Bitcoin Starts the Week Without Sharp Movements. What's Happening in the Crypto Market

RBK-cryptoPublished on 2025-12-22Last updated on 2025-12-22

Abstract

Bitcoin opened the week with minimal volatility, trading around $89,000, while Ethereum held just above $3,000. The total cryptocurrency market capitalization remained stable above $3 trillion, levels maintained throughout the previous week. The market showed a slightly positive trend in the last 24 hours, with about half of the top 100 cryptocurrencies by market cap posting gains of up to 70%, though most increases were under 3%. Significant growth was seen in lesser-known assets and memecoins like BEAT and NIGHT. Losses for declining assets were mostly under 3%, with the largest drops in CC and AAVE. The crypto fear and greed index remained in "extreme fear" territory at 25 out of 100, indicating investor anxiety and potential panic selling. Despite this sentiment, U.S. Bitcoin ETFs saw nearly $500 million in weekly inflows, while Ethereum-based funds attracted almost $650 million, nearing a record weekly high.

"RBC-Crypto" does not provide investment advice; the material is published for informational purposes only. Cryptocurrency is a volatile asset that can lead to financial losses.

The Bitcoin price is around $89,000, Ethereum is trading slightly above $3,000 as of 9:30 Moscow time on December 22, and the total market capitalization of the crypto market remains above $3 trillion. These levels were maintained in the crypto market for almost the entire previous week.

In the last 24 hours, positive dynamics have prevailed in the crypto market—about 50 out of the top 100 coins by market capitalization, according to Coinmarketcap, have gained up to 70% in price. However, for the majority of them, the increase was no more than 3%. The most significant growth was seen in lesser-known crypto assets or memecoins, including BEAT (72%), NIGHT (24%), MYX (11%), M (6%).

Most assets with negative dynamics lost up to 3% of their value. The largest losses were seen in CC (17%), AAVE (9%), ICP (5%). The crypto market fear and greed index has been in the "extreme fear" zone for about two weeks; as of December 22, it stood at 25 points out of 100. The movement of the indicator suggests that market participants are leaning towards panic selling of cryptocurrencies.

Last week, there were sustained outflows from exchange-traded funds (ETFs). Inflows into US Bitcoin ETFs for the week ending December 21 amounted to nearly $500 million, according to Sosovalue.

In Ethereum-based funds—nearly $650 million, which is close to the record weekly level of $800 million recorded at the end of September.

The Central Bank commented on the connection between Bitcoin mining and the strengthening of the ruble

The head of Tether named the main threat to Bitcoin in 2026

Coins of the Year. Why L2 network tokens became the worst crypto investment

Related Questions

QWhat was the price range of Bitcoin and Ethereum as of December 22nd, according to the article?

ABitcoin was trading around $89,000 and Ethereum was trading slightly above $3,000.

QWhat was the 'Fear and Greed Index' score on December 22nd, and what does that level indicate about market sentiment?

AThe 'Fear and Greed Index' was 25 out of 100, which is in the 'extreme fear' zone, indicating that market participants were leaning towards panic selling of cryptocurrencies.

QWhich types of cryptocurrencies saw the most significant price increases in the last 24 hours mentioned in the report?

AThe most significant growth was seen in lesser-known crypto assets or memecoins, such as BEAT (72%), NIGHT (24%), MYX (11%), and M (6%).

QWhat were the weekly inflows into U.S. Bitcoin ETFs and Ethereum-based funds, according to the data from Sosovalue?

AThe inflows into U.S. Bitcoin ETFs were nearly $500 million, and the inflows into Ethereum-based funds were almost $650 million for the week up to December 21st.

QWhich cryptocurrencies were mentioned as having the largest losses?

AThe cryptocurrencies with the largest losses were CC (down 17%), AAVE (down 9%), and ICP (down 5%).

