分析师：2026年加密货币市场难现山寨币季，“蓝筹幸存者”将脱颖而出

cointelegraphPublished on 2025-12-23Last updated on 2025-12-23

Abstract

CoinEx Research首席分析师Jeff Ko预测，2026年不太可能出现全面的山寨币牛市（altseason），流动性将高度集中于少数“蓝筹加密货币”而非普惠市场。他认为散户投资者期待的普涨行情难以实现，只有具备实际应用价值的蓝筹项目能获得资金青睐。Ko预计2026年全球流动性将温和改善，但央行政策分化会限制效果，同时比特币对M2货币供应量增长的敏感性自2024年ETF推出后已减弱。他对比特币2026年的目标价位设定在18万美元。然而，资深分析师Peter Brandt持不同观点，他认为当前周期尚未结束，比特币可能再经历80%的暴跌，底部或探至2.5万美元，并预测下一轮牛市高峰将出现在2029年9月——恰逢2028年4月减半事件后一年，符合四年周期规律。数据显示，比特币本季度已下跌22%，成为历史上第四季度第二差表现。尽管历史上前四季度通常表现强劲，但当前市场已清除大量风险仓位。分析师认为这为2026年构筑更健康的市场基础创造条件。比特币现报价约8.8万美元，较10月历史高点下跌30%。

CoinEx Research首席分析师Jeff Ko表示，典型的山寨币上涨行情可能在明年逐渐消退，只有「蓝筹」加密货币才能获得大部分流动性。

「期待水涨船高行情的散户投资者将会失望，」Ko告诉Cointelegraph，「我们预测不会出现传统的山寨币季；相反，流动性将极其挑剔，只会流向真正具有实际应用价值的蓝筹幸存者。」

Ko预计「2026年全球流动性将出现顺风，但会受到各国央行政策分歧的影响」，并补充说比特币对M2货币供应量增长的历史敏感性「自2024年ETF推出以来已经减弱，相关性逐渐降低」。

他补充说，该公司的「基本预测是比特币到2026年目标价18万美元」。

然而，并非所有分析师都同意这一观点，资深分析师Peter Brandt预测将出现另一轮漫长而持久的熊市。

比特币下一个峰值将在2029年

资深期货交易员Brandt周二表示，15年来，比特币在对数尺度上经历了五次抛物线式上涨，随后至少下跌80%，但「当前周期尚未结束」。

然而，当被问及本轮周期的底部时，他「预测下一个牛市高点将出现在2029年9月」。

这一预测将与四年周期理论完美契合，峰值出现在减半事件（预计在2028年4月左右）之后一年。然而，像前几个周期那样下跌80%可能会使BTC在此之前暴跌至25,000美元。

四年周期结束了吗？

历史上，第四季度通常是比特币表现最强劲的时期之一。根据Coinglass的数据，过去12个第四季度中，有8个季度出现了比特币最大的季度涨幅，其中只有一个季度的涨幅为个位数。

相关：比特币需求明显萎缩，分析师信号新熊市来临

然而，比特币本季度下跌超过22%，成为有史以来第二差的第四季度。

宏观投资资讯Milk Road周一表示，「这通常意味着市场已经清除了大量过剩风险和弱势仓位。」

「因此对于2026年，这并不自动保证上涨，但历史上看，以深度重置结束的周期往往具备更好的蓄势条件。」

比特币（BTC）目前交易价格约为88,000美元，较10月的历史高点下跌30%。

杂志：比特币关键水平82.5万美元，以太坊‘尚未结束’：交易秘密

2029 Finale Prediction: When Cryptocurrency Completely "Vanishes", Who Can Remain in This Financial Upheaval?

By 2029, the crypto industry will have transformed into a largely invisible but foundational layer for traditional finance. This timeline outlines the key shifts from now until then. By mid-2026, the most sought-after assets on-chain will not be traditional tokens, but synthetic perpetual contracts for private, high-growth companies (like SpaceX, OpenAI). These become primary price discovery tools, highlighting the market's craving for real-world asset value. Most altcoins enter a sustained bear market as their fundamental lack of asset-backed value is exposed. In late 2026, the "AI + Crypto" narrative largely fades as AI giants prove they don't need crypto infrastructure, except for prediction markets betting on model performance. Simultaneously, a quiet but significant wave of tokenization for institutional assets (money market funds, private credit) begins. The industry splits into a noisy speculative economy and a silent institutional one. Throughout 2027, major public blockchain foundations pivot decisively to serve institutional clients, building compliance toolkits and sales teams. However, key sectors hit growth ceilings: private perpetual contracts are legally restricted from public promotion, stable币 growth is capped by looming political uncertainty, and tokenization projects remain cautious. In 2028, following a U.S. election assumed to maintain a regulatory (not prohibitive) stance, a pivotal change occurs. After a major liquidation crisis exposes the flaws of synthetic contracts lacking a real-asset anchor, new regulations allow the *public solicitation* of private security sales (secondary market shares) to accredited investors. This creates a legitimate, direct on-ramp for retail capital into previously illiquid private equity. By 2029, the resulting bull market is driven by trading in real, innovative company shares (biotech, robotics, AI labs), not speculative tokens. "Crypto" as a distinct asset class recedes; it becomes the mundane, unseen plumbing for this new global private markets infrastructure. Tokens that survive are those capturing real cash flows from this infrastructure. Speculation persists but is marginalized. The core questions posed at the start are answered: token value is tied to legally enforceable claims on real assets, frontier tech adoption happens via private market channels, and crypto's absorption into traditional finance is marked by its becoming boring and invisible. The key validation for this entire thesis is whether, by late 2028, a legal pathway exists for ordinary accredited investors to access private assets directly.

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2029 Finale Prediction: When Cryptocurrency Completely "Vanishes", Who Can Remain in This Financial Upheaval?

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After the U.S. Banned Fable 5, Zhipu's Stock Soared 47%

On June 15, Chinese AI company Zhipu's stock surged up to 47.6% in Hong Kong, closing with a 32.82% gain. This sharp rise followed two key industry events. On June 12, Anthropic was compelled by a U.S. government export control order to suspend global access to its latest flagship models, Claude Fable 5 and Claude Mythos 5, impacting developers and businesses reliant on them. The next day, Zhipu announced it was opening access to its new open-source flagship model, GLM-5.2, for all Coding Plan users, with API and model weights (under the MIT license) to follow. The Anthropic incident highlighted a critical shift in the AI industry: beyond raw capability, the stability, continuous accessibility, and control over AI models are becoming equally vital, especially as AI integrates deeper into business workflows. Zhipu's move, emphasizing that "frontier intelligence should not belong to a few nor be subject to arbitrary revocation," positioned its open, accessible model as an alternative. GLM-5.2 focuses on "Long Horizon Tasks" with a 1M context window, aiming for consistency in complex, extended projects. Market analysts suggest this event exposes the risk of dependency on closed-source models subject to single jurisdiction policies, potentially accelerating a shift toward domestic base models and localized deployments. The investment response indicates a new valuation metric is emerging—prioritizing which companies can provide AI capabilities that are not only advanced but also reliably and sustainably accessible.

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After the U.S. Banned Fable 5, Zhipu's Stock Soared 47%

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PANews Column Registration and Article Submission Guide

