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MSX Q1 Review and Q2 Outlook: Securing the Main Trends in U.S. Stocks, A Methodology for Precise Stock Selection

MSX Q1 Review & Q2 Outlook: Capturing the U.S. Stock Market Trends and a Precision Stock Selection Methodology In Q1 2026, the crypto market performed poorly, with Bitcoin falling about 23%, marking its worst quarterly start since 2018. In contrast, the U.S. stock market, despite significant drops in the "Magnificent Seven," still saw profitable opportunities in rapidly rotating hot sectors. The decentralized RWA trading platform MSX listed 39 new U.S. stock tokenized assets, covering five main themes: aerospace/defense, energy/resources, AI hardware, optical communications, and regional allocation tools. Among these, 38 achieved positive returns, with an average gain of 37.6%. Four stocks more than doubled, all concentrated in AI hardware and optical communications. MSX's stock selection framework focuses on identifying companies with clear industrial trends, tangible order flows, and earnings validation, rather than speculative narratives. The platform avoids high-risk bets on large-cap reversals, instead targeting small and mid-cap stocks benefiting from real capital expenditure and supply chain expansion. In Q1, the five main themes were identified through continuous tracking of corporate earnings, capex guidance, and capital flow dynamics—not macro forecasts alone. AI hardware and optical communications were confirmed as systemic opportunities based on actual order transfers and infrastructure demand from big tech's expanding data centers. Although aerospace/defense and regional tools had modest gains, they provided portfolio diversification and non-correlated hedges, enhancing structural resilience. MSX's listing节奏 was dynamically adjusted based on market signals and industrial data rather than pre-set schedules. Looking ahead, Q2 may see a continuation of the AI narrative but with increased selectivity. Aerospace and undervalued software/SaaS sectors present new opportunities. MSX emphasizes a balanced approach: maintaining core exposure to high-conviction AI infrastructure plays while incorporating defensive assets like energy and tools to navigate macro uncertainties, including interest rate paths and geopolitical risks. The platform aims to help users, especially those from crypto backgrounds, build robust, multi-asset strategies through education and thematic investing tools.

Odaily星球日报04/03 06:07

MSX Q1 Review and Q2 Outlook: Securing the Main Trends in U.S. Stocks, A Methodology for Precise Stock Selection

Odaily星球日报04/03 06:07

NVIDIA's Market Share in China Drops Below 60%, Domestic AI Chips Seize Market with 1.65 Million Units Delivered Annually

Nvidia's market share in China's AI accelerator card market has declined significantly, dropping from approximately 95% to 55% in 2025, according to IDC data. During the same period, domestic Chinese manufacturers collectively captured 41% of the market, shipping 1.65 million units out of a total market of 4 million units. Huawei led the domestic suppliers with 812,000 units shipped, representing nearly half of the local market share. This shift is driven by both U.S. export controls and China’s aggressive domestic substitution policies. In November 2025, Beijing mandated that state-funded data centers must use domestic AI chips, accelerating the adoption of local alternatives. Huawei recently launched the Atlas 350 accelerator card, claiming 2.87 times the inference performance of Nvidia’s H20 in low-precision computing, though direct comparisons are complicated by architectural differences. While Chinese chips still lag behind in training large-scale AI models—estimated to be 5-10 years behind Nvidia—they have reached a "good enough" level for many commercial applications like inference tasks. The main challenge remains software ecosystem development, as Nvidia’s CUDA platform remains the industry standard. Chinese firms are responding with compatibility efforts and open-source initiatives. Several domestic AI chip companies are now pursuing IPOs, and Huawei continues heavy R&D spending to reduce foreign dependency. Even if U.S. export policies ease, the structural move toward domestic AI chips appears irreversible.

marsbit04/03 05:51

NVIDIA's Market Share in China Drops Below 60%, Domestic AI Chips Seize Market with 1.65 Million Units Delivered Annually

marsbit04/03 05:51

The Life-and-Death Game of Large Models: From the 'Six Dragons' to the Dual Giants Going Public — The Bubble, Breakthrough, and Endgame of AI Entrepreneurship

The Chinese AI large model startup landscape has undergone a drastic reshuffle in just two years. The initial "AI Six Dragons" quickly narrowed to the "Four Strong," and by early 2026, only Zhipu AI and MiniMax had successfully listed on the Hong Kong Stock Exchange, becoming the first independent large model companies to go public. The industry has shifted from a technology and capital-driven frenzy to a focus on commercial viability and sustainable business models. Zhipu AI and MiniMax, though now publicly traded, face immense pressure with significant losses, high valuations, and challenges in achieving profitability. Zhipu relies heavily on enterprise customization projects, while MiniMax depends on overseas consumer products with limited monetization. In contrast, non-listed companies like DeepSeek and Kimi have thrived by focusing on technical excellence and niche markets. DeepSeek targets global users with cost-efficient operations, and Kimi dominates long-text processing for professional use cases. Meanwhile, former contenders like Baichuan AI and 01.AI have shifted to vertical sectors, struggling against tech giants and thinner margins. The industry is governed by three key realities: only a few players can compete in the general-purpose large model space; public listings bring heightened scrutiny and inevitable valuation corrections; and vertical markets are highly competitive, not a safe retreat. The sector is expected to consolidate within one to two years, with a stable structure emerging—led by major tech firms, a few top independent companies, and specialized vertical players. Listing is not an exit but a rite of passage, separating those that can achieve profitability from those that cannot. The era of speculation is over; survival depends on technology, product strength, and sustainable business models.

marsbit04/03 04:31

The Life-and-Death Game of Large Models: From the 'Six Dragons' to the Dual Giants Going Public — The Bubble, Breakthrough, and Endgame of AI Entrepreneurship

marsbit04/03 04:31

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