FOMO情绪引爆市场 ! AVAX 考验来袭! 此次反弹能否持续?

金色财经Pubblicato 2024-12-20Pubblicato ultima volta 2024-12-20

如果 Avalanche 价格将 31 美元的重要阻力位转变为支撑位,则可能处于 56% 牛市的边缘

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Avalanche 的价格在过去三天内有所回升,并试图突破 50 日移动平均线。排名第十二的加密货币 AVAX 的交易价格为 27.22 美元,高于本周的 22.75 美元低点。交易员现在希望更多的涨幅能将其推高 56% 至关键阻力位 42 美元。

AVAX 激增的潜在催化剂

短期内,多种因素可能会推高 Avalanche 的价格。Avalanche 在周四的一份声明中表示,它从倒闭的 Luna Foundation Guard 手中收购了 190 万枚 AVAX 代币。这些代币最初价值 4500 万美元,现在价值 5300 万美元。

与此同时,美联储可能决定在 11 月会议上降息。特朗普赢得大选后的第二天降息可能会引发包括加密货币在内的风险资产进一步上涨。

网络数据显示,Avalanche 区块链表现良好,活跃地址数量已升至 94,154 个,为两周以来的最高水平。

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Avalanche 活跃地址

此外,Avalanche 在过去几个月中进行了多项备受瞩目的合作。最近,它被选中参与美国最大银行摩根大通 (JP Morgan) 的项目 Kinexys。此次合作将探索大型机构的隐私和身份解决方案。

通过对一些链上指标的进一步分析可以发现撰文时鲸鱼活动增加了 49%,交易量增加了 14%。

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这表明较大的市场参与者和活跃交易者积极参与 AVAX,可能表明一种积极的情绪。

Avalanche 股价有望重新测试 42 美元?

技术面表明 Avalanche 价格可能出现反弹,可能升至重要阻力位 42 美元,即 5 月 22 日的最高水平。

在该货币对自 8 月 7 日以来连接较高低点的上升趋势线上找到强势后,此次反弹的可能性上升。它还试图突破 50 天和 100 天指数移动平均线 (EMA),表明多头即将重新获得控制权。

此外,雪崩价格振荡器已开始指向上方,相对强弱指数 (RSI) 已穿过 50 的中性点。MACD 指标的两条线也已指向上方,即将穿过零线。

因此,在成交量支撑下,突破阻力位 31 美元,将进一步上涨至 42 美元。这样的反弹意味着从当前水平反弹 56%。

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Avalanche 价格图表

另一方面,跌破上升趋势线将使看涨观点失效,并表明市场中还有更多空头。如果发生这种情况,AVAX代币将跌至下一个关键支撑位 17.27 美元,这是 8 月份的最低点。 Avalanche 在未来几周可能会继续表现良好,只要其价格保持在 22 美元至 26 美元之间,它就可能出现看涨突破。

值得一提的是,通过对 Coinglass 数据的研究表明,在 26.73 美元的水平上,AVAX 的清算池价值高达 563K,这表明可能出现短期回撤。

该水平可以作为支撑或阻力,取决于市场的反应以及鲸鱼推动和交易活动的程度。

在 Avalanche 的案例中,巨额交易者正在涌入市场,大额交易数量的增加就是明证。

在下一次清算被利用之后,AVAX 可能会在预期的反弹之前面临短暂的回撤。

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AVAX 的下一步计划是什么?

如果支撑位保持不变并成为新的阻力位,山寨币的看涨势头可能会持续,从而进一步上涨。尽管它有许多催化剂,例如美联储的决定和 Luna Guard 代币的回购,但如果阻力位 28.16 美元保持不变,市场可能会出现短期回撤,它需要突破 31 美元的关键阻力位才能确认看涨趋势。

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After Aave's Exit and TVL's Sharp Fluctuation, Where Does MegaETH's Valuation Anchor Lie?

Following the withdrawal of Aave and a sharp drop in its Total Value Locked (TVL), the valuation of the high-performance DeFi blockchain MegaETH faces scrutiny. Once a highly anticipated project with a fully diluted valuation (FDV) reaching around $2 billion, MegaETH saw its TVL plummet from a May peak of $245 million to just over $30 million in July, a roughly 70% decline. Its native token, MEGA, currently trades around $0.048 with a market cap of approximately $54 million and an FDV of about $480 million. The report identifies a core vulnerability: MegaETH's TVL was heavily dependent on a single protocol, Aave V3, which at its peak contributed around 90% of the chain's TVL. A significant portion of this capital is attributed to leveraged yield-farming strategies involving stablecoins like USDe. When the profitability of these strategies diminished, capital rapidly exited, exposing the lack of diversified, sustainable activity. Three key mismatches between MegaETH's valuation and its fundamentals are highlighted: 1. **Valuation vs. Real Usage:** With an FDV of ~$4.8B but only ~$1M in annualized protocol revenue and ~2,600 daily active addresses, the valuation appears disconnected from current economic activity. 2. **Token Narrative vs. Ecosystem Reality:** Despite its DeFi narrative, nearly 80% of the chain's recent protocol revenue comes from a trading card game, Monster, not from core DeFi applications like Aave. The chain's native stablecoin, USDM, also shows low trading volume and a declining market cap. 3. **Short-Term Hype vs. Long-Term Delivery:** Initial hype from token generation, blue-chip integrations, and influencer support has faded. Major protocols like Uniswap now hold minimal TVL on the chain, indicating that early capital was largely transient and driven by incentives rather than organic demand. The situation reflects a broader market trend where investors are becoming less tolerant of valuations based on inflated TVL and narrative, demanding clearer evidence of sustainable transactions, revenue, and ecosystem development. While MEGA's price may experience short-term rebounds from market sentiment, a fundamental re-rating likely depends on the team's ability to convert its remaining resources into tangible, user-retaining applications and genuine ecosystem growth.

