assets may also be at risk of repeated pledges. If the equity market is drastically adjusted, corporate credit risk will be re-assessed, credit spreads may widen, and the financing environment will be further tightened.

4d ago

Federal Reserve Hamak: Unsure that inflation will continue to improve; inflation needs to be reduced to 2% faster

Comparing the news, according to Kim 10, the Federal Reserve's Hamak recently stated that inflation needs to be reduced to 2% faster. He said, “The two recent inflation reports are encouraging, but we are not sure that inflation will continue to improve in this direction. Americans are facing real pressure from inflation. In addition to inflation, we also need to focus on private credit and whether there is a bubble in artificial intelligence. There is also noise in employment data. Currently, a large amount of leverage is used to buy treasury bonds, so treasury bonds are one area where I am concerned about financial stability.”

9d ago

Jane Street is planning to transfer $11 billion in public debt to outside investors to provide flexibility for further investment in AI

Comparatively, according to the Financial Times, Jane Street is in negotiations with some investors, including Pimco, to transfer about $11 billion of debt from the open market to private instruments through a private credit deal. According to the analysis, Jane Street's debt transfer is aimed at reducing quarterly financial disclosure requirements for a large number of creditors while providing greater flexibility for the company to further invest in AI infrastructure such as data centers and related technology.

15d ago

AI data center financing differentiation: giants' loans are not affected, and project parties are beginning to bear higher costs

Author: Huohuo Original title: Can AI data centers still borrow cheap money? TL; DR · Alphabet's new round of corporate bonds attracted subscription demand of about $115 billion, and plans to raise up to $25 billion to supplement AI infrastructure construction funds. · After abandoning the €1 billion bond program, Pure DC switched to bank financing, and the pricing of data center debt is becoming more expensive. · The market disagreement is not whether AI infrastructure can be funded, but rather that financing costs and bargaining power between different borrowers are widening. · Related subjects: META, MSFT, GOOGL, AMZN, NVDA, ORCL, EQIX, DLR, data center CMBS, private credit platforms. Google's parent company Alphabet's massive bond offering attracted around $115 billion in subscription demand. Earlier market news showed that Alphabet is preparing to issue a new round of US corporate bonds. It plans to raise up to 25 billion US dollars. The bonds can be divided into up to 10 tiers, with a term of 2 to 40 years, and the final scale is yet to be determined. This funding will supplement Google's continued expansion of AI infrastructure. On almost the same line, Pure Data Centres Group abandoned the original plan to issue €1 billion bonds in July and switched to bank financing. Some data center mortgage transactions also need to increase yield in order to attract buyers to complete subscriptions. Looking at these two things together, AI infrastructure financing has not stopped, but the debt market is being stratified. Tech giants with the strongest balance sheets and clearest credit qualifications can still attract large-scale capital; while data center developers, which rely more on project cash flow and capital market windows, are beginning to face more picky bond buyers. This incident affects AI asset pricing because data centers are not built solely on technological narratives. It needs to continue to borrow money, rent land, connect electricity, and purchase equipment, and turn future rent and computing power requirements into today's financing capabilities. The current dispute is not whether AI funding will be interrupted. High-quality projects can still receive credit funds from banks, institutions, and private sources. The change is that the open market is beginning to recalculate accounts based on credit assets: who the borrower is, whether the lease is strong enough, whether electricity costs will get out of control, and whether the cash flow can cover the debt. The open bond market has not closed, but the beginning of stratified Alphabet bonds receiving approximately $115 billion in subscription demand is an important sign. It shows that as long as the issuer is strong enough and the market believes in its cash flow and solvency, AI infrastructure-related financing can still obtain a large number of purchases. But that doesn't mean all AI data center debts get the same treatment. Alphabet issues US corporate bonds, and behind them are the tech giants' own credit credentials; Pure DC is facing a data center financing environment that is closer to pricing cash flow for projects and assets. The two are part of the same AI infrastructure chain, but they are not the same kind of risk. The most immediate change is that some borrowers are still getting more expensive to borrow money. Widening interest spreads mean investors are demanding a higher additional yield than treasury bonds or benchmark interest rates. For borrowers, this is an increase in financing costs. According to Bloomberg Law July 21, Oaktree-backed Pure DC dropped the proposed €1 billion bond and switched to bank financing. The same report also mentioned that of the data center securities issued since the beginning of last year, nearly 80% of the current quoted interest spreads are higher than when they were issued. This is not a funding freeze. The buyer is still there, only the price has changed. Investors are willing to buy AI data center debt, but are unwilling to continue using previous low-risk assumptions. The Pure DC case also needs to be viewed in the context of a complete financing rhythm. The company announced in May that it had secured financing of 2.7 billion US dollars, and in July it also announced that it had obtained 1.3 billion euros of senior debt for the first phase of the Seinäjoki AI Park in Finland. It's not that it can't get money; the open bond market is no longer a frictionless export. In the past two years, AI infrastructure changed from a growth story to a credit story, and the stock market is more concerned about whether AI demand can continue, whether there are not enough chips, and whether the model will continue to expand. But for debt investors, the question is more straightforward: who will pay back the money, when, and how stable is the cash flow. Issuance such as Alphabet can attract huge subscriptions. Essentially, the market is willing to price AI infrastructure investment within the overall credit framework of large technology companies. Investors are not only buying a data center project, but the issuer's overall cash flow, assets and liabilities...

