Blockonomi

Key Highlights

IonQ achieved a groundbreaking 99.99% fidelity world record and targets millions of qubits by 2030.

IBM earned a “Perfect 10” Smart Score rating on TipRanks with Moderate Buy consensus and analysts projecting 40.49% upside.

Microsoft’s Majorana 1 chip powers chemistry research applications and carries a Strong Buy rating with 56.62% potential upside.

Alphabet’s Google released research suggesting blockchain encryption could be compromised by quantum algorithms as early as 2029.

Industry analysts forecast the quantum computing sector will surge from $1.42 billion in 2024 to $4.24 billion by 2030.

Quantum computing has transitioned from theoretical research into tangible commercial applications at an accelerating pace. For investors monitoring this emerging sector, three companies emerge as particularly compelling: IonQ, IBM, and Microsoft.

The quantum computing industry reached a valuation of $1.42 billion in 2024. Market researchers anticipate this figure will climb to $4.24 billion by the decade’s end. Such explosive expansion is attracting enterprise clients, lucrative government partnerships, and substantial capital investments.

IonQ: Prioritizing Precision Over Speed

IonQ has established itself as the premier pure-play quantum computing enterprise. The company’s technology recently achieved an unprecedented 99.99% fidelity rating in industry-standard benchmarking tests—a global achievement.

Precision represents the fundamental obstacle preventing quantum computing’s mainstream adoption. Systems plagued by frequent computational errors cannot deliver reliable results for practical applications.

IonQ’s approach centers on trapped ion technology. This methodology prioritizes exceptional accuracy over raw processing velocity, contrasting sharply with the superconducting architectures favored by competitors.

The organization’s 2026 roadmap includes deploying a 256-qubit architecture. Looking further ahead, IonQ aims to construct million-qubit systems by 2030. Successfully achieving these milestones while maintaining current accuracy standards could position the company as dominant in precision-dependent sectors.

IonQ’s quantum systems are accessible through partnerships with Amazon Web Services, Microsoft Azure, and Google Cloud. The company currently commands approximately $11 billion in market capitalization.

IBM: Bridging Quantum and Traditional Computing

IBM has charted a distinctive strategic course. Instead of solely pursuing qubit quantity, the tech giant emphasizes integrating quantum capabilities into established enterprise infrastructure.

IBM’s development strategy centers on hybrid architectures where conventional CPUs, GPUs, and quantum processors operate cohesively. Industry experts consider this integration model the most viable pathway toward immediate commercial viability.

TipRanks analysts awarded IBM the platform’s maximum Smart Score of 10 out of 10. The stock maintains a Moderate Buy consensus rating, with Wall Street projecting 40.49% appreciation potential.

IBM leverages its extensive enterprise computing heritage and established client relationships, providing immediate market access for quantum services. The company’s development pipeline emphasizes enhanced qubit coherence and sophisticated error correction protocols.

Microsoft: Strategic Innovation with Transformative Potential

Microsoft has maintained a relatively understated public profile regarding quantum achievements compared to rivals like Google or IonQ. Nevertheless, its Majorana 1 quantum processor is delivering measurable outcomes.

The processor currently facilitates advanced chemistry research, enabling quantum simulations of intricate molecular behaviors that exceed classical computing capabilities. CEO Satya Nadella has characterized quantum technology as the forthcoming catalyst for cloud computing evolution.

Microsoft’s research concentrates on topological qubit architectures—a forward-looking methodology promising superior stability compared to existing quantum systems. The company’s Azure Quantum platform seamlessly embeds quantum capabilities into corporate computing environments.

Wall Street analysts assign Microsoft a Strong Buy recommendation with 56.62% upside potential. The stock holds a Smart Score of eight out of ten on TipRanks.

Alphabet’s Google division released 2025 research demonstrating an algorithm potentially capable of compromising contemporary blockchain encryption protocols in minutes—possibly operational by 2029. This revelation emphasizes the remarkable velocity of quantum computing advancement.

The post Top Quantum Computing Stocks for 2026: IonQ, IBM, and Microsoft Lead the Charge appeared first on Blockonomi.

Key Points

Authorities apprehended a 20-year-old suspect following an incendiary attack on Sam Altman’s San Francisco residence early Friday morning

An exterior gate caught fire from the explosive device, though no casualties were reported

Approximately 60 minutes after the initial incident, the individual made threatening statements about burning OpenAI’s Third Street facilities

According to OpenAI representatives, structural damage remained “minimal” and San Francisco operations continued without disruption

The incident occurred shortly following a comprehensive New Yorker exposé questioning Altman’s leadership credibility

Law enforcement officials arrested a suspect in his early twenties on Friday following an incendiary assault on the residence of OpenAI’s chief executive, Sam Altman, in San Francisco, coupled with menacing statements directed at the artificial intelligence company’s main offices.

OpenAI says its CEO Sam Altman was targeted after someone threw a Molotov cocktail at his home

The company confirmed the suspect is in custody pic.twitter.com/FS5tVbx8S6

— Dexerto (@Dexerto) April 10, 2026

The assault took place during the early morning hours, specifically around 4 a.m. Pacific time, in San Francisco’s prestigious Russian Hill district. The individual launched an improvised incendiary weapon at Altman’s property, igniting flames at an external gate structure.

Fortunately, no individuals sustained injuries during the incident. Representatives from OpenAI acknowledged the attack through an official statement provided to Forbes, characterizing the resulting property damage as “minimal.”

Law enforcement personnel responded to a subsequent emergency call approximately one hour following the initial attack. An individual had issued verbal threats about setting ablaze a structure located on the 1400 block of Third Street. The artificial intelligence company maintains its primary headquarters at 1455 Third Street.

Authorities determined the person responsible for the threats matched the description of the individual from the earlier residential attack. The suspect was taken into custody with criminal charges currently under consideration. