MVC Market Watch: The Second Half of the Overall Dollar Market Consolidation

marsbitPublicado em 2026-02-21Última atualização em 2026-02-21

Resumo

Amid the Chinese Lunar New Year, the cryptocurrency market remains subdued following the clearing of positions last year. Despite a brief surge in volatility from late-January liquidations, the overall downtrend persists with no clear end in sight. Short-term prospects for crypto assets are viewed cautiously, though the current correction is seen as a consolidation phase within Bitcoin’s broader upward trend since 2022. Market activity remains lackluster, with Bitcoin declining further amid high-volume turnover. Some positive signals include manageable outflows from crypto ETFs, no material liquidation pressure on MSTR, and relatively mild on-chain liquidation data compared to October-November. However, persistent headwinds—such as elevated U.S. equity valuations, ongoing crypto capital outflows, and stagnant dollar liquidity—suggest limited near-term upside. The analysis frames the period since November 2024 as a high-level consolidation for Bitcoin, potentially setting the stage for a significant move later in the year. Optimistically, crypto may enter a new allocation cycle by Q3–Q4, with a market outlook that could eventually rival that of silver. Looking further ahead to 2026, the report highlights two key themes: 1. Base and precious metals, particularly in Latin American and RMB-denominated resource equities. 2. AI-disrupted industries, with beneficiaries primarily in the U.S. and China. The note concludes by reflecting on rapid changes in global production framew...

1/ Coinciding with the Chinese Lunar New Year, we wish our readers good health and great success.

2/ From a market perspective, although the position clearance was completed last year, the cryptocurrency market, which has lost its heartbeat, still causes concern. As of now, the end signal of this deep correction has not yet been seen. The liquidation of leveraged major players at the end of January only temporarily created demand through high volatility, further accelerating the clearance of old crypto holdings.

3/ Looking ahead, we are not optimistic about short-term crypto assets. However, overall, we tend to view this adjustment as a continued consolidation since the end of 2024. For Bitcoin, which has led dollar-denominated assets for two consecutive years, this adjustment has not altered the upward trend since 2022. In terms of international markets, we are bullish on the performance of non-ferrous metal-related industries in the capital markets and some companies benefiting from AI-disruptive industries throughout the year.

Overview and Commentary on Overall Market Conditions and Trends

The market has little to commend. We have seen Bitcoin further decline and the market experience high-volume turnover, although we also observed some optimistic signals:

1 Despite the record-high trading volume, outflow data is controllable, and the foundation of crypto ETFs remains unshaken;

2 MSTR does not face actual liquidation or financing pressure;

3 On-exchange liquidation data is relatively mild compared to October-November;

However, the market has not provided positive reasons. We still see US stocks at high levels, continuous crypto outflows, and the persistent danger of stagnant endogenous dollar liquidity. Gold and silver show no signs of ending their trends. Therefore, there is still little to expect from the crypto market in the short to medium term, which is the main reason we did not provide a separate market observation for crypto in January.

Nevertheless, we are more inclined to view the market movement since November 2024 as a consolidation after Bitcoin's highs under the distorted endogenous dollar liquidity. For a major asset class, this movement suggests the possibility of even more spectacular future performances. In speculative terms, we optimistically guess that the consolidation of crypto assets will enter a new allocation cycle in Q3-Q4 of this year, and the subsequent market movement will be no less significant than this round of silver.

Furthermore, for the full year of 2026, we are particularly optimistic about the following global asset directions:

1 The non-ferrous metals sector, represented by the elasticity of Latin American and RMB resource stocks;

2 Beneficiaries in AI-disruptive industries, with China and the US as prominent examples;

Standing at the beginning of 2026 and the Year of the Horse, our perception of the world's disparities is deeper than in 2025 and 2024. The existing world order of production is iterating rapidly, and the silent majority may face the helplessness of having decades of effort taken away overnight by a single 'seedance'. The opportunities in this round of capital markets might be the best chance for the majority who have no opportunity to transform themselves into AI sensors. The once-in-15-years major opportunity in non-ferrous metals will also begin in 2026. Let's encourage each other.

Wishing everyone smooth sailing and all the best once again.

Perguntas relacionadas

QWhat is the overall market sentiment towards crypto assets in the short term according to the article?

