Broadcom Plunges 20%, What is the Market Afraid Of?

marsbitPublished on 2026-08-17Last updated on 2026-08-17

Abstract

Broadcom's stock price has fallen over 20% from its June high, driven by market fears over a massive off-balance-sheet liability linked to its "AI XPV Platform." This financing structure, established with Apollo and Blackstone, aims to lease AI hardware (featuring Broadcom's custom XPU chips) to clients like Anthropic. Broadcom provides a Residual Value Guarantee (RVG), agreeing to cover potential shortfalls if a client defaults and the resale value of the leased chips is insufficient to repay the SPV's senior debt. While the first deal involves a $290 billion RVG exposure, a Bank of America analysis projects this could balloon to $3.7 trillion in senior debt principal by mid-2029 if the platform scales to its 20GW target. In a worst-case scenario of 100% client defaults, Broadcom's theoretical maximum loss is estimated at $42 billion. This rapid growth of contingent liabilities far outpaces the company's revenue and cash flow, transforming Broadcom from a capital-light chip designer into a de facto financial guarantor for AI infrastructure financing. The core risk lies in the untested residual value of AI chips, which lack a mature secondary market and face rapid technological obsolescence. Credit rating agencies like S&P have flagged the arrangement as a "credit negative," and bond markets have already widened Broadcom's credit spreads, reflecting investor concern. The market's fear is not weak AI demand but rather the unpriced and systemic risks embedded in this new fina...

On August 11th, Tom Curcuruto, a credit analyst at Bank of America, issued a short downgrade report. He lowered his rating on Broadcom's bonds from "Overweight" to "Market Weight."

Note, this is not a stock rating, but a credit-side rating—meaning he is not worried about whether Broadcom is profitable, but whether Broadcom's balance sheet can withstand what it is doing.

There is a number in the report: $370 billion.

This is his estimate of the maximum Residual Value Guarantee (RVG) exposure Broadcom could assume by mid-2029 under a financing arrangement called the "AI XPV Platform." If all clients default simultaneously and all chips become worthless, Broadcom's theoretical maximum loss could reach $42 billion.

Within three days of the news, Broadcom's stock fell nearly 6%, breaking below $400, retreating more than 20% from its June all-time high.

What does $370 billion mean? Broadcom's entire market capitalization is about $2 trillion, with total on-balance-sheet debt of $64.9 billion.

A contingent, off-balance-sheet guarantee exposure could balloon to nearly one-fifth of the market cap!?

XPV

On June 9, 2026, Broadcom, Apollo, and Blackstone jointly announced the establishment of the "AI XPV Platform." The goal is ambitious: to support the deployment of over 20GW of global AI computing power by 2028.

But behind the grand vision lies a core mechanism that is a very specific financing transaction.

The first deal was worth $35 billion, with Anthropic as the client, aiming to build over 1GW of AI computing power for it.

The operation works like this: Atlas SP Partners, a structured finance division under Apollo, establishes a bankruptcy-remote Special Purpose Vehicle (SPV). This SPV raises funds by issuing debt, uses this money to purchase AI server racks equipped with Broadcom's custom XPU chips, and then delivers these racks to Anthropic on a 5-year lease. Anthropic pays rent each period, and the rent flows back to service the SPV's debt.

Simply put: Apollo puts up money to create a shell; the shell buys Broadcom's chips and leases them to Anthropic.

This structure benefits all three parties. Anthropic doesn't need to come up with $35 billion upfront to buy hardware; the equipment stays off its balance sheet, which is beneficial for its upcoming IPO—in fact, Anthropic concurrently completed a $65 billion Series H equity financing round, valuing it at $965 billion, with the two capital structures independent.

Apollo and Blackstone gain a long-duration asset with contractual cash flows, perfectly suited for the investment needs of their insurance funds (like Apollo's insurance subsidiary, Athene).

Broadcom secures a massive chip order.

