Want In On SpaceX? Kraken Unveils Early IPO Access Via xStocks

bitcoinistОпубліковано о 2026-06-06Востаннє оновлено о 2026-06-06

Анотація

Kraken now allows eligible customers in over 110 markets, excluding the US, Canada, Australia, and the UK, to register interest in the upcoming SpaceX IPO through its xStocks IPO Access program. Participation requires a verified standard Kraken mobile app account. Successful applicants will receive SPCXx, a tokenized claim backed 1:1 by SpaceX shares, instead of traditional brokerage positions. These tokenized shares can then be traded 24/7 on Kraken and other xStocks venues post-allocation. This initiative aims to broaden retail access to high-profile IPOs, typically dominated by large institutions, and is part of Kraken's larger push into tokenized equity markets. The highly anticipated SpaceX public offering is expected to begin trading on June 12.

Kraken has opened a path for eligible customers in more than 110 markets to register interest in SpaceX before the company starts public trading, and anyone who receives an allocation will get SPCXx, a tokenized claim backed 1:1 by the underlying shares.

The move puts one of the year’s most watched offerings inside a crypto app, but only for users outside the US, Canada, Australia and the UK.

How The Access Works

To take part, users need a verified Kraken account and the Kraken mobile app, not Kraken Pro or the desktop site. Kraken said the SpaceX program is being run through xStocks IPO Access, which lets eligible customers submit interest ahead of the listing, and any allocation will be issued as a token rather than a traditional brokerage position.

Source: Kraken

The company’s support pages say the feature is available in the EEA and most of the rest of the world, while US residents and clients in Canada, Australia and the UK are excluded. Kraken also said the tokenized shares can trade around the clock on Kraken and other participating xStocks venues after allocation.

The structure matters because it changes who can get near an IPO at all. In the usual process, access to pricing near the offering often goes to large institutions and a limited set of broker clients, while most retail buyers only show up once trading is already live.

BTCUSD now trading at $60,744. Chart: TradingView

A Wider Push Into Tokenized Markets

Kraken is pitching the offering as part of a broader push to bring tokenized equities into everyday use, and SpaceX is the first IPO it has placed behind that door.

The exchange’s blog says the company is opening the door to a large global audience, while its support material frames the program as a way to let eligible customers submit interest before the stock begins open-market trading.

That gives the product a different feel from a standard stock listing. Instead of waiting for a broker to open a book order or for a public market debut to settle, users would be dealing with a token tied to the share after allocation, with trading possible across the xStocks network at any hour.

SpaceX Becomes The Test Case

SpaceX is a fitting first name for the experiment because demand for the company has been intense and the public offering is being watched closely.

The company is expected to begin trading publicly on June 12 and that demand has already topped the number of shares available, based on Bloomberg’s reporting.

Featured image from Unsplash, chart from TradingView

Пов'язані питання

QWhat is the name of the program through which Kraken is offering eligible customers the chance to register interest in the SpaceX IPO?

AThe program is called xStocks IPO Access.

QHow will customers who receive an allocation of SpaceX shares via Kraken actually hold their investment?

AThey will receive SPCXx, a tokenized claim backed 1:1 by the underlying shares, rather than a traditional brokerage position.

QWhich major countries' residents are explicitly excluded from participating in Kraken's SpaceX IPO access program?

AResidents of the United States, Canada, Australia, and the United Kingdom are excluded.

QWhat is one key difference between accessing SpaceX via Kraken's tokenized offering and a standard stock listing, according to the article?

AInstead of waiting for a broker to open an order or for a public market debut, users deal with a token tied to the share, which can be traded around the clock on the xStocks network.

QWhen is SpaceX expected to begin trading publicly, according to the article?

ASpaceX is expected to begin trading publicly on June 12.

