Indepth Research

Provide in-depth research reports and independent analysis, leveraging data, technology, and economic insights to deliver a comprehensive examination of the blockchain ecosystem, project potential, and market trends.

Matrixport Research Report | Re-evaluating the Long-Term Allocation Value of U.S. Stocks: Institutional Dividends, Industry Cycles, and Global Capital Resonance

Matrixport Research Report: Reassessing the Long-Term Allocation Value of U.S. Stocks — Institutional Advantages, Industry Cycle, and Global Capital in Sync The core of U.S. stocks' long-term allocation value lies in the convergence of three key drivers: institutional advantages, the real validation cycle of the AI industry, and structural capital inflows—rather than short-term macro trading opportunities. U.S. equity markets, particularly the Nasdaq, have significantly outperformed global peers like China’s创业板指 and恒生科技指数 from 2015 to 2025, with smaller drawdowns and stronger compound returns. This resilience stems from deep institutional strengths: a mature innovation financing ecosystem, corporate fiscal discipline, shareholder return mechanisms, and the dollar’s global liquidity role. The AI industry is transitioning from infrastructure expansion to application penetration. Real adoption is accelerating—78% of organizations reported using AI in 2024—and capital expenditure by AI-related U.S. firms has nearly doubled since 2019. This reflects tangible investment, not speculative valuation. Global institutional capital, particularly from Europe, has structurally increased allocation to U.S. equities, with overseas holdings rising ~48% over the past two years. The deep, liquid U.S. market offers concentrated exposure to leading tech and AI assets with high regulatory predictability and low transaction costs. While 2026 may see moderate rate cuts and fiscal policy debates, the long-term outlook remains robust. Short-term volatility may offer entry opportunities. The enduring value of U.S. stocks is anchored in this self-reinforcing system of institutional, technological, and capital advantages—making them a core holding for long-term investors.

Matrixport02/13 08:38

Matrixport Research Report | Re-evaluating the Long-Term Allocation Value of U.S. Stocks: Institutional Dividends, Industry Cycles, and Global Capital Resonance

Matrixport02/13 08:38

Matrixport Research Report | Re-evaluating the Long-Term Allocation Value of U.S. Stocks: Institutional Advantages, Industry Cycles, and Global Capital Resonance

Amidst rising asset volatility, US equities remain a core long-term allocation option for global investors, driven by three structural pillars: institutional advantages, technological innovation, and shifting global capital flows. The institutional framework of US markets—spanning venture capital to public listings—supports sustained growth with lower friction and stronger shareholder returns. From 2015 to 2025, the Nasdaq Composite outperformed China’s创业板指 and恒生科技指数 by 2-3x with significantly smaller drawdowns (-36.4% vs. -69.7% and -74.4%), highlighting the power of compounding with reduced timing risk. The AI-driven industrial cycle is transitioning from infrastructure expansion to application penetration. By 2024, 78% of organizations reported using AI, up from 55% in 2023. US AI-related capex nearly doubled from 2019 to 2025, reflecting real investment and demand. The profit realization cycle remains early, with ample room for diffusion across sectors. Global capital allocation has shifted from tactical to structural: overseas holdings of US equities rose 47.6% from 2023 to 2025, led by European institutional inflows. The US market’s depth, liquidity, regulatory transparency, and concentration of high-quality tech assets make it uniquely positioned for large-scale, long-term capital deployment. While 2026 may see moderate rate cuts and fiscal policy debates, the long-term drivers—institutional resilience, AI adoption, and structural capital inflows—remain intact. Short-term volatility may present entry opportunities for disciplined investors. Matrixport now offers US stock trading with stablecoin settlements and 24/7 instant access, enabling efficient global asset allocation. *Disclaimer: This is not investment advice. Digital asset trading carries risks. Consult a professional before investing. Matrixport assumes no liability for decisions based on this content.*

marsbit02/12 12:37

Matrixport Research Report | Re-evaluating the Long-Term Allocation Value of U.S. Stocks: Institutional Advantages, Industry Cycles, and Global Capital Resonance

marsbit02/12 12:37

X Money to launch ‘external beta’ soon, but will it have crypto support?

Elon Musk announced that X Money, the upcoming payment platform for X (formerly Twitter), will enter an external beta phase within the next one to two months. The platform aims to become a central hub for all monetary transactions as part of Musk's plan to transform X into a super app. While specifics remain scarce, speculation is growing about potential cryptocurrency integration, fueled by Musk’s pro-crypto history, Tesla’s Bitcoin holdings, and industry trends toward stablecoins. However, no official confirmation of crypto support has been provided. Major partners like Visa are already involved, and the platform is expected to support P2P payments, debit cards, and bank transfers.

ambcrypto02/12 11:03

X Money to launch ‘external beta’ soon, but will it have crypto support?

ambcrypto02/12 11:03

Matrixport Research Report | Re-evaluating the Long-Term Allocation Value of U.S. Stocks: Institutional Dividends, Industry Cycles, and Global Capital Resonance