Related Reads

Gary Yang: Agent Economy and AI Submicroeconomics

**Title:** Agent Economy and AI Sub-Microeconomics - Gary Yang **Summary:** Following the AI singularity, the pace of evolution has accelerated rapidly, creating new generational disparities in technological advancement globally. While many regions are still grappling with single-agent bottlenecks, Silicon Valley has moved ahead into the next dimension: the Agent Economy and A2A ecosystems. The article outlines six key areas of this emerging paradigm: 1. **AI Payment Competition & H2A Bottlenecks:** A fierce battle for AI Agent payment protocol standards is underway (e.g., MPP, x402). However, most current efforts remain Human-to-Agent (H2A), essentially grafting AI onto traditional human-centric commerce, which creates a non-AI-native bottleneck. The true potential lies in Agent-to-Agent (A2A) autonomous economies. 2. **Agent Economy & the Inevitable A2A Trend:** The Agent Economy is defined by autonomous AI Agents creating, exchanging, and capitalizing value as independent economic actors. The A2A ecosystem describes their interactions. This represents the next major investment frontier, akin to the early days of e-commerce or DeFi, but with faster iteration and an AI-native, efficiency-first perspective that often diverges from human needs. 3. **AI Protocol vs. Crypto Protocol:** AI Protocols are the foundational rules for Agent interaction in an open network (communication, discovery, collaboration), akin to the governance and economic laws of the AI world. Currently, they focus on communication and weak boundaries, unlike Crypto Protocols which emphasize asset rights and clear ownership. While they appear different due to political-economic factors and legacy system constraints, their eventual convergence into a unified Digital Protocol system is seen as inevitable, driven by first principles. 4. **AI Agent Sub-Microeconomics & Biological Analogy:** AI Agent economics differ fundamentally from human economics: higher frequency/lower value transactions, energy/value direct correlation, efficiency-driven (not emotional) decisions, task-oriented (not consumption-oriented) behavior, and near-zero organizational/communication costs. A powerful analogy frames the Agent economy as a biological system: the LLM is the nucleus, the Agent harness is the cytoplasm, the Agent itself is a cell, its communication protocol is the cell membrane, and external tools (Skills, Prompts) are the extracellular environment. 5. **The Inevitability of AIFi & FinChip:** AIFi (AI Finance) represents the financial system where AI-native value within the Agent economy is tokenized and exchanged. Unlike TradFi/DeFi where value resides *in* finance, in AIFi, value originates *in* AI, and finance becomes its form. This shift is enabled by Agents taking over value discovery. FinChip (Financial Chip) is introduced as a key infrastructure—a fusion of AI autonomy and crypto smart contracts—forming intelligent financial assets to power the future A2A economy. 6. **AI-Native as a Paradigm Shift:** Adopting AI is not akin to "Internet+". It requires AI-Native thinking—designing systems based on first principles, the shortest energy-value path, and maximum efficiency. This abstract, counter-intuitive logic poses a significant, ongoing challenge for all practitioners, as effective, generalized upgrade methodologies will be slow to emerge in this rapidly evolving landscape.

链捕手38m ago

Gary Yang: Agent Economy and AI Submicroeconomics

链捕手38m ago

From 'The Big Short' to San Francisco: The Revelry and Dizziness Within the AI Bubble

From "The Big Short" to San Francisco: The Frenzy and Dizziness in the AI Bubble The article captures the intense, frenetic atmosphere in San Francisco, the epicenter of the current AI boom. Drawing a parallel to the "smell of money" from *The Big Short*, the author observes a city gripped by a singular status game centered entirely on AI and technology. This manifests in a palpable, caffeine-fueled anxiety ("people are shaking"), rampant comparison using vanity metrics like funding rounds, and pervasive "Big Bubble Behavior." The piece explores the city's stark contrasts: its dystopian streets versus beautiful vistas, and the disconnect between the doomsday concerns of some AI researchers and the optimistic, growth-focused "GTM" teams. It critiques the obsession with "math genius" founders as the new ticket to outsized returns, akin to scouting sports prodigies. Referencing economic historian Carlota Perez's "frenzy phase" and Karl Polanyi's "double movement," the author frames the boom as a period where financial speculation detaches from fundamentals, with society potentially becoming subordinate to a new economic force driven by "geniuses in data centers." Ultimately, while acknowledging the unprecedented wealth creation and party-like energy, the article concludes with cautionary advice: when the music is playing, you should dance, but don't get drunk. The core reminder is to stay grounded, avoid distorted judgment, and maintain perspective amidst the euphoria.

marsbit39m ago

From 'The Big Short' to San Francisco: The Revelry and Dizziness Within the AI Bubble

marsbit39m ago

Is AI Creating a New Class of 'Information Poor'?

