Ethereum price is trying to steady itself after a rough February, but the bigger question is whether this bounce has enough strength to push through the $2,500 ceiling.

At press time, ETH was trading near $2,050, up about 3% over the past 24 hours. The move extends a week-long rebound of roughly 9%. Even so, the token is still down 30% over the past month and sits nearly 58% below its August 2025 peak of $4,946.

February started with Ethereum (ETH) trading between $2,200 and $2,400 before sellers took control mid-month. The slide accelerated around Feb. 24–25, when the price dipped toward $1,800. Since then, buyers have stepped back in, lifting the price back above the $2,000 mark.

Volatility spikes to highest level since March 2025

Derivative data shows a notable shift in positioning. According to a Feb. 26 analysis by CryptoQuant analyst PelinayPA, funding rates had remained positive for an extended period earlier this year, indicating that long traders were paying shorts.

Despite that optimism, the price failed to build a consistent rally. More recently, when short positions grew and the price faced pressure, funding went sharply negative.

Binance, which has the biggest share of global derivatives liquidity, often sets the tone during liquidation waves. The short- to mid-term trajectory of Ethereum is often affected by changes in Binance funding.

Funding has now flipped back to positive. This indicates that there is less immediate downside pressure now that many short positions have been cleared. Positive funding, however, does not prove a long-term recovery. The market could experience a long squeeze if it rises too quickly.

In a separate report, analyst Arab Chain revealed that Ethereum’s 30-day realized volatility on Binance has climbed to roughly 0.97, its highest level since March 2025.

Such high volatility often precedes a significant directional move, but if buying and selling pressure is evenly distributed, it can also occur during a prolonged period of sideways trading.

Ethereum price technical analysis

From a chart perspective, ETH is still in a clear daily downtrend, marked by lower highs and lower lows. Price recently bounced after touching the lower Bollinger Band near the $1,850–$1,900 zone. It now trades around $2,050, below key resistance areas.

Immediate support sits near $2,000, followed by the recent low between $1,850 and $1,900. On the upside, supply is clustered around $2,130–$2,150, then $2,300–$2,350.

Because it corresponds with a previous breakdown area and has psychological weight, the $2,500 level continues to be the primary structural barrier. 

Momentum is improving but not yet decisive. Following a recovery from oversold conditions, the relative strength index is close to 44.

A sustained move above 50 would strengthen the case for a shift in momentum. Bollinger Bands are starting to narrow after widening during the selloff, suggesting a possible attempt at a breakout. 

For Ethereum to recover $2,500, it must clear the $2,200 area with substantial volume and maintain above $2,000 to form a higher low. The current move might turn out to be a relief bounce inside a bigger downward structure if there is no follow-through.

• Dogecoin price hovers near $0.10 amid fresh rejection above this level.
• Open interest has dropped below $1 billion.
• DOGE could drop to $0.08 if weakness intensifies.

Dogecoin’s latest price rally has hit a snag, with the meme coin slipping back under the key $0.10 threshold amid fading momentum in the meme coin sector.

On Thursday, February 26, 2026, DOGE hovered around $0.1004, clinging to modest daily gains after a volatile week that saw it dip as low as $0.0914 the previous day.

This retreat highlights persistent challenges for the meme-themed cryptocurrencies, once buoyed by celebrity endorsements but now grappling with broader market headwinds and technical barriers.

DOGE price retested highs above $0.10

Dogecoin briefly surged past $0.10 on Wednesday, fueled by a sharp rebound for Bitcoin and top altcoins.

Traders eyed momentum above the psychological level as a potential springboard for renewed interest, especially after DOGE touched $0.11 on February 25 before retreating.

However, the uptick proved short-lived, with selling pressure mounting as the token failed to sustain gains, retreating amid thinner trading volumes and scepticism over long-term catalysts.

A unique angle here is the role of retail investor fatigue.

On-chain metrics show smaller holders distributing positions after the spike, wary of the slide seen following Dogecoin price rallying to its peak in 2025.