Matrixport Research Report: Reassessing the Long-Term Allocation Value of U.S. Stocks — Institutional Advantages, Industry Cycle, and Global Capital Resonance The core of U.S. stocks' long-term allocation value lies in the convergence of three key drivers: institutional advantages, the tangible AI industry cycle, and structural increases in global capital allocation—not short-term macro trading. U.S. equities remain a core allocation option for long-term investors, supported by structural strengths. From 2015 to 2025, the Nasdaq Composite significantly outperformed major Chinese tech indices with lower drawdowns, reflecting the benefits of a mature innovation financing ecosystem, corporate cash flow discipline, and the dollar’s global liquidity role. The AI industry is transitioning from infrastructure expansion to application penetration. Real adoption is accelerating, with 78% of organizations reporting AI use in 2024. U.S. AI-related capex nearly doubled from 2019 to 2025, indicating sustained investment cycle rather than speculative hype. Global institutional holdings of U.S. equities rose ~48% from 2023 to 2025, reflecting strategic reallocation—not short-term inflows. This is driven by the market’s depth, regulatory predictability, and concentrated exposure to leading tech and AI assets. While 2026 may see moderate rate cuts and fiscal policy debates, the long-term outlook remains intact. Short-term volatility may offer entry opportunities, given the resilience of structural drivers. In summary, U.S. stocks represent a rare combination of institutional, technological, and capital advantages, reinforcing their role as a long-term core holding.

Matrixport02/12 10:51

Matrixport Research Report | Re-evaluating the Long-Term Allocation Value of U.S. Stocks: Institutional Dividends, Industry Cycles, and Global Capital Resonance

Matrixport02/12 10:51

Bitcoin's Triple Resonance at the Bottom: The Ultimate Direction of Macroeconomics, On-Chain Data, and Miner Economics

Bitcoin is currently undergoing a significant correction, having fallen from its October 2025 all-time high of ~$126,000 to the $60,000-$70,000 range. This report analyzes the potential for a cycle bottom, arguing that traditional "four-year cycle" models are less reliable due to structural shifts like institutional adoption via ETFs and heightened sensitivity to macro liquidity. A multi-factor model identifies a high-confidence structural bottom zone between $52,000 and $58,000. This range represents a triple confluence of key support levels: the 200-week moving average (a historical bull/bear divider), the network's average realized price (the aggregate cost basis of all coins), and the shutdown price for a significant portion of the mining network (particularly Antminer S21 series miners). While a deeper fall to a "physical hard bottom" of ~$44,000 (the shutdown price for the most efficient miners) is possible in a worst-case scenario, it is considered unlikely barring a systemic financial crash. The analysis is set against the "Warsh Shock," a macro event where the new Fed Chair's hawkish stance on quantitative tightening has tightened liquidity, pressuring risk assets like Bitcoin. Despite the price drop, on-chain data shows short-term holders are capitulating, while long-term holders are accumulating. Furthermore, stablecoin reserves remain near all-time highs, indicating significant dry powder is waiting on the sidelines to re-enter the market. The recommended strategy is a pyramidal accumulation approach within the $52k-$58k value zone, with patience advised until macro conditions improve or key on-chain capitulation metrics are met.

marsbit02/12 09:28

Bitcoin's Triple Resonance at the Bottom: The Ultimate Direction of Macroeconomics, On-Chain Data, and Miner Economics

marsbit02/12 09:28

Tokens, Models, and Bubbles: The Crypto × AI Game in the Primary Market

Based on a two-year retrospective, this article analyzes the convergence of Crypto and AI from a primary market perspective. Initially, the crypto space heavily promoted "Crypto Helps AI" through three main narratives: computation power tokenization, data tokenization, and model tokenization. However, these efforts largely resulted in what the author calls a "tokenization illusion"—projects that issued tokens but lacked real product-market fit or sustainable business models. The piece critiques these approaches: decentralized compute networks often fail to meet enterprise reliability standards; tokenized data struggles with supply-demand alignment due to low user motivation and high professional requirements; and model tokenization is fundamentally flawed since AI models are non-scarce, easily replicable, and depreciate quickly. Additionally, projects focusing on verifiable inference (like ZKML or OPML) are solutions in search of a problem, as real-world AI failures are rarely due to malicious tampering but rather design errors or misconfigurations. The author references Vitalik Buterin’s updated views, which now present a more balanced perspective compared to two years ago. Buterin outlines four quadrants of Crypto × AI integration: two where crypto (especially Ethereum) provides trustless, economic layers for AI agents and private interactions, and two where AI enhances crypto—through local LLMs acting as user shields for security and AI improving market efficiency and DAO governance. The conclusion emphasizes that meaningful progress lies at the intersection of both fields, beyond mere tokenization or speculative narratives, and expresses hope for more substantive developments in the future.