Пов'язані матеріали

Robots Begin to 'Consume Data': The Hidden Production Chain from Indian Data Factories to Billion-Dollar Humanoid Robots

Robots have started to 'consume data,' driving the formation of a new industrial supply chain focused on producing training data for embodied AI. Unlike large language models, which are trained on vast internet text corpora, embodied AI models face a 'data desert' in the physical world. This has created a massive demand for first-person perspective video data (Ego Data), captured by workers wearing cameras in places like Indian garment factories. Companies like Neocambrian AI are establishing 'data factories' where workers perform standardized tasks (e.g., sorting clothes, kitchen organization) to generate thousands of hours of video. Research, such as NVIDIA's EgoScale, demonstrates that scaling this human demonstration data predictably improves robot performance, particularly for dexterous manipulation. This has validated a training path combining large-scale human data for pre-training with smaller amounts of robot-specific data for fine-tuning. The value of different data types varies significantly, forming a 'data pyramid.' The base consists of low-cost, large-scale internet and Ego Data. Higher layers include more expensive motion-capture data (e.g., from data gloves), simulation/synthetic data, and the most costly and scarce layer: real robot teleoperation data. This demand has spawned a layered ecosystem of data suppliers: low-cost data factories, motion capture and alignment specialists, robot-native teleoperation service providers, simulation data companies, and platforms aiming for data standardization. Robot companies themselves are adopting a 'layered procurement' strategy: outsourcing generic Ego Data while building in-house capabilities for robot-specific adaptation data and the critical deployment/failure data generated in real-world applications. The industry is shifting focus from hardware and basic mobility to the data pipelines required for general-purpose capability. While parallels exist to data labeling companies like Scale AI in the LLM boom, the physical complexity of robot data—involving action success ambiguity and sim-to-real gaps—requires more integrated solutions for data collection, annotation, and a continuous feedback loop. The race is on to build the data engines that will teach robots to operate reliably in the unstructured real world.

marsbit39 хв тому

Robots Begin to 'Consume Data': The Hidden Production Chain from Indian Data Factories to Billion-Dollar Humanoid Robots

marsbit39 хв тому

Spicy Commentary | Michael Saylor's 'Player Talk'; 60-Year-Old Aunt Liquidated After 'Scamming a Young Man'

**"Spicy Commentary": Three Tales of Crypto's Wild Week** This week's "Spicy Commentary" column highlights three dramatic stories from the cryptocurrency world. First, **MicroStrategy's Michael Saylor** addressed the controversy over his company potentially selling Bitcoin. At the BTC Prague event, he clarified, "I never said the company can't sell Bitcoin. I told *you* never to sell *your* Bitcoin." This "do as I say, not as I do" stance was criticized by netizens as peak linguistic gymnastics, noting a history of him previously stating the company would "never" sell. Second, a **bizarre fraud case** emerged from Beijing. A 60-year-old woman, obsessed with getting rich from crypto but unwilling to risk her own savings, posed online as the 20-something "god-daughter" of a high-ranking official. She catfished a young man, convincing him to give her over 200,000 yuan for fabricated emergencies. She then invested all the stolen money into cryptocurrency with 10x leverage, only to lose everything in a market crash. The woman was sentenced to four years in prison for fraud. Finally, a **sobering trader's tale** surfaced on Reddit. A user posted "Tale of a crypto trader," confessing their net worth had plummeted from a peak of $45 million to roughly $17,200, primarily due to holding meme coins too long. The post, described as a crypto "book of confessions," sparked reactions ranging from sympathy to critique about greed, poor risk management, and the perils of treating meme coins as long-term investments instead of taking profits. The column concludes that this week featured masterful rhetoric, elaborate scams, and extreme financial volatility, stitching together another chapter in crypto's unpredictable theater.