CoinGlass data shows that open interest in Dogecoin futures has dropped to under $1 billion.

The dip has been progressive since the peak of over $5 billion in September 2025.

This shift highlights how community-driven hype, Dogecoin’s hallmark, is waning as macro factors overshadow viral buzz.

Dogecoin price analysis

Dogecoin is trading near $0.098 as of writing on Thursday, preserving about 4% of the advance from the prior session.

The slight dip from intraday highs aligns with the rejection at the upper boundary of a falling channel.

Dogecoin has also traded lower amid falling 50-day and 100-day SMAs.

Bulls, therefore, face the $0.10 and the SMA barriers as immediate resistance levels.

The daily MACD has climbed following a signal line rebound earlier in the week, pointing to budding bullish energy.

Buyers are also unwavering as RSI lingers near the 50 mark, hinting at neutral sentiment.

This means fresh gains could follow if buyers retake control.

Yet, a close below $0.10 could revive selling, targeting the February lows of $0.08 and exposing deeper corrections.

From a distinctive perspective, Dogecoin’s stall mirrors a “meme exhaustion pattern” seen in past cycles.

After quick pops, prices have often quickly pared gains.

With year-to-date declines persisting and Bitcoin’s surge also stalling, DOGE bulls need a decisive breakout to shift momentum.

Key Takeaways

• AI as the New Power User: Yat Siu posits that AI agents will replace humans as the primary on-chain executors, managing transactions and wallet security autonomously.
• The End of Complexity: By abstracting away seed phrases and gas fees, AI Agents remove the technical barriers currently preventing mainstream adoption.
• 2026 Inflection Point: Animoca forecasts a ‘Year of Utility’ where valuation models shift from speculation to functional usage within the Open Metaverse.

Uniswap price targets $4.55 prior breakdown level as traders position ahead of a governance vote that could expand fee burns and boost protocol revenue.

Uniswap (UNI) traded at $4.02 at press time, up about 10% in the past 24 hours. The token is trading near the top of its weekly range between $3.29 and $4.12.

UNI has gained 18% over the past week, showing a firm bounce from recent lows, though it is still 15% lower over the past month.

Spot trading volume jumped to $554 million, up 119% in one day. CoinGlass data shows futures volume climbing nearly 80% to $640.5 million, while open interest rose 15.2% to $285.6 million.

When both volume and open interest rise together, it usually means new positions are being opened rather than just shorts closing. 

Fee switch expansion adds direct value to UNI

Uniswap governance is advancing a proposal to widen its fee switch system. It follows the 2025 UNIfication rollout, which began charging protocol fees on Ethereum and introduced UNI token burns.

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Under the new proposal, protocol fees would also be applied across eight additional Layer 2 networks, including Arbitrum, Base, and Optimism. The plan would automate fee collection and send the proceeds back to Ethereum mainnet, where they would be used to buy and burn UNI tokens.

If approved, the expansion could lift annualized protocol revenue to about $61 million, up from $34 million. Part of swap fees would shift from liquidity providers to the treasury, directly linking trading activity to token supply reduction.

That dynamic tends to attract long-term holders because it means usage will translate into measurable value capture. Voting is split into two phases, with the first already live and the second scheduled between Feb. 27 and March 1.

Technical outlook: $4.60 in play if breakout holds

UNI has built a clear base around $3.70–$3.80. Price has held that zone multiple times, and recent candles show buyers stepping in on dips. With Bollinger Bands tightening, the market may be gearing up for a sharp move.

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Momentum has improved, with relative strength index pushing back above the midline. Price is also testing a descending trendline from December highs and pressing against short-term moving averages.

Volatility had tightened during consolidation, and the recent expansion in volume suggests the market is preparing for a larger move. A 20% advance from the $3.80 floor projects a target near $4.55–$4.60, an area that lines up with prior breakdown levels and moving average resistance.

