When the Spreads Reach 50%: The Rise of Pre-Market Crypto-Stock Arbitrage

比推2026-03-16 tarihinde yayınlandı2026-03-16 tarihinde güncellendi

Özet

In the context of the crypto bear market, a new arbitrage opportunity is gaining traction: pre-IPO stock tokenization trading across different platforms. The article highlights significant price discrepancies—sometimes exceeding 50%—for high-profile companies like Kalshi, Polymarket, and SpaceX (xAI) on platforms such as PreStocks, Jarsy, and Tessera. These gaps, driven by varying trading mechanisms and liquidity conditions, reveal a strong market demand for a unified platform that bridges traditional and crypto pre-market trading. The piece argues that building such an intermediary could capitalize on these arbitrage opportunities, especially with a wave of major IPOs expected in 2026, while generating revenue through trading fees and liquidity provision.

Author: Wenser, Odaily Planet Daily

Editor: Hao Fangzhou

Original Title: Spreads Exceeding 50%, The Pre-Market Crypto-Stock Arbitrage Market to Become a New Business in the Crypto Bear Market

Not long ago, Mysten Labs CEO evan.sui shared his views on the "bear market." He mentioned that he does not agree with the so-called "the bear market is great, keep building" argument. In fact, the bear market is not "great"; packaging it as good for everyone overlooks the real costs (such as discouraging builders and users). Many retail investors and excellent teams will face cash flow breaks and have to exit, ultimately harming the long-term development of the crypto industry.

However, data evidence is inconsistent with this view. A report released by Lattice VC in October 2024 showed that at that time, over 80% of crypto startups that announced seed round financing during the 2022 bear market were still building. In other words, if project parties can ensure relative stability in personnel and funds, the bear market is indeed more conducive to project construction and development. As for the reasons, perhaps it's because project parties focus more on product development and experience optimization during a bear market; or perhaps the bear market trains project parties in various abilities to survive. In short, being in a crypto bear market, project parties determined to start a business might instead find a way out of desperation and carve their own path of development.

In view of this, we will explore the potential employment tracks and project directions in this cycle through a series of articles titled "Crypto Bear Market Startup Guide." If crypto projects are born and grow rapidly in the future as a result, Odaily Planet Daily also welcomes project parties to discuss cooperation.

Today, let's first talk about the hottest potential entrepreneurial direction at the moment besides prediction markets—the pre-market price difference market for crypto and stocks.

The Real Demand of the Pre-Market Crypto-Stock Market: Platform Differentiation and Liquidity Bridge

As an intermediate bridge connecting the crypto market and the traditional financial market, crypto-stock trading platforms have not only received high attention and active participation from crypto project parties, but global leading securities platforms including Nasdaq and the New York Stock Exchange have also ventured into it, aiming to capture the incremental market while further activating liquidity in the traditional financial market.

Furthermore, not only have listed cryptocurrency concept stocks undergone tokenization and on-chain contract transformation, but many hot concept stocks that have not yet IPOed have also been highly sought after by both the crypto market and the traditional financial market, thus giving rise to several pre-market stock tokenization trading platforms.

Considering that the capital market is about to welcome a wave of US listings this year, including OpenAI, Anthropic, SpaceX (xAI), Kalshi, Polymarket, OKX, Kraken, and a series of AI model companies, commercial aerospace companies, prediction market platforms, and crypto exchanges, 2026 is undoubtedly a "big year for IPOs."

Against the backdrop of the crypto market falling intermittently with occasional rebounds and the stock market rising everywhere节节攀升, the heat of the pre-market stock trading market further corroborates the above view—there is strong demand for pre-market trading of hot concept stocks in both the crypto market and the traditional financial market.

This is the main reason for the emergence of pre-market stock trading platforms such as PreStocks, Jarsy, and Tessera. Additionally, compared to pre-market stock trading markets in the traditional financial market such as Hiive and Nasdaq Private Market, the trading methods, purchase quotas, and entry barriers of the crypto pre-market trading market are more flexible, and the premiums are relatively higher, so many users participate enthusiastically.

But just as the same token can have different degrees of price differences on different exchanges, before the pre-market stock market temporarily introduces a mechanism similar to an oracle, whatever the reason, we can clearly see that the pricing of the same underlying stock on the different platforms mentioned above has certain price differences.

Based on the above information, we can make a judgment—the crypto market still lacks one or more "bridge platforms between pre-market stock trading markets."

