NEW YORK / MANILA — November 11, 2026 | WWC ONE MEDIA | Global Financial Markets, Artificial Intelligence and Investment News
Wall Street is taking the artificial intelligence boom into potentially dangerous new territory, with two investment firms proposing nine exchange-traded funds that would allow everyday investors to speculate on the deteriorating creditworthiness of companies building the world’s AI infrastructure.
The financial products would offer retail investors exposure to credit-default swaps, sophisticated derivatives historically used by institutional investors to hedge against corporate debt defaults.
According to Bloomberg’s November 10 report, Tuttle Capital Management and Defiance ETFs are seeking to capitalize on surging demand for protection against potential losses involving AI-related borrowers, including CoreWeave, Oracle and Meta Platforms.
The timing is extraordinary.
Technology shares have suffered one of their sharpest recent selloffs, companies are borrowing hundreds of billions of dollars to construct AI data centers, and investors are increasingly questioning whether the expected profits from artificial intelligence can justify the enormous debt supporting its expansion.
The proposed funds could make it easier for retail investors to position themselves for worsening credit conditions across parts of the AI industry.
But they also introduce complicated risks that many ordinary investors may not fully understand.
As Wall Street transforms fears of an AI debt crisis into products for everyday traders, a new question is emerging: Are investors being offered protection against the next technology crash, or being drawn into another dangerous wave of financial speculation?
Nine Proposed ETFs Target the Growing AI Debt Crisis
The investment firms have submitted separate registration documents to the US Securities and Exchange Commission.
Tuttle Capital Management filed paperwork covering five proposed credit-default-swap ETFs on November 3, while Defiance’s November 5 filing covered four additional funds.
Bloomberg brought wider attention to the proposals on November 10.
The products are designed to provide exposure to changes in the perceived creditworthiness of selected companies or groups of companies connected to artificial intelligence.
Tuttle’s proposed funds include strategies focused on Oracle, CoreWeave, major technology companies, hyperscale cloud providers and semiconductor manufacturers.
Defiance’s planned funds include credit-risk exposure to CoreWeave, Oracle, Meta and a broader collection of AI infrastructure companies.
The proposals represent a departure from conventional AI investment funds.
Traditional technology ETFs generally aim to benefit when semiconductor manufacturers, cloud providers or software companies rise in value.
These new products would instead seek to benefit from increases in the market price of protection against corporate credit risk.
That distinction matters.
An ETF linked to credit-default swaps does not necessarily profit when a company’s stock falls, and an investor does not need an actual bankruptcy to experience gains or losses.
The products had not begun trading as of November 11, and their final fees, trading tickers and launch dates had not been established.
The SEC has not approved the proposed investments.
What Are Credit-Default Swaps, and Why Is Wall Street Targeting AI?
Credit-default swaps, commonly called CDS, are derivatives that transfer credit risk between counterparties.
A buyer of protection makes payments to a seller in return for compensation if a specified credit event occurs under the contract.
Such events can include a qualifying failure to pay debt or bankruptcy.
The market price of CDS protection also fluctuates before any default occurs.
When investors believe a borrower has become riskier, the cost of protection generally rises.
When confidence improves, protection costs may decline.
For example, a five-year CDS spread of 1,000 basis points broadly corresponds to an annual premium of 10% of the insured notional amount, although actual contract payments and valuation depend on market conventions and upfront pricing.
A theoretical investor purchasing $1 million of protection at that quoted spread would face an annualized premium equivalent of approximately $100,000 before accounting for those contract details.
The trade can gain value if protection becomes more expensive after purchase.
But the buyer can also lose money if credit spreads narrow, even without an actual default.
For the proposed AI credit ETFs, fund managers would seek to package this type of exposure into exchange-traded securities.
That could allow investors to access a segment of the credit market normally associated with professional bond traders, banks and hedge funds.
However, the structure introduces risks involving derivatives pricing, liquidity, leverage, counterparty exposure and the cost of maintaining protection.
Oracle’s $47.6 Billion CDS Trading Surge Reveals Growing Anxiety
Oracle has emerged as one of the most closely watched companies in the AI credit market.
The software and cloud-computing group is investing heavily in infrastructure designed to support increasingly demanding artificial intelligence workloads.
That expansion has required substantial financing.
Bloomberg-linked reporting citing Barclays credit strategist Jigar Patel indicates that cumulative CDS trading volume involving Oracle reached approximately $47.6 billion during 2026 through late October, compared with $8.7 billion during the earlier reference period cited in the analysis.
The sharp increase demonstrates how actively investors are trading Oracle-related credit risk.
However, trading volume should not be confused with outstanding corporate debt, actual default losses or a prediction of bankruptcy.