A firm break above $4.20 would strengthen the case for that move. If the price slips below $3.70, the recovery attempt would weaken, opening the door to a return toward $3.30.

Over the past five years, enterprises have invested aggressively in AI pilots, generative tools, and automation platforms. Yet most organizations remain trapped in experimentation mode. AI dashboards exist. Chatbots are deployed. Predictive models operate separately across teams, but enterprise-wide financial impact remains limited. The issue is not technological maturity; it is strategic orchestration. Scaling AI requires governance architecture, value engineering discipline, capital alignment, and executive-level integration. This is where a specialized AI strategy consulting Company creates transformational leverage. Through structured AI strategy and consulting services, enterprises convert fragmented innovation into measurable performance, building an AI-native operating model that drives durable competitive advantage.

The Hard Truth: AI Adoption Is Not AI Transformation

We work with enterprises that proudly report “AI adoption.” But adoption is not transformation. Most organizations face:

• Disconnected AI initiatives across departments
• Undefined ROI accountability
• No centralized governance framework
• Underdeveloped AI roadmap sequencing
• Weak alignment with corporate strategy

The result? Incremental gains instead of exponential impact. An effective enterprise AI strategy does not deploy AI tools. It redesigns the enterprise around intelligence. That requires structured AI strategy consulting for enterprises, not experimentation.

What Enterprise AI Strategy Actually Means

An enterprise AI strategy is a capital allocation decision. It determines where intelligence will generate the highest economic return across the organization. It defines how AI investments translate into measurable growth, efficiency, and long-term competitive advantage.

• Where AI will drive margin expansion
• How predictive intelligence will compress decision cycles
• Which workflows will become autonomous
• How governance will mitigate regulatory exposure
• How workforce capability will evolve

AI cannot sit in innovation labs. It must shape financial planning, operational architecture, and strategic differentiation. This is the mandate of the high-level AI Strategic Advisory.

The Role of a Leading AI Strategy Consulting Company

As a top-tier AI strategy consulting Company, our approach is not technology-first. It is value-first. We engage across five strategic pillars:

1. Enterprise AI Maturity & Readiness Diagnostics

Before scaling, we assess:

• Data infrastructure robustness
• Model lifecycle governance maturity
• Security & compliance architecture
• Executive AI fluency
• Operational integration readiness

Without clear maturity and strategic alignment, scaling AI initiatives only amplifies inefficiencies.

2. Strategic AI Use Case Engineering

Not every AI initiative deserves capital. We prioritize use cases based on:

• EBITDA impact potential
• Strategic defensibility
• Competitive moat creation
• Implementation scalability
• Time-to-value acceleration

This precision separates high-performing enterprises from reactive adopters.

3. Structured AI Roadmap Development

A disciplined AI roadmap development Company sequences AI initiatives across a phased transformation:

Phase I: Value Capture

Automation, predictive analytics, cost compression.

Phase II: Strategic Differentiation

AI-driven product innovation, customer intelligence, and dynamic pricing.

Phase III: AI-Native Enterprise

Autonomous systems, real-time decision intelligence, predictive capital allocation.

Sequencing protects capital efficiency while maximizing compounded returns.

AI Strategy and Consulting Services: Beyond Implementation

Premium AI strategy and consulting services go far beyond deploying tools or building models. They align artificial intelligence with enterprise vision, financial performance, and long-term competitive positioning. Instead of focusing only on technical execution, they design the strategic, operational, and governance architecture required to scale AI responsibly and profitably. Premium AI strategy and consulting services integrate:

• Strategic advisory
• Governance architecture
• Financial modeling
• Operational redesign
• Continuous optimization

Most AI vendors deploy tools. We engineer transformation.

AI Value Engineering: The Discipline That Changes Everything

AI investment without value engineering is speculation. Our AI value engineering services are built around a rigorous AI value engineering framework that ensures:

• Every initiative maps to financial KPIs
• ROI is forecasted before deployment
• Workflow redesign unlocks AI leverage
• Performance dashboards track measurable gains

Through AI strategy and value engineering services, we help enterprises quantify:

• Revenue uplift
• Margin expansion
• Cost reduction
• Risk mitigation
• Productivity improvement

This is how AI becomes an earnings multiplier.