This is probably a necessary step to push stock tokenization and pre-market stock tokenization further forward—a unified comprehensive platform covering pre-market trading in both traditional financial markets and crypto markets.

Below, we will take the 2 leading prediction market platforms Kalshi and Polymarket, which are recently seeking $20 billion in financing, and SpaceX (xAI), valued at $1.25 trillion, as examples to discuss the feasibility and real demand of this "entrepreneurial direction."

Comparing Pre-Market Spreads of PreStocks, Jarsy, Tessera 3 Major Platforms: Maximum Spread Rate Exceeds 50%, Price Difference Up to Nearly $150

Kalshi Pre-Market Spread: Up to $148, Spread Rate About 37%

Taking the Kalshi pre-market trading market as an example, its prices on different platforms are as follows—

PreStocks platform, the pre-market price of the stock token is about $397; (Compared to the $369 we mentioned one month ago in the article "Kalshi Trading Volume Continues to Break New Highs, What is a Reasonable Pre-Market Stock Price?" (https://www.odaily.news/zh-CN/post/5209330), it has increased by nearly $30, a increase of 7.6%)

Jarsy platform, the pre-market stock price is quoted at about $545. (Compared to the $504 we mentioned one month ago in the article "Kalshi Trading Volume Continues to Break New Highs, What is a Reasonable Pre-Market Stock Price?" (https://www.odaily.news/zh-CN/post/5209330), it has increased by over $40, a increase of 8.1%)

In other words, the pre-market stock price of Kalshi has a spread of up to $148 between the two major trading platforms (Odaily Planet Daily Note: Considering that the two platforms adopt an order book trading mechanism and an on-chain liquidity token trading mechanism respectively, we are only making an abstract comparison here, temporarily not involving specific asset delivery forms, the same below). If calculated based on the $360 price of the traditional financial market pre-market trading platform Hiive, the pre-market spread is even as high as $185.

Polymarket Pre-Market Spread: Up to $94, Spread Rate Over 50%

Taking the Polymarket pre-market trading market as an example, its prices on different platforms are as follows—

PreStocks platform, the pre-market price of the stock token is about $186 (Odaily Planet Daily Note: up 23% in the past 30 days);

Jarsy platform, the pre-market stock price is quoted at about $280.

In other words, the pre-market stock price of Polymarket has a spread of about $94 between the 2 major platforms, with a spread rate of about 50.5%.

SpaceX(xAI) Pre-Market Spread: About $75, Spread Rate 12.7%

Taking SpaceX(xAI) as an example, its prices on different platforms are as follows—

PreStocks platform, the pre-market price of the stock token is about $666 (Odaily Planet Daily Note: up 4.1% in the past 30 days);

Tessera platform, the pre-market price of the stock token is temporarily reported at about $591 (Odaily Planet Daily Note: up about 14.5% in the past 30 days).

In other words, the pre-market stock price of SpaceX has a spread of about $75 between the 2 major platforms, with a spread rate of about 12.7%.

In summary, based on existing pre-market trading platforms, it might be possible to build a crypto-stock pre-market spread market to meet the trading demand and speculation demand of the market after having sufficient pre-market tokens or pre-market equity capital.

Of course, considering that the current market liquidity remains within the million-dollar level, the main business model of this platform may lie in transaction fees or LP fees, as well as the realization of price differences from the platform's own investment quotas.

Twitter:https://twitter.com/BitpushNewsCN

Bitpush TG Communication Group:https://t.me/BitPushCommunity

Bitpush TG Subscription: https://t.me/bitpush

Original link:https://www.bitpush.news/articles/7619997

İlgili Sorular

QWhat is the main topic of the article regarding the crypto bear market?

AThe article discusses the emergence of a new potential business opportunity in the crypto bear market: the pre-market price arbitrage market for tokenized stocks, where significant price differences (spreads) exist across different trading platforms.

QWhich companies are mentioned as examples to illustrate the price differences in the pre-market stock trading platforms?

AThe article mentions Kalshi, Polymarket, and SpaceX (xAI) as examples to illustrate the price differences on platforms like PreStocks, Jarsy, and Tessera.

QWhat was the largest price difference (spread) mentioned for Polymarket's pre-market stock, and what was the spread rate?

AFor Polymarket, the largest price difference mentioned was $94, with a spread rate of approximately 50.5%.

QAccording to the article, what is the proposed solution to address the price differences across various pre-market trading platforms?