比推02/12 06:16

Tokens, Models, and Bubbles: The Crypto × AI Game in the Primary Market

比推02/12 06:16

Viewing Crypto × AI from the Primary Market: An Experiment in Tokenization Illusion

This article analyzes the convergence of cryptocurrency and artificial intelligence (AI), critiquing the prevailing trend of "tokenization illusion" in Crypto × AI projects. Initially, the discussion highlights Vitalik Buterin's earlier skepticism toward Crypto-Helps-AI initiatives—such as tokenizing computing power, data, and AI models—which often lack sustainable product-market fit. These efforts face issues like unreliable compute services, low-quality data supply, and the non-scarce nature of AI models. The author also questions the practicality of verifiable inference (e.g., ZKML), arguing it addresses non-existent threats, as AI errors typically stem from design flaws rather than malicious tampering. Buterin’s updated perspective now balances both AI-Helps-Crypto and Crypto-Helps-AI, focusing on four key areas: using Ethereum for trustless AI interactions and economic layers for AI agents, and leveraging AI for smart contract auditing, prediction markets, and DAO governance. The conclusion emphasizes a more mature, integrated approach beyond mere tokenization, hoping for tangible progress in the coming years.

marsbit02/12 06:11

Viewing Crypto × AI from the Primary Market: An Experiment in Tokenization Illusion

marsbit02/12 06:11

The 'True and False Prosperity' of Perpetual Contracts: Can You See Through It?

Perpetual futures (perps) have become a dominant force in crypto trading, with volumes surging to about 75% of spot trading activity. While cumulative perp trading volume doubled to $14 trillion in just the past six months—exceeding the total volume of the previous four years—this growth occurred even as the total crypto market cap fell nearly 40%. However, volume alone can be misleading. To better understand market depth and trader conviction, Open Interest (OI) is a critical metric. OI has tripled from ~$4B last February to ~$13B now, indicating increased capital commitment. The OI-to-volume ratio rose from 0.33x to 0.49x over the past year, though it fluctuated significantly—peaking at ~0.72x mid-year before dropping after a major liquidation event in October. At the protocol level, platforms like Hyperliquid show strong capital efficiency, converting over 45% of daily volume into open positions and generating a take rate of ~3.2 bps. Others, like Aster, prioritize capital retention over fee maximization. The key takeaway is that sustainable growth in perp markets depends not just on high volume, but on growing OI and converting trading activity into sticky, confident capital.

marsbit02/12 03:11

The 'True and False Prosperity' of Perpetual Contracts: Can You See Through It?

marsbit02/12 03:11

The 'True and False Prosperity' of Perpetual Contracts: Have You Seen Through It?

The article "Perpetual Contracts: Real or Illusory Boom?" examines the explosive growth of perpetual futures (perps) markets, arguing that trading volume alone is a misleading metric. While perps have become dominant—growing from 44% to 75% of DEX spot volume since February 2025—this surge doesn't necessarily reflect meaningful capital deployment. Key insights include: - Total perp volume doubled to $14 trillion in just six months, even as crypto market cap fell 40%. - Open Interest (OI), which measures unrealized risk exposure, only grew ~50% in that period, indicating much of the volume is from rapid capital recycling rather than new committed capital. - The OI/Volume ratio (a measure of capital efficiency) rose from 0.33x to 0.49x over the past year, but with significant volatility, including a sharp drop after a major liquidation event in October. - Protocol-level analysis shows Hyperliquid leads in capital efficiency (OI/Vol >45%) and fee generation (~3.2 bps take rate), while others like Aster prioritize capital retention over fees. The conclusion: True market health is best read by combining volume with OI and fee data. Sustainable platforms will be those that optimize for "conviction" (long-term capital) rather than just incentivized volume.

比推02/11 19:29

The 'True and False Prosperity' of Perpetual Contracts: Have You Seen Through It?

比推02/11 19:29

Stop Paying Attention to These Zombie Projects

The crypto market in 2025 is marked by extreme contradictions: while over 20 million tokens have been launched, more than 57% have failed. A new wave of "zombie projects"—backed by top VCs and listed on major exchanges—continues to operate with minimal product development or real-world utility. This analysis highlights several疑似僵尸化 projects: - **Sleepless AI**: Once a Binance Labs incubator star, its token fell 99% from its peak. It promises AI-driven emotional companions but shows no substantial technical updates or iOS/Android app launches, raising suspicions of being a repackaged Web2 product. - **Hooked Protocol**: Its Learn-to-Earn model initially attracted users through subsidies, but token value collapsed 99% after incentives faded. Its shift to "AI-powered education" appears more like marketing than tangible tech progress. - **Saga**: Positioned as a "one-click chain launch" solution, it pivoted repeatedly between gaming and AI narratives due to lack of adoption. A $7M security breach and 99% token drop further eroded trust. - **Dymension**: Despite claiming 10,000+ RollApps, most show no activity. TVL remains low at $1.3M, and the token price dropped 99%, reflecting a ghost ecosystem. Zombie projects persist due to: 1. Capital-driven listings prioritizing narrative over substance. 2. Opaque team backgrounds enabling low-exit accountability. 3. "Narrative parasitism"—rebranding to chase trends without real development. In 2026, investors must prioritize verifiable deliverables, organic user retention beyond subsidies, and teams with consistent focus—not frequent pivots. Real value comes from projects solving actual problems, not exploiting hype.

marsbit02/11 14:43

Stop Paying Attention to These Zombie Projects

marsbit02/11 14:43

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