AI Business Strategy Services: Embedding Intelligence into Enterprise Growth

AI Business Strategy Services ensure that artificial intelligence is not treated as an operational add-on, but as a core driver of enterprise growth and competitive positioning. Instead of limiting AI to efficiency gains, these services integrate intelligence directly into high-impact strategic decisions.

This includes embedding AI into:

• Market expansion and competitive positioning strategies
• Customer lifetime value prediction and personalization models
• Supply chain resilience and demand forecasting frameworks
• Capital allocation and scenario simulation planning
• Enterprise-wide risk forecasting and mitigation systems

AI should not simply optimize existing workflows. It should challenge assumptions, unlock new revenue models, and shape the future direction of the organization.

The 2026 Enterprise AI Reality: What Leaders Must Prepare For

AI transformation is accelerating. We see five dominant trends shaping global enterprises:

1. AI-Native Operating Models

Organizations redesign workflows so that AI initiates decisions autonomously.

2. Generative AI and Structured Intelligence

Enterprises are combining LLM capabilities with proprietary data ecosystems to create strategic decision engines.

3. Regulatory Pressure Intensification

AI governance is becoming a board-level oversight priority.

4. Autonomous Supply Chain Orchestration

Predictive systems manage procurement dynamically.

5. AI-Driven Financial Simulation

Capital allocation is influenced by real-time scenario modeling.

A forward-looking AI Strategic Advisory partner ensures your enterprise is not reacting but leading.

Governance: The Competitive Signal Investors Watch

Scaling AI without governance creates:

• Regulatory exposure
• Ethical risk
• Brand vulnerability
• Investor skepticism

Advanced AI Consulting Services embed:

• Transparent model governance
• Ethical AI standards
• Compliance-by-design architecture
• Continuous audit mechanisms

Governance maturity is becoming a market differentiator.

AI Business Value Optimization: Driving Executive Accountability

Today’s C-suite no longer views AI as an innovation experiment; it is a performance mandate. Leadership teams increasingly demand clear financial transparency and measurable outcomes from every AI investment. They expect:

• Clearly quantified AI-driven ROI
• Direct margin impact attribution
• Risk-adjusted performance forecasting
• Measurable workforce productivity gains

Structured AI business value optimization transforms artificial intelligence into a board-level performance engine. It embeds AI metrics into financial reporting, strategic planning, and capital allocation decisions; shifting the conversation from technology spending to measurable enterprise performance and sustainable value creation.

Solving Enterprise-Level Challenges Through AI Strategy Consulting for Enterprises

Enterprise leaders do not struggle with ambition; they struggle with clarity, alignment, and execution discipline. That is where structured AI strategy consulting for enterprises becomes decisive.

We consistently address board-level concerns such as:

“Our AI investments lack measurable impact.”
We deploy structured AI value engineering services that connect every AI initiative directly to financial reporting, EBITDA contribution, and capital efficiency metrics.

“AI initiatives are fragmented across departments.”
We architect centralized enterprise AI strategy governance models that unify data, models, and accountability under a single transformation framework.

“We don’t know which AI initiatives deserve priority.”
Through disciplined sequencing led by an expert AI roadmap development Company, we identify high-leverage opportunities and phase investments for maximum compounded return.

“Regulatory uncertainty is increasing our exposure.”
We embed compliance-by-design architecture through advanced AI Strategic Advisory, ensuring governance maturity scales alongside innovation.

“We lack senior AI leadership internally.”
We provide executive-level AI strategy consulting for enterprises, equipping leadership teams with the frameworks, metrics, and oversight necessary to drive enterprise-wide transformation.

This is not technical assistance. This is enterprise reinvention through structured intelligence.