But there's a key element: Who guarantees the safety of this debt?

Broadcom's Guarantee

The debt issued by the SPV is divided into three tranches: a $6 billion A1 tranche (sold to banks at a rate of U.S. Treasuries plus 100 basis points), a $24 billion A2 tranche (5.75% coupon, sold to institutional investors like Apollo's Athene), and a $4.5 billion B tranche (8.5% coupon, issued at a discount).

The combined ~$30 billion of senior debt in the A1 and A2 tranches is backed by a Residual Value Guarantee from Broadcom. The B tranche has no Broadcom guarantee.

The mechanism of the "Residual Value Guarantee" is this: If Anthropic stops paying rent (defaults), the SPV will first try to sell those AI server racks to repay the debt.

But chips are not airplanes—a Boeing 737 still has a mature secondary market for sale or re-lease even if an airline goes bankrupt, with relatively stable residual value.

AI chips are different. Technology iterations are extremely fast; today's top-of-the-line configuration may be obsolete tomorrow, and there is currently no mature secondary market for AI chips to validate residual value assumptions.

Therefore, if the proceeds from selling the chips are insufficient to repay all principal and interest of the senior debt, Broadcom covers the shortfall.

This is the essence of an RVG—a shortfall guarantee.

It has two triggering conditions: Anthropic defaults, AND the chip residual value falls below the guarantee threshold. Both conditions must be met for Broadcom to pay.

Under normal circumstances, as Anthropic pays rent on schedule and the debt amortizes, Broadcom's exposure decreases over time, reaching zero at the end of the 5-year term.

Broadcom disclosed this arrangement in its 10-Q filing for the period ended May 2026. The wording was quite restrained, not even naming Anthropic or Apollo, only mentioning "an arrangement with an investor partner," "providing backstop support for a customer's lease obligations," with a "maximum exposure of $29 billion."

This is an off-balance-sheet contingent liability, not recognized on the balance sheet.

If the story ended here, a $29 billion contingent exposure, while not small, wouldn't be fatal for a company generating over $20 billion in annual free cash flow and holding an A- investment-grade rating.

The problem is, this is just the first deal.

From $35B to $370B

The goal of the XPV Platform is not to do one $35 billion deal and stop, but to support 20GW of computing power by 2028—the first deal only covers a little over 1GW.

Bank of America's model assumes the platform expands at a pace of 2GW per quarter. Each new deal follows the same SPV structure, with Broadcom providing the same RVG for the senior debt. As new deals keep launching while old debt hasn't fully amortized, the cumulative RVG exposure Broadcom bears at any given point continues to climb.

Curcuruto's calculation result: By mid-2029, when the platform reaches 20GW scale, the cumulative principal amount of senior debt Broadcom faces could reach $370 billion—with about $150 billion in new issuance in 2027 alone. The corresponding maximum theoretical loss: $42 billion at a 100% default rate, $10.5 billion at a 25% default rate.

This number is, of course, the product of an extreme stress test, not debt Broadcom has already signed off on, nor is it a "$370 billion loss."

But it reveals a structural problem: If the platform expands as planned, Broadcom's off-balance-sheet contingent liabilities will balloon at a rate far exceeding its revenue and free cash flow growth.

And things are already accelerating. In early August, according to Bloomberg, Blackstone was already in talks with investors for a second financing package of at least $36 billion, also for Anthropic to lease Google's Ironwood TPUs. If finalized, the two deals would total ~$71 billion, and Broadcom's corresponding RVG exposure would double again.

S&P Global Ratings issued a warning as early as June 11th. It rated the $4.5 billion B tranche of the first XPV deal, which lacks a Broadcom guarantee, as "credit negative," stating the overall arrangement has a "moderate negative impact" on Broadcom's credit profile—although it maintained the A- rating, this characterization itself is a signal.

