Circle stock recovers 150% as USDC supply hits ATH – Here’s what happened

ambcryptoОпубліковано о 2026-03-17Востаннє оновлено о 2026-03-17

Анотація

Circle's stock (CRCL) has surged by 150% since its February low of $49.9, closing at $125.83 on March 17. The rebound follows an 83% decline from its post-IPO peak of $298, driven by fading hype and a broader crypto downturn. Analysts attribute the recovery primarily to the growing adoption of Circle’s stablecoin, USDC, whose supply reached a record $79 billion—a 13% increase in two months. Over 10% of USDC is concentrated on Solana, and platforms like Hyperliquid saw 155% growth in USDC supply in a month. The expansion occurred despite a contraction in crypto trading, suggesting a decoupling from the broader market. Additionally, AI agentic payments were highlighted as a future growth driver, with Circle betting on stablecoins disrupting the global FX market. While Bitcoin’s recovery lifted other crypto stocks, CRCL outperformed on a YTD basis. Wall Street maintains a "HOLD" rating with a $145 price target.

Circle Internet Group stock, CRCL, has recovered by over 150% from its February lows of $49.9 – A 2.5x pump in a month. On the 17th of March alone, the stock added an extra 9%, closing at $125.83.

Despite the remarkable bounce, the stock had fallen hard in late 2025 and early this year. After the initial IPO hype faded and the crypto rout intensified, CRCL slumped 83%, dropping from $298 to $49.

While Bitcoin’s rebound could be partly responsible for the CRCL lift-off, analysts singled out the growing adoption of Circle’s stablecoin USDC as a key driver.

USDC supply hits record $79B

According to Jon Ma, founder of the crypto analytics platform Artemis, USDC adoption could be the greatest catalyst for CRCL’s Q1 recovery.

Noting that the $50 was an evident buy zone, Ma added,

Circle at $50/share was obvious. Stablecoin supply was $73B +25% YoY. Agentic payments were mentioned by Citrini as a winner in 2028.

Source: Artemis

During the February dip, USDC supply was about $70B. Now, its has expanded to $79B, marking a 13% increased in two months.

At the network level, over 10% of the USDC supply is concentrated in Solana [SOL]. Other trading platforms like Hyperliquid have seen 155% growth in USDC supply in the past month alone.

Interestingly, USDC’s push toward a record supply came amid a broader contraction in crypto trading. For analysts, this meant stablecoin was decoupling from the broader crypto market.

Ma’s agentic payments comment referenced a Citrini Research report that theorized that AI agents will transact on stablecoin rails and bypass traditional intermediaries by 2028.

In fact, Circle is already betting on AI agentic payment systems and the possibility that stablecoins could replace the current global foreign exchange (FX) market.

Can CRCL reclaim key levels?

Amid strong fundamentals growth, CRCL has reversed most of its late 2025 losses. Reclaiming the $125-$160 price range could effectively erase all the H2 2025 losses.

Source: CRCL price, TradingView

Meanwhile, the BTC recovery lifted other crypto stocks too, including Robinhood (Nasdaq: HOOD), Coinbase (Nasdaq: COIN), and Strategy (Nasdaq: MSTR). Notably, MSTR was up 14%, and COIN had recovered 22% over the past month.

But on a year-to-date (YTD) basis, Circle’s CRCL still outperformed them all. Despite the 150% upswing, the Wall Street analyst consensus rating for CRCL was a ‘HOLD’ with some projecting a price target of $145.

Source: Google Finance (as of March 17, Tuesday, GMT 10.00)

Final Summary

  • CRCL stock has recovered by 150% from the February low of $49, reversing all Q1 2026 losses.
  • Analysts cited strong USDC adoption and AI agentic payments as key catalysts behind the explosive run.

Пов'язані питання

QWhat is the percentage recovery of Circle's stock (CRCL) from its February lows, and what was the closing price on March 17th?

ACircle's stock (CRCL) has recovered by over 150% from its February lows of $49.9, and it closed at $125.83 on March 17th.

QAccording to analysts, what was a key driver behind CRCL's Q1 recovery besides Bitcoin's rebound?

AAnalysts singled out the growing adoption of Circle's stablecoin, USDC, as a key driver for CRCL's Q1 recovery.

QWhat milestone did the supply of USDC reach, and what was the percentage growth from February to the time of writing?

AThe supply of USDC hit a record $79 billion, marking a 13% increase from approximately $70 billion in February.

QWhat future application for stablecoins was cited by Citrini Research and is being bet on by Circle?

ACitrini Research theorized that AI agents will transact on stablecoin rails by 2028, and Circle is betting on AI agentic payment systems and the possibility that stablecoins could replace the global foreign exchange market.

QWhat is the Wall Street analyst consensus rating for CRCL stock, and what is one projected price target mentioned?

AThe Wall Street analyst consensus rating for CRCL was a 'HOLD', with some projecting a price target of $145.

Пов'язані матеріали

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.

marsbit42 хв тому

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

marsbit42 хв тому

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.

marsbit47 хв тому

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

marsbit47 хв тому

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.

marsbit47 хв тому

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

marsbit47 хв тому

Торгівля

Спот
活动图片