Why Strategic Timing Determines Market Leadership

AI advantage compounds over time. It behaves like a strategic flywheel; the earlier it is structured correctly, the faster it accelerates. When disciplined AI strategy and consulting services are deployed early:

• Data ecosystems mature faster and become proprietary assets
• Intelligence layers deepen with every operational cycle
• Decision velocity increases across the enterprise
• Competitive defensibility strengthens through accumulated insight

Organizations that delay structured AI transformation face widening capability gaps. Delay creates a structural disadvantage. Acceleration builds category leadership.

What Differentiates Elite AI Strategy Consulting Companies

Not all AI advisory firms operate at the same strategic depth. As AI implementation becomes increasingly accessible and technology tools commoditize, the true differentiator lies in strategic architecture, financial rigor, and enterprise-level execution capability. When evaluating a premium AI strategy consulting Company, enterprises should assess whether the firm brings:

• Advanced financial engineering capability – The ability to model AI investments against EBITDA impact, capital efficiency, and long-term value creation rather than surface-level ROI projections. 
• Deep governance architecture expertise – Experience embedding compliance, ethical AI standards, model transparency, and regulatory safeguards into system design from day one. 
• Cross-industry transformation depth – Proven experience scaling AI across diverse sectors, understanding both operational complexity and industry-specific regulatory environments. 
• Structured and repeatable AI roadmap development frameworks – A disciplined methodology for sequencing AI initiatives to maximize compounding returns while minimizing disruption. 
• Demonstrable AI business value optimization outcomes – Clear evidence of measurable financial impact, not just successful deployments.

AI implementation is increasingly standardized. Strategic AI transformation built on governance, economics, and long-term competitive positioning remains rare.

The Bigger Picture

Enterprise AI transformation is not achieved through isolated pilots or experimental deployments. It requires structured orchestration across governance, capital allocation, operational design, and measurable value realization. A specialized AI strategy consulting Company provides this architecture.

Through disciplined AI strategy and consulting services, advanced AI value engineering services, and integrated AI Business Strategy Services, organizations convert AI from technological capability into strategic dominance. The next competitive era will not reward experimentation; it will reward execution at scale.

Organizations that adopt a structured AI strategy today will secure tomorrow’s market leadership. As a premier AI strategy consulting Company, Antier designs enterprise-wide AI frameworks that align intelligence with financial and operational outcomes. Our expertise ensures AI initiatives are not just deployed, but systematically converted into measurable business impact and lasting competitive advantage.

Key Takeaways

• The Catalyst: Canton Network integration unlocks institutional RWA data streams for Chainlink.
• The Data: Grayscale’s GLNK fund now holds $61 million in assets, defying broader ETF outflow trends.
• The Setup: $LINK must hold $9.16 to validate the breakout from oversold conditions.

Centrifuge and Resolv said on Feb. 25 that they are deploying up to $100 million of JAAA, a tokenized AAA-rated credit fund, as leveraged collateral on Aave Horizon – marking decentralized finance’s (DeFi) largest real-world asset (RWA) loop trade to date.

Resolv – a protocol that maintains the USR stablecoin with a total value locked of $162 million – is adding JAAA (an on-chain version of Janus Henderson’s AAA-rated CLO investment fund) to its system using Centrifuge’s tokenization technology. Centrifuge currently has a TVL of $1.35 billion.

Instead of just holding the fund, Resolv will use JAAA as collateral inside Aave’s lending markets to generate yield and support its stablecoin. Aave is the largest DeFi protocol, with nearly $28 billion in total value locked, according to DeFiLlama, while Aave Horizon is its institution-focused deployment.

The move shows how tokenized assets are increasingly being used in real financial products rather than just existing on-chain. It also comes as the tokenized RWA market continues to grow, with distributed asset value now above $25 billion, up about 7% over the past month, according to RWA.xyz.

“Resolv allocating to JAAA and deploying it through Aave Horizon demonstrates the next phase of tokenization: utility at scale,” Nadim Chamoun, director of business development at Centrifuge Labs, told The Defiant.