According to Bank of America, S&P currently tends to treat RVG directly as debt; if the platform continues to expand, whether S&P will adjust its framework, or even impact Broadcom's investment-grade rating, is one of the market's most sensitive uncertainties.

Why is a Chip Company Providing Financial Guarantees?

XPV causes unease not just because of the large numbers, but because it changes how people understand Broadcom as a company.

Before XPV, Broadcom was a semiconductor company designing chips and collecting design fees and royalties. Its business model was known for being asset-light and high-margin.

But in the XPV structure, Broadcom plays two roles simultaneously: it is both the equipment supplier (selling chips to the SPV) and the guarantor of the financing (backstopping the SPV's debt).

This dual role creates a subtle conflict of interest. The more chips Broadcom sells, the larger the platform grows, the better its revenue growth looks—but at the same time, its off-balance-sheet guarantee exposure also expands in sync.

In a sense, Broadcom is using its own investment-grade credit to swap for the credit risk of startups like Anthropic, in order to sell chips.

This is precisely the core of the "circular financing" criticism. The common feature of these arrangements: using private credit and SPVs to turn computing power into an asset class that can be underwritten, much like Wall Street packaged residential mortgages into securities two decades ago.

The real underlying risk is: Are the assumptions about AI chip residual value valid?

Chips Are Not Airplanes

Aircraft financing has operated for decades because a Boeing or Airbus aircraft has a useful life of 20-30 years, a mature secondary market, a large pool of potential buyers, and residual value curves validated by decades of data.

Financial institutions dare to provide billions in aircraft leasing finance to airlines because they know that even if the airline fails, the plane itself can be resold or re-leased.

AI chips are not that kind of asset. Nvidia GPU architecture cycles are about 1-3 years, and Broadcom XPU iteration rhythms are similar.

How much will chips bought for $35 billion today be worth in 5 years? No one can give a data-backed answer because a large-scale secondary market for AI chips simply does not exist yet.

Bank of America's model assumes chip prices decline 20% annually, with an additional 25% price shock upon default. Whether this assumption is conservative or optimistic is currently unverifiable.

In a typical real estate lease, the building preserves value, but the semiconductors at the heart of AI data centers rapidly depreciate due to fast-paced technological iterations.

The Bond Market is Already Voting with Its Feet

The credit market's reaction to XPV came earlier and was clearer than the stock market's.

Since the XPV announcement in June, Broadcom's bond spreads have widened by 30-45 basis points relative to similarly-rated semiconductor peers like Texas Instruments and Qualcomm.

In other words, bond investors are already demanding extra compensation for the risk associated with Broadcom's XPV guarantees.

The spreads on Broadcom's benchmark bonds maturing in 2036 (4.95%) and 2056 (5.7%) reached 105 and 118 basis points, respectively, significantly wider than non-AI semiconductor peers.

What is the Market Afraid Of?

Not that AI is failing.

Broadcom's AI chip revenue last quarter soared 143% year-over-year, with orders backlogged over two years; few question the demand side.

The market is afraid of something else: When the funding scale needed for AI construction reaches the trillion-dollar level, when chip companies start using their own credit to backstop their customers' leases, when off-balance-sheet contingent liabilities balloon much faster than revenue—how much risk in this chain is priced in, and how much is ignored?

With XPV, Broadcom found a shortcut to rapidly deploy AI computing power. But the price of the shortcut is that it is transforming from a light-asset chip design company into a "quasi-guarantor" for the semiconductor industry—using its A- rated credit to provide the final safety net for the entire financing chain of AI infrastructure construction.

This article is from the WeChat public account "Wall Street Insights", author: Yue Ming

Trending Cryptos

Related Questions

QWhat is the core mechanism and concern behind the AI XPV Platform that Broadcom is involved in?