A large trading volume can result from hedging, portfolio repositioning, speculation or repeated transactions.
Oracle’s expansion has attracted attention because the company is simultaneously pursuing major artificial intelligence infrastructure projects and raising capital through debt and equity markets.
In related coverage, WWC ONE MEDIA reported on Oracle’s $10 billion bond offering during a major US corporate borrowing rush and examined whether aggressive AI financing could undermine investor confidence.
The debt market’s growing concern does not mean Oracle is close to default.
Its debt carries investment-grade ratings, and the company has substantial established business operations.
Nevertheless, investors are increasingly scrutinizing how much money the business must spend before its AI investments produce sufficient financial returns.
CoreWeave Becomes a Major Warning Sign for AI Financing
If Oracle represents the growing credit concerns surrounding a large established technology company, CoreWeave illustrates the financial challenges facing specialized AI infrastructure providers.
CoreWeave builds and operates powerful cloud-computing systems designed to support artificial intelligence applications.
The company has benefited from extraordinary demand for advanced computing capacity.
But providing that capacity requires billions of dollars in specialized processors, data centers, electricity infrastructure and supporting equipment.
CoreWeave’s business model therefore depends heavily on upfront investment and financing.
According to Bloomberg-related reporting, cumulative CDS trading involving the company reached approximately $4.6 billion, compared with about $145 million during the earlier comparison period.
Reuters reported that CoreWeave’s five-year CDS spread rose above 1,000 basis points during the recent market turmoil.
That reflects significantly greater perceived credit risk than the market assigns to many established investment-grade technology companies.
However, an elevated CDS spread does not establish that CoreWeave will default.
Credit markets can be volatile, particularly when trading liquidity is limited.
In a related investigation, WWC ONE MEDIA examined CoreWeave’s substantial debt obligations, rising borrowing costs and the growing concerns surrounding its role in the AI investment boom.
CoreWeave’s November 10 financial results offered a reminder that strong business demand and financial risk can exist simultaneously.
The company reported third-quarter revenue of approximately $3.66 billion, representing year-over-year growth of about 168%.
It also raised its full-year revenue outlook to between $13 billion and $13.3 billion.
Its contracted future revenue backlog reached approximately $132.5 billion.
Despite those substantial growth figures, the company continues to face high borrowing costs, large capital expenditure commitments and significant net losses.
This contradiction has become central to the AI credit debate.
A business can have strong customer demand and still encounter financial difficulties if its borrowing and infrastructure costs grow faster than its ability to generate sustainable cash flow.
Why Meta and Semiconductor Companies Are Also Being Targeted
The proposed ETF strategies extend beyond the most indebted specialized cloud companies.
Defiance has included a fund linked to Meta Platforms, while Tuttle has proposed strategies involving large technology groups and semiconductor manufacturers.
The inclusion of established companies demonstrates how concerns over AI capital spending have spread throughout the technology industry.
Meta is investing heavily in artificial intelligence infrastructure to support its advertising, social media and AI products.
Other large technology businesses are similarly expanding their computing capacity.
These corporations generally possess stronger financial resources and more diversified revenue streams than smaller AI infrastructure providers.
Nevertheless, their financing needs and spending commitments have attracted increasing attention from credit investors.
Even financially strong companies can experience widening CDS spreads when uncertainty increases.
That does not make their credit risk equivalent to that of lower-rated borrowers.
The proposed ETFs will expose investors to different underlying companies, levels of credit risk and portfolio construction strategies.
Understanding those differences will be essential before considering any investment.
Nearly $466 Billion in AI Debt Raises Questions About a New Financial Bubble
The proposed funds arrive amid an extraordinary increase in AI-related borrowing.
Financial Times reporting indicates that companies connected to artificial intelligence raised approximately $466 billion in debt during 2026 through the period covered by its October analysis, compared with roughly $101 billion over the comparable period in 2025.
The increase reflects how rapidly companies are financing data centers, semiconductor purchases, electricity infrastructure and cloud-computing expansion.
The borrowing is not necessarily irrational.
Businesses can reasonably use debt to finance productive infrastructure when the resulting revenue and cash flows justify the cost.
However, problems can emerge when companies rely on optimistic assumptions about future demand, project delivery or profitability.
A slowdown in AI spending, unexpected construction delays or higher interest rates could place pressure on heavily indebted borrowers.
Investors have also become increasingly concerned about the financial relationships linking AI developers, semiconductor manufacturers, cloud providers and lenders.
The industry’s interconnected structure could amplify problems if a major company encounters difficulties.
Those developments illustrate the scale of capital involved in the AI infrastructure race.
But it would be premature to conclude that the borrowing boom must end in widespread corporate defaults.