15d agoburnking#AI #financing

Arthur Hayes: The AI bubble is a credit story similar to 2008, not a profit story like 2000

Comparing news, Arthur Hayes posted an article on the X platform saying that his article “Situationship” discusses how the AI bubble will burst and why monetary easing will push BTC back to the bull market. He believes that the key variable in judging whether AI is a bubble is an internal framework issue, that is, investors should distinguish whether AI capital expenditure represents technology or real estate. Currently, the market sees trillion-dollar construction as technology and gives high growth valuation multiples, but he believes that AI capital expenditure is essentially another real estate investment; only that the computing power within the data center will create a silicon-based life form and help the development of human civilization in the most profound way since railways. Arthur Hayes said the difference between real estate and computing power is important because hedge funds, banks, private credit funds, and the final government are treating data center and power plant construction financing similar to loans to Apple rather than to the Lehman Brothers. He believes that the bursting of the AI bubble will occur when financial intermediaries overbuild data centers and related infrastructure with the tacit support of the US and Chinese governments. As a result, the AI bubble is a credit story similar to 2008, not a profit story similar to 2000.

17d ago

Analysis: Bitcoin long-term holders transferred chips on a large scale for two consecutive days, or to avoid macro risks in advance

Comparing news, analyst Murphy wrote that in the past two consecutive days, there have been transfers of more than 65,000 BTC in a single day (transfers within the same entity have been excluded), which has led to a sharp drop in long-term holders' (LTH) net holders' (LTH) positions. He pointed out that LTH net holdings changed their previous upward trend in May and remained stagnant until July, a rare phenomenon in the past year. Murphy said that nearly 14,000 BTC were transferred to exchanges. For example, Trump's listed company transferred 2,628 BTC to the Crypto.com exchange as part of this. The destination and purpose of the remaining LTH net holdings reduction is unknown. He also listed risk points that may have an impact on BTC at the current macro level, including the current 9-3 split of the Federal Reserve to cut interest rates, the Middle East conflict and oil prices, the high concentration of US stock AI sector valuations and reliance on debt and private credit financing, and the accumulation of yen arbitrage trading positions once again to a one-sided headroom close to historical extremes. At the same time, it suggests that the current sensitivity of BTC's own chip structure may amplify these risks.

19d ago

Fluid partners with AGI3, a subsidiary of Kinetic Group, and Kinetic plans to acquire up to 10% FLUID tokens

Comparing news, DeFi protocol Fluid and AGI3 Group issued a governance proposal and announced a strategic ecosystem partnership. Kinetic Group plans to acquire up to 10% of the FLUID token supply through secondary market purchases, OTC transactions, etc., and the related tokens will not come from DAO vaults or team allocations. The Fluid Foundation will provide an additional 5% of FLUID tokens to establish escrow in compliant private banks and institutional digital asset custodians in Switzerland, the European Union, Hong Kong, and Singapore. These tokens will be locked for at least four years to 2030. As part of the strategic partnership, AGI3 will grant 2% of the shares to the Fluid Foundation, also locked in for four years. AGI3 was founded by Kinetic Group, a private asset management group regulated by the Dubai Financial Services Authority (DFSA), and focuses on building complex financial infrastructure across payment, banking, capital markets and tokenization. The core product of the partnership is AGI3 Markets, a permissioned DeFi instance for institutions, equipped with KYC/AML review mechanisms to support the lending and trading of RWA assets such as tokenized private credit, treasury bonds, commodities, stocks, and corporate bonds. The parties agreed that all agreed revenue and incentive budgets generated by AGI3 Markets will be split 50/50.

29d ago

Big bear Michael Burry warned of long-term US debt, which is under multiple pressures such as a surge in AI debt and oil prices approaching $100

Comparing news, Michael Burry, the archetypal figure of the Big Bear, wrote that long-term US debt trends should be closely watched. Multiple factors are putting pressure on the US Treasury bond market, such as the rapid expansion in the size of AI-related debt, rising inflation volatility, unstable base trading conditions, and the return of oil prices to close to $100. It said it is currently uncertain how long the private equity and private credit markets will last.

29d ago

Analyst: Nvidia is becoming a capital allocator in the AI era, promoting the financialization of the industry

Comparing news, analyst Rick said Nvidia is playing a role similar to a central bank in the AI era. Although Nvidia is unable to issue currency or determine interest rates, it is affecting the direction of the AI industry's most scarce resource — capital. He pointed out that the AI industry is gradually shifting from the traditional semiconductor supply chain to an infrastructure asset system, and capital itself is beginning to become an important part of the AI ecosystem. In this process, Nvidia is driving the operation of the entire industry's capital flywheel by locking in core production capacity such as GPUs, HBM, and advanced packaging, and helping customers and suppliers solve financing issues. Currently, the AI industry has formed a circular model where financing to buy GPUs → GPU rental generates cash flow → cash flow supports new financing → continues to buy GPUs, so that GPUs gradually have infrastructure asset attributes, which can generate long-term cash flow, support mortgage financing, and even asset securitization. At the same time, tech giants such as Microsoft, Google, Meta, and Amazon continued to expand AI capital expenses. NeoCloud companies relied on debt financing to expand, HBM suppliers and advanced packaging manufacturers accelerated production expansion, and private credit funds, infrastructure funds, and sovereign wealth funds also began to invest in AI data centers. Analysts believe that as the scale of investment in AI infrastructure expands, the AI industry may become one of the world's largest capital absorption areas. In the future, hundreds of billions of dollars of AI capital expenditure will continue to flow to GPUs, data centers, power, fiber optics, cooling systems, HBM, and advanced packaging. This trend may also affect the structure of financial markets: even if short-term interest rates fall, long-term financing costs are likely to remain high due to strong demand for AI capital. At the same time, capital will be further concentrated on AI companies with stable cash flow and high growth certainty, and financing pressure on traditional industries may rise further.

29d ago