【重磅解读】 BTC合约仓位降低到59.6亿美元,ETH酝酿价格回撤

jinjin说币Published on 2022-12-12Last updated on 2022-12-13

Abstract

BTC盘整运行

1、BTC震荡走低

BTC的日K线图中,价格走势相对平稳,BTC运行在布林线中轨上方。布林线短期收口,提示BTC即将确认突破方向。在此期间,成交量已经持续萎缩迹象,12月10日和12月11日的成交量收缩,提示行情表现不佳,仍然有下跌风险。

2、长期投资者出逃

BTC和合约持仓数量维持低位运行,目前12月12日的合约仓位下降到了59.6亿美元,为一年来的最低数值。合约投资者目前对行情明显看淡,意味着BTC近期仍然维持清淡的交易状态,预示着交易机会有限。

3、LTC缩量盘整

LTC是近期主流币反弹的主力,日K线图显示已经明显出现走弱迹象,成交量萎缩到非常低的水平。目前日K线交易量仅相当于10月24日以前的水平,因此难以支撑价格继续上涨。与此相对应的,是BTC缩量也达到了近期低位,

4、ETH成交量萎缩更为明显

ETH最高成交量峰值出现在6月13日 11月9日,当时价格跌幅较大,推动了投资者交易热情升温。而目前来看,ETH交易量继续收缩趋势仍然没有结束迹象。从2021年12月到2022年1月期间的交易量与2022难12月10日和12月11日的成交量非常相似,都处于最低水平。而2022年1月以后,ETH价格继续大幅度回撤,延续了价格颓势。本次成交量降低到低水平以后,关注价格异动预期。

Related Reads

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.

marsbit1h ago

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

marsbit1h ago

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.

marsbit4h ago

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

marsbit4h ago

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.

marsbit4h ago

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

marsbit4h ago

Trading

Spot
Futures
活动图片