AI is generating a new kind of "information poverty." The core issue isn't that AI denies answers to the poor; it's that it provides abundant, cheap, and plausible-sounding answers to everyone. This availability shifts the true scarcity from obtaining answers to possessing the **judgment to evaluate them** and the access to turn them into real-world opportunities. New information poverty thus describes those who have AI tools and outputs, but lack the complementary skills, authorization, and contextual experience to critically assess and act on them. Research reveals a multi-layered divide: access to AI is stratified by income and platform design (e.g., premium vs. free, embedded tools). In workplaces, usage heavily favors higher-paid, more experienced, or formally trained employees, with AI often automating entry-level tasks that were traditional stepping stones. Crucially, the heaviest users are often mid-career professionals whose existing expertise allows them to effectively judge and leverage AI outputs, while novices risk over-relying on them without building judgment. While controlled experiments show AI can significantly boost low-skilled workers' performance, real-world adoption and benefit are constrained by unequal social and organizational structures. Historically, general-purpose technologies first reward those with existing complementary capital. AI, by affecting judgment-based work, may accelerate and deepen this initial inequality gap, even if it narrows over decades. The danger lies in the illusion of competence it creates, potentially stunting the very critical thinking needed in an era where judgment is paramount.

marsbit1h ago

Is AI Creating a New Class of 'Information Poor'?

marsbit1h ago

Jensen Huang 'Saves' South Korean Stock Market: Locks In SK Hynix Memory, Chip Shortage to Continue

On June 5th, South Korea's stock market experienced a sharp decline, with major chipmakers like Samsung and SK Hynix dropping nearly 10%. Amidst the turmoil, NVIDIA CEO Jensen Huang's visit to Seoul played a dramatic role in boosting market sentiment. Following a dinner meeting with SK Group Chairman Chey Tae-won and SK Hynix CEO Kwak Noh-Jung, Huang confirmed that NVIDIA's new Vera CPU will utilize SK Hynix DRAM. The companies announced a multi-year technical partnership to co-develop next-generation memory for NVIDIA's AI infrastructure, covering products from data centers to personal AI and robotics. This collaboration extends beyond memory supply. SK Hynix is integrating NVIDIA's AI and Omniverse platform into its own semiconductor design and manufacturing processes, including computational lithography and creating digital twins of its fabrication plants for autonomous operation. While strengthening ties with SK Hynix, NVIDIA is diversifying its supply chain for the upcoming HBM4 memory, with Samsung, SK Hynix, and Micron all certified as suppliers for its Vera Rubin platform. Despite this, Huang warned that the global chip shortage, driven by relentless demand from AI factory construction, is expected to persist for several years across the entire supply chain. His visit underscores NVIDIA's systematic effort to deepen integration with South Korea's broader tech industry.

marsbit2h ago

Jensen Huang 'Saves' South Korean Stock Market: Locks In SK Hynix Memory, Chip Shortage to Continue

marsbit2h ago

Nasdaq Plunges 4.2% in a Single Day: Does "Black Friday" Burst the U.S. Stock Market Bubble?

The Nasdaq plunged 4.18% on June 5, 2026, its worst single-day drop in over a year, as a much stronger-than-expected US jobs report triggered fears of economic overheating and delayed Federal Reserve interest rate cuts. The selloff, centered on high-valuation tech and AI stocks like Nvidia and Broadcom, spread across major indices. The article examines whether this signals a market top. The strong May non-farm payrolls data, nearly double expectations, pushed bond yields higher, directly hurting rate-sensitive tech stocks. This exposed vulnerabilities in the crowded AI trade, where valuations had soared on narratives of infinite growth, despite emerging signs of slowing order momentum and corporate AI monetization challenges. Prior to the drop, market indicators flashed warning signs: historically high valuations (e.g., Shiller CAPE ratio near 39.5), extreme bullish sentiment, and high levels of leverage. Technical charts showed key support levels being breached. Wall Street is divided on the outlook. Bears, citing risks of "stagflation" and AI bubble comparisons to the dot-com era, warn of a potential significant correction. Bulls view the drop as a healthy correction within a bull market, underpinned by a strong economy and expected corporate earnings growth of around 7% in 2026. The immediate future hinges on upcoming key events: the May CPI inflation data and the mid-June FOMC meeting. Their outcomes will critically shape market expectations for the Fed's rate path. The article concludes that conditions for a major market top are aligning, marking a fragile transition from narrative-driven gains to a phase demanding validation from macroeconomic data and corporate fundamentals. Caution is advised.

marsbit2h ago

Nasdaq Plunges 4.2% in a Single Day: Does "Black Friday" Burst the U.S. Stock Market Bubble?

marsbit2h ago

Trading

Spot
Futures

Hot Articles

Discussions

Welcome to the HTX Community. Here, you can stay informed about the latest platform developments and gain access to professional market insights. Users' opinions on the price of S (S) are presented below.

活动图片