The outcome will depend on customer demand, operating cash generation, financing conditions and the performance of the infrastructure being built.
Wall Street Banks Are Becoming More Cautious
The debt market’s growing anxiety extends beyond individual AI companies.
Reuters reported on November 9 that banks and institutional investors were becoming more selective about financing AI infrastructure following the recent stock market selloff.
Lenders have increased scrutiny of project cash flows, customer guarantees, construction timetables and contractual obligations.
Specialized data center operators and neocloud companies are considered particularly vulnerable because of their reliance on external financing.
Reuters also reported Goldman Sachs projections indicating that global hyperscaler debt issuance could reach approximately $420 billion in 2027, compared with $250 billion in 2026.
Those estimates suggest that the financing requirements of major technology businesses could remain substantial even after the recent market turbulence.
However, higher borrowing costs could place pressure on weaker projects.
Some investors have begun demanding additional compensation for lending to companies exposed to the AI infrastructure boom.
The effect could be particularly pronounced among borrowers with speculative-grade credit ratings.
Investment-grade technology companies may retain access to capital on more favorable terms, but even they are not immune to broader changes in bond-market sentiment.
AI Stock Market Selloff Adds Urgency to the New ETF Proposals
The proposed funds come after a severe correction in technology shares.
On November 5, the Nasdaq 100 declined approximately 6.4%, wiping out about $2.5 trillion in market capitalization during the session, according to Reuters.
The selloff reflected mounting concerns over AI infrastructure spending, political uncertainty and potential restrictions affecting data center development.
Chipmakers and specialized AI cloud providers suffered particularly heavy losses.
The market decline also contributed to greater caution among credit investors.
As stock prices fell, investors reassessed the financial assumptions underlying some of the industry’s largest investment projects.
Credit-default-swap spreads widened for several technology borrowers, indicating rising demand for protection.
Yet the relationship between stock prices and credit risk is not straightforward.
A company’s shares can decline sharply without materially affecting its ability to repay debt.
Likewise, corporate creditworthiness can deteriorate even when equity markets appear relatively stable.
That distinction is crucial for investors considering the proposed ETFs.
These funds would be designed around credit derivatives rather than directly shorting technology stocks.
Why Experts Are Skeptical About Retail Demand
Although the proposed funds could attract attention from investors worried about the AI boom, some ETF analysts question whether ordinary traders will embrace the products.
Bloomberg ETF analyst James Seyffart has expressed skepticism about the likely retail appeal of credit-default-swap-based ETFs.
CDS instruments became widely known during the 2008 financial crisis, when investors and financial institutions used them to hedge or speculate on deteriorating credit quality.
But awareness of the instruments does not necessarily translate into an understanding of their mechanics.
Retail investors may find it difficult to distinguish between a stock-market decline and a deterioration in a company’s creditworthiness.
The proposed products may also use leverage, introducing additional volatility and the possibility of substantial losses.
Unlike traditional equity funds, CDS-based investments can be affected by premium payments and changes in derivative pricing.
A company could avoid default and still generate gains for a protection buyer if spreads widen sufficiently.
Conversely, an investor could lose money even after negative corporate headlines if spreads narrow or the cost of protection overwhelms potential gains.
For these reasons, the products may appeal more strongly to sophisticated traders than to investors seeking conventional long-term exposure to the technology sector.
Could AI Credit ETFs Make Market Selloffs Worse?
The introduction of ETFs linked to corporate default risk raises a broader market question.
Could easier access to credit speculation amplify volatility?
In theory, a successful new ETF could increase trading demand for certain CDS contracts.
That could influence liquidity and pricing in the underlying market.
However, greater participation does not automatically produce destabilizing outcomes.
Additional trading can sometimes improve price discovery and provide more opportunities for investors to hedge existing exposures.
The effects will depend on the scale of assets attracted, the liquidity of the underlying credit contracts, the use of leverage and how market participants manage their positions.
The proposed funds are not yet operating, so their actual influence on the credit market cannot be assessed.
Any claim that these ETFs have already triggered defaults or accelerated a financial crisis would be unsupported.
Still, the proposals reflect the expanding willingness of ETF providers to package increasingly specialized market strategies for retail distribution.
What the 2008 Financial Crisis Teaches Investors About Credit Derivatives
Credit-default swaps acquired a controversial reputation during the global financial crisis.
Before 2008, financial institutions accumulated extensive exposure to mortgage-linked securities and derivatives.
When the US housing market deteriorated, losses and counterparty obligations created serious financial instability.
The collapse of Lehman Brothers and the government rescue of American International Group highlighted weaknesses in risk management, leverage and financial interconnectedness.