AThe article suggests building a bridge platform or a unified comprehensive platform that connects pre-market trading in both traditional financial markets and crypto markets to arbitrage the price differences.

QWhat reason does the article give for the emergence of platforms like PreStocks, Jarsy, and Tessera?

AThese platforms emerged due to the high demand from both crypto and traditional financial markets for pre-market trading of hot concept stocks, especially with the upcoming IPO boom in 2026 involving companies like OpenAI, Anthropic, SpaceX, and others.

İlgili Okumalar

FBI Agent Stole Millions in Crypto, Ultimately Betrayed by His Own ChatGPT

A former FBI counterintelligence agent, Patrick Steven Yaroch, was arrested on July 31 for stealing nearly $1 million in cryptocurrency from a spy suspect's digital wallet he was investigating. The 41-year-old memorized the wallet's seed phrase from FBI databases and transferred the funds over 10-12 transactions into his own account over a year ago. While not discovered by internal audits, his actions were uncovered after he voluntarily confessed to Department of Justice colleagues, citing overwhelming guilt. Investigators later found crucial evidence on his phone, including ChatGPT conversations where he sought advice on retiring early to a Portuguese vineyard with the stolen money. Following his confession, approximately $925,000 was recovered from his Kraken and Suilend accounts and returned to government control. The case highlights vulnerabilities in how law enforcement secures seized crypto assets and the potential for personal digital records to serve as evidence.

marsbit16 dk önce

FBI Agent Stole Millions in Crypto, Ultimately Betrayed by His Own ChatGPT

marsbit16 dk önce

The Biggest AI Black Hole: After Anthropic's Annual Revenue Hits $1 Trillion, Compute Power Prices Soar 10x

The article explores the potential for a dramatic surge in compute prices driven by the AI industry's explosive growth. It highlights a provocative prediction by tech podcaster Dwarkesh Patel: if AI labs like Anthropic continue their rapid revenue growth (projected to reach $1 trillion annually) while compute supply only expands at about 3x per year, the price of computing power could skyrocket by 10x or more. The core argument is a paradigm shift: GPUs are transitioning from mere hardware tools to carriers of "digital labor." If a single H100 GPU can host an AI agent capable of replacing a top-tier software engineer (with a Silicon Valley salary of $250k), its economic value should be recalibrated accordingly. Currently, the annual rental cost of an H100 is around $16k, creating a massive 15x valuation gap—a "labor arbitrage black hole." This imbalance stems from a critical mismatch: AI capabilities and commercial revenue are growing faster than the physical infrastructure (chips, data centers) can be built. With compute supply constrained by physical limits like chip manufacturing capacity, and demand soaring, prices are pressured upward. The piece further argues that expensive compute incentivizes using the most capable (and expensive) AI models, as cheaper, less efficient models waste more costly compute time—a phenomenon linked to the Alchian-Allen effect. Counterarguments are noted, suggesting AI's value may be capped in physical-world applications and that history often disproves predictions of resource scarcity. However, the response is that compute supply lacks the elasticity of traditional commodities. The conclusion is that before compute potentially becomes cheap and abundant, the industry may face an intense period of compute inflation and an arms race for this strategic resource.

marsbit25 dk önce

The Biggest AI Black Hole: After Anthropic's Annual Revenue Hits $1 Trillion, Compute Power Prices Soar 10x

marsbit25 dk önce

China's 'Bio DeepSeek' Emerges: 4 Oxford Prodigies Let AI Take Over Life Science

China's 'Biology DeepSeek' Emerges: Four Oxford Alumni Aim to Let AI Take Over Life Sciences Following DeepSeek-V4-Flash's global impact, a Chinese counterpart for life sciences has arrived. Jindu Bio, founded by four Oxford University alumni, has developed GeneLLM, a multi-omics large language model. Published in top journals *Nature Communications* and *Advanced Science*, GeneLLM is the first model pre-trained directly on raw omics data, aiming to understand the "language" and "system" of life. GeneLLM treats the four RNA bases (A, U, G, C) as fundamental tokens, learning from raw sequencing data without relying on pre-defined annotations. It uses a Transformer architecture to predict the next base, processing trillions of RNA reads. With versions ranging from 1.5 billion to 30 billion parameters, it achieves high accuracy in disease prediction with significantly lower-cost, shallow-depth sequencing, making precision medicine more accessible. Beyond the model, Jindu Bio is building BioFord Harness, an infrastructure to connect AI with physical labs. This system translates scientific intent into executable commands for various lab equipment, manages scheduling, and creates a data feedback loop. Its platform features five collaborative AI agents for literature review, experimental design, scientific reasoning, lab scheduling, and data analysis, drastically speeding up research cycles. Crucially, it turns all experimental data—including failures—into valuable learning material. The founding team combines expertise in bioengineering, AI, computational biology, and business. After initial challenges in securing funding, the company completed four financing rounds in 2023 following China's national push for "AI+" initiatives, supported by prominent investors like Sequoia Capital China and Gaotegaj Investment. In the broader AI for BioScience landscape, Jindu carves a unique niche. Unlike digital-only AI scientists or capital-intensive fully automated labs, it focuses on the "last mile" of infrastructure—orchestrating the entire research workflow by bridging AI models with existing laboratory hardware. Its long-term vision is to build an intelligent operating system for life sciences, defining a new, scalable paradigm for scientific discovery.

