【重磅解读】主力持币减少9.4万枚BTC,DASH反转形态加强

jinjin说币Publicado em 2022-12-13Última atualização em 2022-12-14

Resumo

BTC横盘整理,酝酿突破。

1、BTC横盘整理

BTC的日K线图中,价格震荡相当反复无常,整体波动率又非常低,意味着脱离1.7万美元的难道较大。但是考虑到横盘时间延长,低价区的持币集中度提升,BTC还是会选择突破方向。

2、主力持币减少

BTC的主力持币继续呈现出发散趋势,目前12月12日的巨鲸地址数已经下降到了2033个,相对10月28日短线高位的2127个降幅为94个,折合为BTC数量为94000个。也就是说,BTC持币数量已经在不断下降,主力减仓迹象明确,预示着行情仍然处在低迷阶段。

3、DASH短线拉升

DASH短线拉升期间,价格仍然在50美元下方运行。随着涨幅的扩大,DASH进一步验证了圆弧底反转的有效性,提示了行情向上的交易方向。因此,从目前来看,持币仍然是不错的选择。特别是考虑到BTC等主流币近期走势稳定,横盘调整却没有持续破位表现,预示着强势币种的表现较好增加。

4、LTC确认支撑

LTC短线反弹期间,确认了日K线图中布林线下轨的支撑效果,进一步验证了向上的可能性。据此判断,LTC已经处在了蓄势待发阶段,随着融资利率维持正数值,LTC蓄势期间可继续关注低吸机会。一旦BTC企稳反弹,LTC仍然有表现较好。

Leituras Relacionadas

Vitalik's Algorithmic Stablecoin Vision: Interpreting the Mechanism and Challenges from an Options Perspective

Vitalik Buterin's recent algorithmic stablecoin proposal envisions using an option-like mechanism to create a stablecoin without the liquidation risks inherent in traditional collateralized debt position (CDP) models. The design splits one unit of ETH into two components: a 'stable' leg (P) that maintains value up to a certain strike price, and an 'upside' leg (N) that captures any appreciation above that price. Together, they always sum to one ETH, eliminating the need for debt or liquidation mechanisms. From an options perspective, the stable leg essentially functions as a synthetic, covered call position. However, significant challenges exist. For the stable asset to maintain its peg, it must continuously roll deep in-the-money call options, leading to potential rollover slippage, predictable trading paths vulnerable to front-running, and liquidity issues. Crucially, the system's scalability depends on a constant demand for the upside leg—a form of leveraged ETH long position without funding rates or liquidation risk. It's unclear if such persistent, specific demand will materialize from speculators or market makers who have simpler alternatives like perpetual swaps. The author, drawing from experience with Rysk, argues that DeFi options have struggled as standalone trading products due to complexity and fragmented liquidity. Their potential lies instead as foundational infrastructure underpinning more complex financial primitives like stablecoins, structured yields, or index products—transforming from a direct product into a core pricing and risk distribution engine for the next generation of on-chain finance.

marsbitHá 1h

Vitalik's Algorithmic Stablecoin Vision: Interpreting the Mechanism and Challenges from an Options Perspective

marsbitHá 1h

GPT-5.6 Countdown: Abandon the Illusion of a Single API, Computational Iteration Can't Outpace a Single Page of Compliance

In mid-June, three seemingly independent industry events—the compliance-driven throttling of Fable 5, the open-sourcing of GLM-5.2, and the leaked release timeline for GPT-5.6—are pushing the global AI industry toward a watershed moment. These shifts signal a fundamental restructuring of the industry's underlying logic. First, **"usability" has substantially overtaken "advanced capabilities"** as the primary weight, pushing the global large language model (LLM) supply chain into a "dual-track" phase of controlled closed-source and local open-source coexistence. Second, **the competitive moats of closed-source giants are shifting**. Their technical focus is moving from "language intelligence" toward "spatial intelligence (world models)"—a domain heavily reliant on computing power. Third, faced with常态化 transnational compliance risks, **a "model-agnostic" decoupled design has become a survival necessity for application-layer developers to maintain business continuity.** The article details how Anthropic's Fable 5, despite its advanced engineering feats, was restricted for non-U.S. citizens within 72 hours of launch, highlighting how geopolitical compliance can instantly limit even the most advanced models. In response, the open-source camp, exemplified by Zhipu AI's MIT-licensed GLM-5.2, is gaining market share by offering stable performance improvements and significant cost advantages (up to 70% savings for enterprises), while achieving full adaptation with domestic semiconductor platforms. Meanwhile, closed-source leaders like OpenAI are pivoting. The anticipated GPT-5.6 reportedly shifts focus from language to spatial intelligence and world models, aiming to rebuild a generational gap in areas like 3D understanding, simulation, and industrial design that demand immense compute. The core conclusion is that the LLM supply chain's logic has changed. Enterprises must now evaluate infrastructure based on a composite of technical performance and policy compliance. For developers, complete reliance on a single closed-source API poses unacceptable risk. Implementing a truly model-agnostic architecture—enabling swift switches to compliant, locally deployable open-source alternatives—is no longer just good practice but a fundamental baseline for business continuity.

marsbitHá 3h

GPT-5.6 Countdown: Abandon the Illusion of a Single API, Computational Iteration Can't Outpace a Single Page of Compliance

marsbitHá 3h

Is the 'Token Subsidy War' Among AI Giants Almost Over?

The article discusses the ongoing "token subsidy war" among AI giants like OpenAI and Anthropic, questioning whether it's nearing its end. It reveals that current AI subscription prices are heavily subsidized, with some plans offering tokens at up to 70 times the actual cost to attract and retain heavy users, especially developers and enterprises. This strategy mirrors past internet-era subsidy battles, but with a key difference: AI tokens lack "lock-in" effects. Unlike ride-hailing or food delivery apps, users can easily switch between AI providers as APIs become standardized, making it difficult for companies to raise prices post-subsidy. The piece highlights a structural asymmetry in the competition. Giants like Google, with massive advertising revenue, can afford to subsidize tokens indefinitely, akin to using "tokens as a weapon." In contrast, venture-backed companies like OpenAI and Anthropic face pressure to become profitable, especially as they approach IPO. The article cites Google Ventures founder Bill Maris, who suggests Google could slash token prices by 80%, putting immense pressure on competitors. Two potential endgames are presented: the "internet service" model (subsidize, monopolize, then raise prices) and the "utility" model (tokens become a standardized, low-margin commodity like electricity). Given the low switching costs, the latter seems more likely. The competition may not have a single winner but could instead accelerate AI's evolution into a foundational, infrastructure-level technology, akin to a public utility. For now, users continue to benefit from heavily subsidized token costs.

marsbitHá 4h

Is the 'Token Subsidy War' Among AI Giants Almost Over?

marsbitHá 4h

Trading

Spot
Futuros
活动图片