However, today’s AI financing market differs substantially from the mortgage structures at the center of that crisis.
AI infrastructure investments are backed by different assets, customers, contractual arrangements and business models.
Financial regulation and derivatives-market practices have also changed since 2008.
The existence of CDS trading does not mean another financial crisis is inevitable.
The relevant lesson is that complex derivatives can create unexpected consequences when investors underestimate liquidity risks, leverage, counterparty exposures or the relationships between financial institutions.
For investors, the focus should remain on understanding how the proposed ETFs actually work rather than assuming that every CDS-related investment represents a repeat of 2008.
What This Means for Asian and Philippine Investors
The growing popularity of sophisticated US investment products could eventually affect investors throughout Asia.
Markets such as Hong Kong and Singapore provide access to a wide range of international ETFs, structured securities and derivatives-linked investments.
Some Philippine investors also access US-listed funds through international brokerage accounts, subject to platform availability, regulatory restrictions and investor eligibility.
AI-related credit ETFs would represent a substantially different investment from owning an index fund or purchasing shares in a technology company.
Potential investors would need to understand the risks of credit derivatives, leverage and changes in corporate bond spreads.
Currency fluctuations could introduce an additional consideration for investors whose primary savings are denominated in Philippine pesos.
It is also important to distinguish speculation about a company defaulting from an investment in its future business growth.
A fund designed to benefit from worsening credit conditions may lose value when the underlying company’s financing outlook improves.
These products should not be interpreted as straightforward substitutes for ordinary bonds, diversified ETFs or cash savings.
Goldman Sachs Sees Continued AI Financing Despite Market Turmoil
Not everyone on Wall Street believes the recent market selloff signals the end of the AI investment boom.
Major financial institutions continue to identify substantial demand for financing data centers, advanced computing equipment and cloud infrastructure.
Goldman Sachs chief executive David Solomon has pointed to ongoing interest in financing large AI projects despite volatility in technology stocks.
In related reporting, WWC ONE MEDIA examined Solomon’s comments on the continuing appetite for AI financing and the broader $1.88 trillion US corporate bond issuance environment.
This creates competing interpretations of current market conditions.
One view is that the recent selloff represents a necessary adjustment after excessive investor optimism.
Under that scenario, financially strong AI companies could continue attracting capital, while weaker businesses encounter more demanding financing conditions.
Another view is that the industry has committed too much money to infrastructure before proving that future revenue can support the investment.
If that concern proves correct, credit losses could become more widespread.
At present, the evidence supports increasing market anxiety and greater selectivity among lenders, rather than a confirmed wave of AI corporate defaults.
Five Risks Retail Investors Should Understand Before Buying AI Credit ETFs
The proposed funds could offer a new way to trade concerns about corporate borrowing, but several risks deserve particular attention.
1. Credit spreads may move differently from share prices.
A decline in a company’s stock does not guarantee profits for a fund buying CDS protection.
2. Derivative costs can erode returns.
Maintaining credit protection generally involves premium expenses and transaction costs.
3. Leverage can increase losses.
Funds using leveraged exposures may experience much greater volatility than conventional diversified investments.
4. Limited liquidity can distort pricing.
Some corporate CDS contracts trade less frequently than large-company shares or major stock indexes.
5. Regulatory approval and launch are not guaranteed.
The funds remain proposals, and their final structures, fees and availability may change.
Retail investors should read the final prospectus and understand the fund’s strategy before considering an investment.
The Bottom Line: Wall Street Is Turning Fear of an AI Debt Crisis Into a Tradable Investment
The proposed credit-default-swap ETFs mark another stage in the financial transformation of artificial intelligence.
For years, the dominant investment strategy was to identify companies that would benefit from rising demand for chips, cloud computing and AI software.
Now investment managers are seeking to create products that could benefit when the market becomes more concerned about those companies’ ability to repay their debts.
Tuttle Capital and Defiance have proposed nine funds covering individual technology borrowers and broader AI-related credit risks.
The proposals arrive as CDS trading volumes surge, borrowing costs increase for some companies and lenders take a closer look at the financial sustainability of massive infrastructure projects.
Yet there is an important difference between growing fear of default and an actual default.
Many major technology borrowers remain financially strong, while even highly leveraged businesses may successfully refinance their obligations or generate sufficient future cash flow.
For retail investors, the greater danger could be misunderstanding the complex instruments being offered.
Wall Street has already found ways for investors to profit from the extraordinary expansion of artificial intelligence. Now it wants to offer products designed to benefit when confidence in that expansion begins to unravel.
But as AI-related debt becomes the latest target of speculative ETFs, will these products help investors protect themselves from financial trouble—or introduce a new generation of traders to risks they may not fully understand until the next market crash?