Chamoun added that the strategy allows Resolv to manage risk more actively while earning the difference between traditional credit yields and on-chain borrowing rates.

For Resolv, the move is also part of a broader effort to diversify the sources of its returns. “Economically, diversification across markets makes clear sense for scalable capital allocators,” Tim Shekikhachev, co-founder of Resolv Labs, told The Defiant. “On-chain yields move with crypto leverage cycles, while global fixed-income markets are anchored in broader macro conditions.”

Shekikhachev added that when crypto rates fall, tokenized credit like JAAA can help balance returns.

“What’s finally unlocked now is that the full supply chain is functioning at scale: capital flows from Resolv USR, through Centrifuge’s tokenization infrastructure, into Aave Horizon’s leverage layer,” he said. “Ultimately, this ends up in AAA-rated assets managed by Anemoy and Janus Henderson, an industry leader in this segment. DeFi won’t replace traditional finance — it will scale by plugging into it.”

Key Takeaways

• The Catalyst: A sharp Bitcoin Rebound forced a short squeeze, reclaiming the critical $68,000 level after testing lows near $64,700.
• The Signal: Circle reported a 77% revenue jump, confirming massive Circle USDC expansion and deepening Market Liquidity.
• The Outperformer: NEAR Protocol surged 17% following the launch of ‘Confidential Intents,’ signaling a capital rotation into high-utility infrastructure.

In online crypto circles, a persistent debate has emerged around whether a quantitative trading firm could nudge Bitcoin’s price at the moment U.S. markets open. Proponents point to a recognizable 10:00 a.m. Eastern Time pattern as potential evidence of coordinated selling, while critics caution that such a signal is not definitive proof of manipulation and may reflect broader market mechanics. The discussion intensified a day after a court-appointed administrator overseeing Terraform Labs’ affairs filed a suit against Jane Street, alleging insider trading tied to Terra’s May 2022 collapse. The intersection of high-speed trading, ETF liquidity, and opaque hedging strategies has kept traders watching the clock as BTC moves through daily cycles.

Key takeaways

• Allegations focus on a recurring 10:00 a.m. ET window at the market open, but analysts say this does not constitute conclusive manipulation or a sole driver of BTC’s price trajectory.
• Public filings show Jane Street’s exposure to BlackRock’s IBIT ETF, alongside stakes in Bitcoin mining firms, suggesting hedging and liquidity strategies rather than a simple directional bet.
• Industry voices argue that a single institution cannot control a global, liquid market as fragmented as Bitcoin, even if some trading strategies amplify volatility around open hours.
• Delta-neutral approaches—holding spot exposure while selling futures—are cited as a common method for capturing spreads rather than betting on direction, according to market observers.
• The discourse features a mix of on-chain data, trading analytics, and public posts from market observers, underscoring the complexity of disclosures and how net exposure can be obscured.
• Contextual factors such as geopolitical risk and competition for investor attention from AI-related equities are cited as broader drivers of BTC price moves beyond any single firm’s activity.

Tickers mentioned: $BTC, $IBIT

Sentiment: Neutral

Market context: The dialogue unfolds amid a broader crypto environment characterized by liquidity fluctuations, evolving ETF dynamics, and ongoing regulatory and macro influences shaping how traders price risk and opportunities.

Why it matters

The debate touches on the core questions facing crypto markets: how liquidity, disclosure, and algorithmic trading intersect with real-world price discovery. If a large player can influence the clock at which liquidity sweeps occur or how efficiently a spot market absorbs ETF-related flows, that could have implications for price integrity and market education. Yet the consensus among many analysts is that Bitcoin’s price formation remains a product of multiple forces, including macro risk appetite, capital allocation shifts, and competitive attention toward AI-driven tech and growth narratives.