"PANews Column Registration and Submission Guide" provides instructions for users to register as columnists and publish articles on the PANews platform. Key application requirements are emphasized: content should focus on in-depth analysis within Crypto, Web3, blockchain, data, and viewpoints. Content primarily for brand/product introductions will not be approved, and heavily AI-generated content will be rejected. Promotional (PR/soft) content is directed to the business channel. **Registration Process:** * **Web:** Go to the official website footer, click "Apply for Column," and register with a phone number or email (login via verification code, no password). Fill in the column name, description, upload an avatar, and submit links to previously published work. * **Mobile:** Navigate to "My" -> "Contribute & Create" and complete the form. **Article Submission Tutorial:** 1. Log in to the PANews website. 2. Access the "Creator Center" from your personal homepage. 3. Use the editor to create and publish articles. **Video Upload:** The platform supports embedding videos from third-party sites (e.g., Bilibili). Copy the embed code from the source video, use the editor's "Insert/Edit media" button, paste the code under the "Embed" tab, and adjust the display size (recommended: width 100%, height 560px). **PANews Skills (AI Agent Tool):** PANews offers an official AI Agent skill set called PANews Skills, enabling AI tools to query platform content, track trends, and publish column articles directly. It includes three main skills: 1. `panews`: For tracking daily must-read lists, popular articles, and funding news. 2. `panews-creator`: For managing columns, publishing articles, and uploading images. 3. `panews-web-viewer`: For parsing PANews webpages into Markdown. These skills are compatible with various AI Agent tools (OpenClaw, Cursor, Claude Code, ChatGPT, Gemini, etc.). To use the `panews-creator` skill, users must obtain a specific authentication value from the PANews website after logging into their columnist account.

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PANews Column Registration and Article Submission Guide

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I Built Myself an Investment Workbench Using AI

For the past two weeks, I've been immersed in Vibe Coding—using AI to write code from natural language descriptions. This process has enabled me to quickly build functional tools that address long-standing personal ideas. Previously, I had many concepts but found execution too cumbersome. Key ideas included a unified dashboard for assets across US stocks, Crypto, HK stocks, and A-shares; a real-time alert system for price movements; an investment map visualizing sector relationships; and a tool to correlate prediction market bets with news and market data. Traditional development hurdles meant these often remained unrealized. Using AI (Codex, Claude Code, and DeepSeek API), I built four initial tools: 1. A **Cross-Market Asset Dashboard** showing total assets, daily P&L, and holdings by market, with added features for alerts and sector mapping. It's deployed locally for privacy. 2. A **Prediction Market (PM) Monitor** tracking bets on events (e.g., company valuations) and correlating probability shifts with news and market movements. I categorize bets by conviction to filter noise. 3. A **Simple Operations Backend** for managing my writing workflow (topics, progress, publishing). It's cloud-deployed for mobile access. 4. A **One-Click Formatting Tool** that automates converting drafts into various platform-specific formats, saving manual effort. While these tools are basic, they represent a significant shift: AI lowers the barrier to creating personalized systems. I believe individual investors can now feasibly build core systems for: * **Asset Observation** (tracking holdings and changes) * **Signal Monitoring** (watching for key market shifts) * **Sector Mapping** (understanding network relationships within a sector) * **Performance Review** (documenting rationale and outcomes) The power of Vibe Coding is its fast feedback loop. Ideas can be implemented, tested, and iterated on rapidly, turning "want-to-do" into "done." This marks the start of my new phase, where I'll share investment thoughts, tool tests, on-chain operations, and educational Web3 content.

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I Built Myself an Investment Workbench Using AI

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Robinhood, the First Stock in the Predictive Market Concept

The online brokerage Robinhood, which previously partnered with prediction market platform Kalshi to offer event contract trading to its users, is now becoming a direct competitor. This shift began after Robinhood, through a joint venture, acquired and rebranded a CFTC-regulated exchange (now Rothera Exchange). Robinhood's motivation stems from the rapid growth of prediction markets on its platform, which significantly boosted its "other transaction revenue." Recognizing that its vast retail user base is the most critical asset, Robinhood aims to capture more value by routing orders to its own exchange instead of sharing fees with Kalshi. It strategically launched its Rothera platform during the high-traffic 2026 FIFA World Cup, successfully processing tens of millions of contracts in its initial days. This move signals a pivotal power shift in the prediction market industry: control over user distribution and access is emerging as a more decisive advantage than the underlying market infrastructure itself. The future competition may increasingly revolve around which platforms control the major user gateways.

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Robinhood, the First Stock in the Predictive Market Concept

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