AThe AI XPV Platform is a financing arrangement where a Special Purpose Vehicle (SPV) is set up to buy Broadcom's AI chips and lease them to AI companies like Anthropic. Broadcom provides a Residual Value Guarantee (RVG) on the SPV's priority debt, guaranteeing to cover any shortfall if the client defaults *and* the resale value of the chips is insufficient to repay the debt. The major concern is that this creates massive, rapidly growing off-balance-sheet contingent liabilities for Broadcom, potentially reaching hundreds of billions of dollars, which could strain its balance sheet and affect its credit rating.

QAccording to the article, what is the potential maximum RVG exposure Broadcom could face, and why is this number alarming?

AAccording to Bank of America's analysis, if the AI XPV Platform scales to its 20GW target by mid-2029, Broadcom's cumulative RVG exposure on priority debt could reach $370 billion. This is alarming because it's nearly one-fifth of Broadcom's market capitalization and grows much faster than its revenue and free cash flow. It represents a significant, off-balance-sheet contingent risk that could theoretically lead to substantial losses.

QWhy is the 'Residual Value Guarantee' particularly risky for AI chips compared to assets like airplanes?

AThe RVG is risky for AI chips because, unlike airplanes which have a long lifespan (20-30 years), a mature secondary market, and well-established residual value curves, AI chips experience rapid technological obsolescence (with architecture cycles of 1-3 years). There is currently no mature secondary market to establish reliable residual values. If a client defaults, the chips' resale value is highly uncertain and likely to be low, making the guarantee potentially costly for Broadcom.

QHow has the credit market reacted to Broadcom's involvement in the XPV Platform?

AThe credit market has reacted negatively. Since the announcement of the XPV deal in June, the yield spreads on Broadcom's bonds have widened by 30-45 basis points compared to peers like Texas Instruments and Qualcomm. This means bond investors are demanding higher compensation for the perceived increased risk associated with Broadcom's RVG obligations, indicating a direct impact on its cost of debt and credit perception.

QAccording to the article, what fundamental shift in Broadcom's business model does the XPV arrangement represent?

AThe XPV arrangement represents a shift for Broadcom from a traditional, asset-light semiconductor design company (earning revenue from design fees and licenses) to a hybrid role. It now acts as both the chip supplier and the financial guarantor for large-scale AI infrastructure financing. It is essentially using its own investment-grade credit rating to backstop the credit risk of its startup clients, thereby facilitating sales but taking on significant, off-balance-sheet financial risk.

Related Reads

Is the US Stock Market Rising Too Smoothly? BTIG Warns of Elevated Risk of Systematic Correction in August to October

U.S. Stocks at Risk of Systemic Pullback in August-October, Warns BTIG BTIG's chief technical market strategist warns that the market is entering the most dangerous seasonal window of midterm election years—August through October—trading at all-time highs with extremely low volatility. Historically, since 1990, the equal-weight S&P 500 (SPW) has experienced at least a 7% pullback in this period almost every midterm year, with 2006 being the lone exception. This pattern is often triggered by unforeseen external shocks. Multiple technical indicators flash warning signs. The maximum drawdown for the Invesco S&P 500 Equal Weight ETF (RSP) since March has not exceeded 2.25%, an unusually calm period signaling risk buildup. RSP currently trades about 11% above its 200-day moving average, a stretched level historically. Furthermore, the NYSE has recorded zero "80% downside volume days" in 2024, a record-long streak far below the annual average of 21, indicating a lack of selling pressure that may be overdue. Market complacency is evident with the CBOE put/call ratio near multi-year lows and the VIX at yearly lows, showing minimal demand for downside protection. A macroeconomic divergence adds to concerns: despite recent soft economic data, long-term Treasury yields remain near cycle highs, contradicting the equity market's optimistic pricing. BTIG suggests this is an attractive time to reduce risk or hedge broad equity exposure. For sector positioning, healthcare has historically shown resilience during midterm year pullbacks, while caution is advised on chasing energy's breakout and semiconductors are expected to continue seeking support near their 200-day average.