AThe article expresses a pessimistic short-term outlook on crypto assets, citing continued market weakness, high U.S. stock valuations, and a lack of positive catalysts.

QHow does the article characterize the market adjustment that began in late 2024 for Bitcoin?

AThe article characterizes it as a consolidation phase following Bitcoin's new highs, a normal movement for a major asset class that does not alter the upward trend that began in 2022.

QWhat two major asset categories does the article express optimism about for their performance throughout the year?

AThe article is optimistic about the global non-ferrous metals sector, represented by Latin American and RMB resource stocks, and AI-disrupted industry beneficiaries, particularly in China and the U.S.

QBy when does the article optimistically predict the crypto market consolidation will enter a new allocation cycle?

AThe article optimistically predicts that the consolidation of crypto assets will enter a new allocation cycle in Q3-Q4 of the current year.

QWhat significant event is mentioned as having only created阶段性 (phase-specific) demand in the crypto market at the end of January?

AThe liquidation of leveraged major players at the end of January, which used high volatility to create phase-specific demand and accelerate the clearing of old crypto holdings.

Leituras Relacionadas

How Likely is it for TradeXYZ to Go Solo from Hyperliquid?

The article analyzes the possibility of TradeXYZ, a dominant project on Hyperliquid's HIP-3 real-world asset (RWA) perpetual contracts market, splitting off to build its own independent trading platform. With TradeXYZ commanding over 90% of HIP-3 volume and over 35% of Hyperliquid's total open interest, its leverage and influence are significant. The primary motive for a split is seen as capturing the underlying protocol fees, of which TradeXYZ currently receives only half. However, several factors strongly discourage such a move. First, replicating Hyperliquid's high-performance infrastructure would be challenging and could degrade TradeXYZ's product quality. Second, Hyperliquid serves as a crucial distribution channel, with most users accessing TradeXYZ's liquidity through its frontend. Third, the close, trusting relationship between the founders of both projects makes a hostile "betrayal" unlikely. The conclusion is that a split would likely result in a lose-lose scenario. Hyperliquid would lose its main growth narrative and see its valuation impacted, while TradeXYZ would face immense technical hurdles, lose its primary user channel, and damage its reputation. Instead of a full separation, the more probable path is for TradeXYZ to negotiate better terms while deepening integration, focusing on enhancing its own brand and user ownership.

marsbitHá 11m

How Likely is it for TradeXYZ to Go Solo from Hyperliquid?

marsbitHá 11m

"Teletubbies" Robot Cleaning Service, $30/Hour, Pure·Manual·Intelligence

Anthropomorphic "Teletubby" robot offers cleaning services in San Francisco at $30/hour, but it's entirely remote-controlled. The robot, created by startup Tau Robotics, can perform household tasks like washing hands, mopping floors, and taking out trash. While the initial demo videos appear impressive and are notably shown at normal speed (unlike many sped-up robot demos), the company reveals the actions are performed via human teleoperation, not autonomous AI. Tau Robotics, founded in 2024, argues this "cheat" is a strategic way to bridge the current capability gap, ensure task completion, and collect real-world home data to eventually train autonomous systems. Their service features three robot models: Chelsea for kitchens/bathrooms, Elon for regular tidying with memory, and Tony for deep cleaning. Priced at $30 per hour, it's cheaper than average human cleaners in the US. The article discusses the broader challenge of deploying humanoid robots in homes, comparing Tau's approach to others like China's Ziliang and the US's 1X Neo, which also use teleoperation. A key reason for choosing a humanoid form is to make remote control more intuitive for human operators. The piece also notes the potential "emotional value" of having a humanoid servant. The service is currently invite-only in San Francisco.

marsbitHá 26m

"Teletubbies" Robot Cleaning Service, $30/Hour, Pure·Manual·Intelligence

marsbitHá 26m

From South Korea to the United States: Blue-Collar Jobs Are Becoming Increasingly Popular, Thanks to AI