marsbit25 dk önce

China's 'Bio DeepSeek' Emerges: 4 Oxford Prodigies Let AI Take Over Life Science

marsbit25 dk önce

The CUDA Moat That Huang Built Over 20 Years Was Chiseled Open by AI in Just 10 Hours

NVIDIA's CUDA, the software empire built over nearly 20 years to dominate AI computing, faces a new challenge. A startup called Infinity used its AI programming agent, "Ignition," to create CUDA-like software for AI chip company d-Matrix in just 10 hours. This highlights how AI agents can rapidly generate and optimize low-level GPU kernels, a core but labor-intensive part of chip software development. While impressive, experts caution this does not equal replicating CUDA's full ecosystem of libraries, debugging tools, and developer community. The real battlefield may be the inference market, where cost and efficiency matter more than the extreme performance needed for training. Here, companies like d-Matrix and Rebellions believe CUDA's lock-in is weaker, and specialized, cost-effective chips have an opportunity. However, NVIDIA's advantages remain formidable. Industry veterans point out that generating code is easier than rigorously validating it for production use—an area where CUDA's toolchain excels. Furthermore, NVIDIA itself is employing AI to accelerate its own development. The long-term competition may shift from who has the most code to who builds the superior ecosystem for verification and optimization. While CUDA's dominance in training is secure for now, the inference side could see the first cracks in its armor.

marsbit30 dk önce

The CUDA Moat That Huang Built Over 20 Years Was Chiseled Open by AI in Just 10 Hours

marsbit30 dk önce

NVIDIA Has Moved the Mountain

**Title: NVIDIA Moves the Mountain** This article analyzes a dramatic two-day reversal in the AI and semiconductor stock markets, driven by a key announcement from NVIDIA. On Monday, August 3rd, Asian markets fell sharply, led by a crash in South Korean leveraged ETFs and panic selling in semiconductors. This spilled over to China's A-share market, where major indices dropped and semiconductor stocks like GigaDevice were hammered despite buyback announcements. The outlook for optical modules (a key AI infrastructure component) appeared bleak, weighed down by rumors of delays in CPO (Co-Packaged Optics) technology adoption. The turnaround came from the U.S. market later that same day. NVIDIA announced its Vera Rubin platform and, crucially, its senior VP declared that CPO technology had entered mass production and would be widely deployed in AI factories in the second half of the year. This directly countered the "CPO delay" narrative. Positive capex data from U.S. cloud giants added to the bullish sentiment. On Tuesday, August 4th, A-shares surged, particularly the ChiNext and STAR boards. The market saw heavy volume with over 2.2 trillion yuan in turnover. Optical module and CPO concept stocks skyrocketed, with leaders like Zhongji Innolight soaring over 13%. The rally was concentrated in growth sectors like tech and communications, while traditional "old economy" stocks like Kweichow Moutai declined. The article also notes other key developments: * A strong earnings report and raised guidance from WuXi AppTec sparked a rally in the CXO (pharma outsourcing) sector. * Mixed signals from the Middle East regarding the Strait of Hormuz. * New Chinese policies supporting the semiconductor industry and Hong Kong-China market cooperation. * Significant inflows into equity ETFs in July, suggesting institutional buying. The piece concludes by highlighting upcoming catalysts: AMD and SpaceX earnings, the potential reopening of the Strait of Hormuz, and NVIDIA's upcoming financial report later in August, which will be the next major test for the AI investment theme.

marsbit31 dk önce

marsbit31 dk önce

İşlemler

Spot