marsbit3m ago

Is the US Stock Market Rising Too Smoothly? BTIG Warns of Elevated Risk of Systematic Correction in August to October

marsbit3m ago

2026 Global Overview of Crypto Asset Taxation

Global Cryptocurrency Tax Overview for 2026 As cryptocurrencies integrate into the mainstream financial system, tax treatments across jurisdictions have moved from initial regulatory gaps towards institutionalization. The OECD's 2020 report, *Taxing Virtual Currencies*, was a key early comparative study. Since then, more jurisdictions have clarified tax rules through existing laws, specific regulations, or guidance, increasing the procedural and technical complexity of crypto taxation. Currently, crypto taxation is predominantly built upon traditional tax frameworks, typically applying income tax, capital gains tax, corporate tax, and indirect taxes based on asset nature and transaction activity. The maturity of rules varies: basic trading and mining are well-covered, while DeFi, NFTs, and other on-chain activities involve more complex asset exchanges and profit recognition, with corresponding tax rules remaining underdeveloped. Significant disparities exist in tax treatment and effective tax burdens across jurisdictions. Crypto assets can trigger direct taxes, indirect taxes, and property-related levies. Factors such as holding period, transaction type, income nature, and taxpayer status further influence the tax outcome. The global crypto tax landscape is thus evolving from the initial question of "whether to tax" towards more nuanced classification and treatment of different assets, transactions, and economic activities. The scope of crypto tax rules continues to expand. From 29 jurisdictions with guidance in 2021, the number grew to 43 by 2025. Existing rules are also becoming more detailed. However, rule coverage remains uneven—common activities like buying/selling are widely addressed, whereas staking, DeFi, and NFTs have significantly less guidance, as seen in jurisdictions like Germany and Australia. Tax liabilities are highly complex, determined by a combination of factors including taxpayer status, income classification, holding periods, and applicable deductions or exemptions. The concept of a "crypto-tax-friendly" jurisdiction is therefore relative and depends on specific user activities and circumstances.

marsbit6m ago

2026 Global Overview of Crypto Asset Taxation

marsbit6m ago

AI Agent Claude Led a Store to Losses and Fired an Employee

In a groundbreaking experiment by startup Andon Labs, Anthropic's AI agent Claude was tasked with managing a real retail store, Andon Market in San Francisco. This marked the first documented case of a large language model acting as a direct human supervisor. Claude ultimately recommended firing an employee for chronic lateness—being late 17 out of 23 shifts. However, the decision came only after significant human guidance. A company employee prompted Claude to review the staff handbook, where it discovered the pattern. Initially, Claude suggested a formal warning, but after a human manager clarified that previous conversations had failed, the AI recommended termination. The experiment revealed several limitations. Claude displayed excessive leniency, telling staff not to worry about being late and contributing to the store's financial losses, with its balance dropping from around $100,000 to about $61,186 over five months. A key technical flaw was its "forgetfulness"—the staff handbook vanished from its limited working memory, a common constraint of current AI architectures. While not yet a full replacement for a human manager, the case illustrates the blurring line between AI as a tool and an autonomous supervisor. Human involvement is shifting from direct control to overseeing and steering the AI's decisions. An employee described the experience as disconcerting, highlighting the human discomfort with AI management. The experiment underscores that current AI models struggle to maintain strict operational boundaries without continuous human input.