AI is reshaping the labor market's value proposition. The traditional four-year college degree is losing its appeal as a guaranteed career path, while skilled blue-collar trades like electricians, welders, and plumbers are experiencing historic demand and wage premiums. This shift is driven by dual pressures: AI's displacement of certain white-collar roles and a booming need for physical infrastructure and data center construction. Data confirms the trend. In the U.S., vocational school revenue surged, and a significant portion of recent layoffs are AI-related. Surveys show a majority of Gen Z adults plan to pursue blue-collar work, citing better job security against AI automation. Vocational education interest has exploded recently. Experts cite a psychological shift as younger generations seek tangible, AI-resistant careers and avoid high student debt. In many cases, salaries for skilled trades now match or exceed those requiring a bachelor's degree. In South Korea, semiconductor vocational high schools boast near-total employment, with graduates securing high-paying roles at companies like Samsung. The shortage is structural, exacerbated by a retiring baby boomer workforce and massive infrastructure projects. Companies like JPMorgan Chase, Meta, and Lowe's are investing heavily in training programs. However, overcoming historical stigma and a "perception gap" around trade careers remains a key challenge to closing the talent gap.

marsbitHá 1h

From South Korea to the United States: Blue-Collar Jobs Are Becoming Increasingly Popular, Thanks to AI

marsbitHá 1h

Qualcomm: AI Hype Subsides, When Will Smartphones Emerge from the Gloom?

Qualcomm reported its Q3 FY2026 results (ending June 2026), with revenue of $9.95B, down 4% YoY but above expectations. Gross margin declined to 53.1%, pressured by rising costs across manufacturing and memory. Key business segments showed mixed performance: Handset revenue fell 19.6% YoY to $5.09B, dragged by an 11% decline in non-Apple Android shipments and weaker high-end mix. Conversely, Automotive revenue surged 61% to $1.59B, and IoT grew 9% to $1.83B. Core operating profit dropped 41% YoY due to margin compression and higher expenses. Management's Q4 FY2026 guidance projects revenue of $9.7B-$10.5B, in line with consensus, but Non-GAAP EPS guidance of $2.05-$2.25 fell short of expectations. Amidst persistent weakness in its core handset market, Qualcomm is pursuing growth in AI, focusing on Edge AI (smartphones, PCs, automotive) and Data Center AI. Its data center strategy includes four pillars: AI accelerators (e.g., AI200), commercial CPUs (Dragonfly C1000), custom silicon, and connectivity solutions. While these initiatives initially boosted its stock, concerns over AI capital expenditure sustainability have since erased those gains. The company targets $5B in data center revenue for FY2027 and $15B for FY2029. The report concludes that with the traditional handset business still under pressure, the data center opportunity is currently viewed as a longer-term option, and a more conservative valuation based on core operations may be warranted until AI contributions materialize.

marsbitHá 1h

Qualcomm: AI Hype Subsides, When Will Smartphones Emerge from the Gloom?

marsbitHá 1h

From TPU to Self-Evolving Agents: How Jeff Dean Predicts the Next Step in AI

At the 2026 YC Startup School, Jeff Dean outlined his vision for AI's next phase, shifting focus from simply scaling models to building intelligent, autonomous systems. He believes AI's progress is no longer just about creating smarter models, but about integrating them into systems capable of long-term, iterative work, automated experimentation, and continuous learning. This evolution moves the competition from "who has the bigger model" to "who can best organize intelligence." Dean suggests AI capabilities are now comparable to a junior engineer, enabling the automation of complex workflows. However, the true challenge and opportunity lie in managing these AI "workers" at scale. He emphasizes the importance of **context engineering**—structuring tools, memory, and feedback loops—over raw model power. For startups, this means building deep expertise in niche domains where general models currently fail (near 0-1% success rates), leveraging proprietary data, specialized tools, and domain-specific evaluators. A recurring theme is re-examining fundamental constraints. Dean's past work, like moving Google's search index to memory or creating the TPU, stemmed from questioning outdated assumptions about hardware and cost. He sees similar inflection points today, particularly in **specialized inference hardware** to drastically reduce latency and energy consumption for real-time Agent operation. Notably, he points out that in modern AI systems, the dominant cost is often not computation but **data movement**. Reliable, long-running Agents require robust system design, borrowing concepts from distributed computing like checkpointing, state management, and parallel exploration to handle failures and maintain progress over days or weeks. As AI automates execution, the scarcest human skills will shift to **defining clear specifications**, **judging what problems are worth solving** (taste), and designing effective feedback loops. Ultimately, Dean's framework prioritizes understanding the problem deeply, identifying the true bottlenecks, and systematically building closed-loop systems where AI can not only perform tasks but also improve AI itself.

marsbitHá 1h