At stake is trust in market transparency. For traders, the issue highlights the importance of understanding how publicly reported positions, hedges, and complex derivatives can mask net exposure. For regulators and exchanges, it underscores the need for clear, timely disclosures that help market participants distinguish legitimate liquidity activity from attempts to edge the price. For investors, the episode reinforces a prudent approach: interpret open-hour moves in the context of the broader market regime rather than attributing them to a single actor.

The discourse also intersects with ongoing legal and regulatory developments. The Terraform administrator’s lawsuit against Jane Street and the ongoing scrutiny of ETF structures like IBIT keep the conversation anchored in concrete questions about governance, disclosure requirements, and the boundaries of high-frequency market making in a frontier asset class. While proponents of a conspiracy narrative may highlight specific posts or data points, skeptics point to a broader pattern: markets are influenced by a constellation of participants with diverse strategies, and attribution to one firm oversimplifies the dynamics at play.

What to watch next

• Updates in the Terraform-related litigation against Jane Street, including any new filings or court rulings that may illuminate insider-trading claims.
• New or amended 13-F filings from Jane Street that shed light on hedging strategies, including positions in IBIT and mining-related equities, and any disclosed derivatives that could affect net Bitcoin exposure.
• On-chain and market data around the 10:00–10:30 a.m. ET window to assess whether any statistically significant patterns persist in the near term.
• Regulatory or industry guidance on disclosure practices for large ETF components and liquidity providers that could affect how market participants interpret “hidden” exposure.
• Monitoring broader market signals—geopolitical developments, liquidity conditions, and AI-sector performance—that could influence Bitcoin independently of any singular trading desk.

Sources & verification

• Court-appointed administrator filing related to Terra/Labs and Jane Street, alleging insider trading tied to the May 2022 collapse.
• Jane Street’s 13-F filings showing holdings in BlackRock’s IBIT ETF and stakes in Bitcoin mining companies such as Bitfarms, Cipher Mining, and Hut 8.
• Public posts and commentary from market observers, including Bechler’s discussions on 10:00 a.m. ET moves and the contention that IBIT-related hedging could conceal net exposure.
• CryptoQuant head of research Julio Moreno’s analysis on whether the described activity is unique to a single firm or part of delta-neutral trading patterns commonly used to capture spreads.
• Industry analysts’ assessments of whether a single actor can meaningfully drive BTC price given the structure and depth of the market, including critiques of the “10 a.m. dump” narrative by researchers such as Alex Krüger.

Market reaction and key details

Bitcoin (CRYPTO: BTC) has long been a magnet for debate over who moves the market and when. In recent weeks, observers have spotlighted a recurring pattern that some traders interpret as a 10:00 a.m. ET “dump” coinciding with the U.S. market open. Proponents of the theory argue that a firm with deep liquidity, such as Jane Street, could deploy algorithmic sales to reap benefits from ETF inflows and to acquire spot Bitcoin at a discount on the open. A prominent critic of the narrative, however, notes that a single actor is unlikely to set the tone for a market as diffuse as Bitcoin’s, where liquidity is drawn from a wide array of exchanges and participants across multiple jurisdictions.

One thread of the debate centers on Jane Street’s disclosed exposure to the IBIT ETF, alongside positions in mining-related equities. Bechler, a crypto influencer, suggested that if Jane Street carries roughly $790 million in IBIT, the actual net Bitcoin exposure could be largely hedged away, masked by options and futures combinations rather than a straightforward long or short bet. This line of reasoning emphasizes that public filings reveal only a fragment of a much larger, more complex risk posture, where hedges might offset or even invert visible positions.

Yet others push back on the idea that the activity is unique to Jane Street. CryptoQuant’s Julio Moreno cautioned that many funds employ delta-neutral strategies—buying spot exposure while selling futures—to capture spreads without committing to a directional bet. In practice, these maneuvers can appear as divergent price actions around the open while serving to maintain neutral exposure in volatile markets. Moreno’s observations underscore a broader point: the mechanics of hedging frequently blend with price movement in ways that are not easily ascribed to a single firm’s choice of timing or size.