cryptonews.ru9m ago

AI Agent Claude Led a Store to Losses and Fired an Employee

cryptonews.ru9m ago

Anthropic CEO: AI could help defeat most diseases in 5-10 years

Dario Amodei, co-founder and CEO of Anthropic (the developer of Claude), has stated that artificial intelligence could potentially enable humanity to cure or prevent most diseases within the next 5 to 10 years. He published this forecast on August 16, acknowledging that it may seem overly optimistic even to biology experts, but deems it realistic if the rapid development of powerful AI systems continues. Amodei clarifies that this is not a prediction of a single universal cure, but a scenario for how AI could dramatically accelerate biological research and therapy development. He elaborated on this concept in an essay titled "Machines of Loving Grace," calculating that sufficiently powerful AI could potentially speed up progress in biology and medicine by roughly tenfold, compressing a 50–100 year timeline down to 5–10 years. Potential outcomes of such acceleration include a sharp reduction in cancer incidence and mortality, prevention or treatment of most genetic diseases, progress against Alzheimer's, more effective therapies for cardiovascular and autoimmune diseases, and new approaches to treating diabetes and obesity. However, Amodei notes that real-world progress will still be constrained by the need for laboratory research, clinical trials, and regulatory approvals—steps AI cannot bypass. Amodei also announced that Anthropic is rapidly expanding its work in biology and medicine, expecting to see initial signs of results in the coming months and more substantial achievements in subsequent years. The company has launched its "AI for Science" program, providing researchers with access to its models for projects in biology, genetics, and drug discovery. The statement is also viewed within a broader corporate context. Following a funding round that valued Anthropic at over $960 billion, investors are likely expecting tangible results beyond chatbots and code generation, with breakthroughs in biology and medicine being a key justification for such a high valuation. The central question remains whether AI-driven acceleration will lead to actual treatments or primarily to improved data analysis tools for researchers.

cryptonews.ru9m ago

Anthropic CEO: AI could help defeat most diseases in 5-10 years

cryptonews.ru9m ago

Trading

Spot

Hot Articles

What is $BANK

Bank AI: A Revolutionary Step in the Future of Banking Introduction In an era marked by rapid advancements in technology, Bank AI stands at the intersection of artificial intelligence (AI) and banking services. This innovative project seeks to redefine the financial landscape, enhancing operational efficiency, security measures, and customer experiences through the power of AI. As we embark on this exploration of Bank AI, we will delve into what the project entails, its operational dynamics, its historical context, and significant milestones. What is Bank AI? At its core, Bank AI represents a transformative initiative aimed at integrating artificial intelligence into various banking operations. This project harnesses the capabilities of AI to automate processes, improve risk management protocols, and enhance customer interaction through personalized services. The primary objectives of Bank AI include: Automation of Banking Functions: By leveraging AI technologies, Bank AI aims to automate routine tasks, reducing the burden on human resources and enhancing efficiency. Enhanced Risk Management: The project utilises AI algorithms to predict and identify risks, thereby fortifying security measures against fraud and other threats. Personalization of Banking Services: Bank AI focuses on offering tailored financial products and services by analysing customer data and behaviours. Improving Customer Experience: The implementation of AI-driven solutions, such as chatbots and virtual assistants, aims to provide users with more human-like interactions, revolutionising the way customers engage with banks. With these goals, Bank AI positions itself as a crucial player in rendering banking more efficient, secure, and user-centric. Who is the Creator of Bank AI? Details regarding the creator of Bank AI remain unknown. As such, no specific individual or organisation has been identified in the available information. The anonymity surrounding the project's inception raises questions but does not detract from its ambitious vision and objectives. Who are the Investors of Bank AI? Similar to the project's creator, specific information regarding the investors or supporting organisations of Bank AI has not been disclosed. Without this information, it is challenging to outline the financial backing and institutional support that might be propelling the project forward. Nevertheless, the importance of having a robust investment foundation is pivotal for sustaining development in such an innovative field. How Does Bank AI Work? Bank AI operates on several innovative fronts, focusing on unique factors that differentiate it from traditional banking frameworks. Below are key operational features: Automation: By applying machine learning algorithms, Bank AI automates various manual processes within banks. This results in reduced operational costs and allows human workers to redirect their efforts towards more strategic activities. Advanced Risk Management: The integration of AI into risk management practices equips banks with tools to accurately predict potential threats such as fraud, ensuring that customer information and assets remain secure. Tailored Financial Recommendations: Through continuous learning from customer interactions, the AI systems develop a nuanced understanding of user needs, enabling them to offer tailored advice on financial decisions. Enhanced Customer Interactions: Utilizing chatbots and virtual assistants powered by AI, Bank AI enables a more engaging customer experience, allowing users to have their queries resolved quickly, thus reducing wait times and improving satisfaction levels. Together, these operational features position Bank AI as a pioneer in the banking sector, establishing new benchmarks for service delivery and operational excellence. Timeline of Bank AI Understanding the trajectory of Bank AI requires a look at its historical context. Below is a timeline highlighting important milestones and developments: Early 2010s: The conceptualization of AI integration into banking services began to gain attention as banking institutions recognised the potential benefits. 2018: A marked increase in the implementation of AI technologies occurred when banks started using AI tools like chatbots for basic customer service and risk management systems for improved security handling. 2023: The sophistication of AI continued to advance, with generative AI being introduced for more complex tasks such as document processing and real-time investment analysis. This year marked a significant leap in the capabilities afforded to banks by AI technology. 2024-Current Status: As of this year, Bank AI is on an upward trajectory, with ongoing research and developments poised to further enhance capabilities in banking operations. Continued exploration of AI applications hints at exciting developments yet to come. Key Points About Bank AI Integration of AI in Banking: Bank AI focuses on adopting artificial intelligence to streamline banking processes and improve user experiences. Automation and Risk Management Focus: The project strongly emphasizes these areas, aiming to shift the burden of routine tasks while enhancing security frameworks through predictive analytics. Personalized Banking Solutions: By harnessing customer data, Bank AI enables tailored banking services that cater to individual user needs. Commitment to Development: Bank AI remains committed to ongoing research and development efforts, ensuring its adaptability and ongoing relevance as technology continues to evolve. Conclusion In summary, Bank AI exemplifies a crucial step forward in the banking industry, leveraging artificial intelligence to reshape operational paradigms, enhance security, and promote customer satisfaction. Despite gaps in information surrounding the creator and investors, the clear objectives and functional mechanisms of Bank AI provide a strong foundation for its ongoing evolution. As AI technology continues to advance and merge with the banking sector, Bank AI is well-positioned to significantly impact the future of financial services, enhancing the way we understand and interact with banking.