Foresight News1 год тому

Spicy Commentary | Michael Saylor's 'Player Talk'; 60-Year-Old Aunt Liquidated After 'Scamming a Young Man'

Foresight News1 год тому

Tremble Humans, AI Continues Its Accelerated Sprint

Trembling, Humans: AI Continues Its Accelerated Sprint Yes, AI is still rapidly accelerating. While deep learning seemed to stall quickly in its early years, large models after years of development show no sign of hitting their ceiling. At the Zhiyuan Conference 2026, the focus is on enabling AI to move from the digital world into the physical world. Scaling Law remains effective, continuing to drive advancements in both large language models and multimodal models. The industry is now entering a phase of pursuing World Models, though unresolved technical paths and data issues mean this exploration may take 3-5 more years. Concurrently, breakthroughs in Agents are accelerating AI's real-world application in fields like healthcare and meetings. Making Agents truly useful requires key hardware-software co-design, evident from the strong presence of chip vendors at the conference. We stand at a new historical threshold where AI is becoming a foundational force reshaping the world. The first day of the conference highlighted AI's evolution from "knowing how to chat" to "knowing how to work." Scaling Law persists, World Models are the next key battleground, and Agents are transitioning from usable to好用 (user-friendly). Scaling Law is not ending but diversifying. New models like Anthropic's Fable 5 demonstrate scaling through parameter size, synthetic data, and reinforcement learning. Advancements in AI Coding and Agent deployment are enabling a trend of AI self-evolution, potentially allowing AI to take over digital world iterations. World Models represent the next frontier for large models extending into the physical realm, but no current model is truly impressive at solving real-world problems. Technical consensus is lacking, with debates on data sources (video, simulation, real-world). Different approaches are emerging: language-centric, pixel-centric, 3D-structure-centric, and visual-representation-centric models. Zhiyuan Institute is exploring a fifth path: unified latent space modeling fusing language and visual representations, and introduced its own under-development World Model, Physis-v0.1. On the product side, Agents are key to bringing AI into daily life. Since 2025, the "Year of the Agent," products have become more proactive and capable of complex tasks. Zhiyuan showcased four vertical Agents for cardiac diagnosis, autonomous research, meeting summarization, and protein risk discovery. However, technical challenges remain, particularly in context engineering like memory and orchestration. "Harness" – the engineering framework around an Agent – is crucial for maximizing its capabilities by clarifying intent, designing workflows, and incorporating validation and feedback. In summary, AI's breakneck pace continues on multiple fronts: foundational model scaling, the ambitious pursuit of World Models for physical understanding, and the ongoing refinement of practical Agents. The journey from capable to truly reliable and useful AI systems is well underway.

marsbit1 год тому

Tremble Humans, AI Continues Its Accelerated Sprint

marsbit1 год тому

The Backside of Musk's Trillion-Dollar Fortune: 85% Can't Be Sold

Elon Musk becomes the world's first trillionaire, driven by SpaceX's IPO valuing the company at $1.77 trillion. However, his vast wealth is largely illiquid: he holds over 85% voting control, likely through super-voting shares that are subject to lock-ups and selling restrictions. While his net worth surpasses $1 trillion across SpaceX, Tesla, and private holdings, only a tiny fraction (potentially under 2% annually) could be converted to cash without jeopardizing control and market confidence. SpaceX's IPO also creates paper millionaires for roughly 4,400 employees, but their holdings face lock-up periods, exercise costs, and taxes, delaying and reducing actual cash proceeds. Only 4.2% of total shares are initially available for public trading, making the stock price highly sensitive to limited net buying or selling pressure. A major test will come when lock-ups expire for the remaining 96% of shares. The article contrasts SpaceX's wealth distribution with potential AI IPOs. Anthropic and OpenAI could generate employee wealth pools 20 times larger than SpaceX's in paper value, due to their higher valuations relative to revenue and potentially more distributed ownership. However, sustaining those high price-to-sales multiples post-IPO is uncertain. A key financial puzzle for SpaceX investors is its xAI unit. While it has locked in an estimated $26 billion in annual compute revenue from clients like Anthropic and Google, the unit reported a $6.4 billion loss in 2025. More critically, estimated annual capital expenditures of ~$30.8 billion exceed that revenue. The long-term viability of SpaceX's AI narrative hinges on whether this compute income can eventually cover the unit's massive ongoing investments and losses.

链捕手1 год тому

The Backside of Musk's Trillion-Dollar Fortune: 85% Can't Be Sold

链捕手1 год тому

Торгівля

Спот
Ф'ючерси
活动图片