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After Aave's Exit and TVL's Sharp Fluctuation, Where Does MegaETH's Valuation Anchor Lie?

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Goldman Sachs In-Depth Report: Who Will Be the Long-Term Winners in China's AI Large Model Industry?

Goldman Sachs Report: China's AI Models at an Inflection Point China's open-source/open-weight large language models (LLMs) have reached performance parity with top global proprietary models, according to a Goldman Sachs report. This is driven by architectural innovations and higher parameter efficiency, allowing Chinese models to achieve comparable capabilities at 2%-10% the parameter size and significantly lower cost. The market is evolving into a two-tiered structure: a high-end segment (e.g., GLM5.2, Qwen3.7 Max) with premium pricing and a low-end, price-sensitive segment for global SMEs and individual users. Key points: * **Cost & Performance:** Innovations like Mixture of Experts (MoE) enable high performance with smaller models. Projects like Meituan's LongCat 2.0, trained on domestic hardware, highlight progress in tech self-sufficiency. * **Open-Source Strategy:** Most Chinese players use open-source/open-weight models for flexibility and ecosystem growth. However, Goldman notes this may underreport actual deployment and revenue. A shift toward "open-weight + community license" models with revenue sharing (e.g., MiniMax) could improve monetization. * **Market Shift & Global Expansion:** Enterprise AI adoption is shifting from "token maximization" to "ROI-first." International expansion, especially in non-US markets, is a major growth driver. Chinese models are increasingly available on global platforms like AWS Bedrock and Microsoft Copilot. * **Competitive Landscape:** Using a framework based on pricing power, cost advantage, and financial strength, Goldman identifies **Zhipu AI and DeepSeek** as the strongest in foundational text models, and **ByteDance** as the leader in multimodal/video generation. The report maintains Buy ratings on MiniMax and Kuaishou. * **Market Growth:** China's AI model API and subscription revenue is projected to grow from an estimated ¥35 billion in 2026 to ¥879 billion by 2030.

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Goldman Sachs In-Depth Report: Who Will Be the Long-Term Winners in China's AI Large Model Industry?

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Goldman Sachs Deep Dive Report: Who Will Become the Long-Term Winners in China's AI Large Model Industry?

Goldman Sachs Report: Who Will Be the Long-Term Winners in China's AI Large Model Industry? China's AI large model sector is at a historic inflection point. Goldman Sachs argues that the intelligence of Chinese open-source/open-weight models is approaching top global proprietary models. Rapid adoption by domestic enterprises and global SMEs is creating a data flywheel effect that will further drive model iteration. The evolution is summarized as moving from "DeepSeek's cost-efficiency moment last year to GLM's model-intelligence moment this year." Chinese models achieve near-state-of-the-art performance at significantly lower cost, primarily due to architectural innovations like Mixture of Experts (MoE) and higher parameter efficiency. Models like DeepSeek V4 Pro (1.6T params), GLM5.2 (0.7T), and MiniMax M3 (0.4T) are much smaller than global leaders. Recent advancements in coding capability are attributed to better data curation and RLHF. Landmarks like Meituan's LongCat 2.0, trained fully on domestic AI chips, demonstrate progress in hardware stack independence. The market is forming a "two-tiered structure." The high-end tier (e.g., GLM5.2, Alibaba's Qwen3.7 Max) prices around $1 per million tokens, about 10-25% of US top models, with estimated inference gross margins of 10-20%. The low-end tier (priced as low as $0.06-$0.2 per million tokens) targets price-sensitive global SMEs and individuals. MiniMax derives 60-70% of revenue overseas. Goldman forecasts China's AI model API/subscription revenue to grow from an estimated RMB 35bn in 2026 to RMB 879bn by 2030. Most Chinese players adopt open-source/open-weight strategies for deployment flexibility and community feedback, though this limits monetization as deployments on third-party platforms (e.g., Alibaba Cloud) may not generate direct revenue. A shift towards "open-weight + community license" models with revenue-sharing agreements (like MiniMax's approach) could improve unit economics. International expansion, particularly in non-US markets, is the key growth driver. The global enterprise AI paradigm is shifting from "token maximization" to "ROI prioritization." Chinese models are already hosted on major global platforms like AWS Bedrock and are under consideration for integration into Microsoft Copilot. Using a competitive framework based on pricing power, cost advantage, and financial strength, Goldman identifies the strongest players: In foundational text models, Zhipu AI (initiated coverage) and DeepSeek lead. In multimodal/video generation, ByteDance's Seed is the frontrunner, with Kuaishou's Kling and MiniMax's Hailuo also well-positioned. Goldman maintains a Buy rating on MiniMax, citing its attractive valuation.

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Goldman Sachs Deep Dive Report: Who Will Become the Long-Term Winners in China's AI Large Model Industry?

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