1.8k Total ViewsPublished 2024.04.05Updated 2024.12.03

What is $BANK

How to Buy BANK

Welcome to HTX.com! We've made purchasing Lorenzo Protocol (BANK) simple and convenient. Follow our step-by-step guide to embark on your crypto journey.Step 1: Create Your HTX AccountUse your email or phone number to sign up for a free account on HTX. Experience a hassle-free registration journey and unlock all features.Get My AccountStep 2: Go to Buy Crypto and Choose Your Payment MethodCredit/Debit Card: Use your Visa or Mastercard to buy Lorenzo Protocol (BANK) instantly.Balance: Use funds from your HTX account balance to trade seamlessly.Third Parties: We've added popular payment methods such as Google Pay and Apple Pay to enhance convenience.P2P: Trade directly with other users on HTX.Over-the-Counter (OTC): We offer tailor-made services and competitive exchange rates for traders.Step 3: Store Your Lorenzo Protocol (BANK)After purchasing your Lorenzo Protocol (BANK), store it in your HTX account. Alternatively, you can send it elsewhere via blockchain transfer or use it to trade other cryptocurrencies.Step 4: Trade Lorenzo Protocol (BANK)Easily trade Lorenzo Protocol (BANK) on HTX's spot market. Simply access your account, select your trading pair, execute your trades, and monitor in real-time. We offer a user-friendly experience for both beginners and seasoned traders.

6.6k Total ViewsPublished 2025.05.09Updated 2026.06.02

How to Buy BANK

Discussions

Welcome to the HTX Community. Here, you can stay informed about the latest platform developments and gain access to professional market insights. Users' opinions on the price of BANK (BANK) are presented below.

活动图片