In the eyes of some researchers, even a credible pattern around the open does not translate into a bear-market engine powered by one institution. Nick Puckrin of Coin Bureau argued that Bitcoin’s price dynamics are inherently multifactorial, and a solitary actor—even one as large as Jane Street—cannot unilaterally dictate longer-term moves. He framed the conversation as part of a more nuanced reality: price action is shaped by geopolitical risk, global liquidity conditions, and the ongoing competition for attention among high-growth tech sectors, including AI.

As the market digests these viewpoints, the intersection of legality, disclosure, and market structure remains a live area of inquiry. The Terra-related lawsuit and the ongoing discourse about ETF flows highlight the need for transparency in how large players interact with both spot markets and derivative instruments. The broader takeaway is not a verdict on manipulation, but a reminder that the Bitcoin market’s depth and fragmentation make it resistant to easy explanations or simple villains.

[PRESS RELEASE – San Francisco, CA, February 26th, 2026]

SolanaCDN delivers 3.8x faster shred propagation through a global mesh of 35,000+ nodes, provided as a public good for the Solana network

Pipe Network today announced the launch of SolanaCDN, a free, open-source Solana validator client with an integrated CDN acceleration layer. Built as a fork of Anza’s Agave, SolanaCDN gives every Solana validator access to faster shred propagation through Pipe’s global network of 35,000+ PoP (Point-of-Presence) nodes.

The client and CDN layer are both completely free. Pipe Network is providing SolanaCDN as public good infrastructure for the Solana ecosystem.

The problem SolanaCDN solves

Validator performance on Solana is heavily influenced by network geography. Validators closer to block producers see shreds earlier, vote sooner, and earn more rewards. Validators in less connected regions face slower propagation, missed votes, and reduced leader slot revenue regardless of their hardware.

SolanaCDN addresses this by giving validators a second, faster path for shred delivery alongside native gossip. Shreds and vote packets route through Pipe’s global mesh, which continuously measures every network path and routes traffic along the fastest available route in real time.

Native gossip still runs underneath. SolanaCDN adds a parallel fast lane.

Performance

SolanaCDN delivers 3.8x faster propagation than standard Turbine, with a P50 cross-region latency of approximately 78ms compared to the roughly 300ms baseline on standard gossip.

The client also ships with Pipe-built optimizations available out of the box before the CDN layer is enabled: optimized shred coalescing for leaders (Fast Shreds), snapshot downloads from Pipe’s global network, and restore progress with real-time ETAs during validator catchup.

Public good infrastructure

Faster propagation is a network effect. Every validator running SolanaCDN improves shred delivery globally, which means faster block finalization, fewer forks, and fewer missed slots across the entire Solana network.

“Validator performance shouldn’t be determined by geography,” said David Rhodus, CEO of Pipe Network. “SolanaCDN gives every validator access to the same fast infrastructure. The more validators that run it, the faster Solana gets for everyone.”

Technical design

SolanaCDN is a fully compatible Agave fork. Validators can install it as a drop-in replacement for their existing client. The CDN layer is optional, activated with a single configuration flag, and is non-consensus by design. It does not modify block production, consensus logic, leader scheduling, or voting rules. All CDN operations are non-blocking and fail-safe. If the CDN layer is unavailable, the validator continues operating normally.

Built-in Prometheus metrics and CDN-versus-gossip race data give operators full visibility into performance changes in their environment.

Availability

SolanaCDN is available now. The source code is published on GitHub and the client is ready to run on Solana mainnet-beta.

Website: https://solanacdn.com

GitHub: https://github.com/pipenetwork/agave-solana

About Pipe Network

Pipe Network is a global edge infrastructure company built on Solana. The network operates 35,000+ hyperlocal PoP nodes globally, providing distributed storage with fast reads and real-time data delivery. Pipe’s overlay network tracks latency, loss, and jitter across every path in real time and routes traffic along the fastest one.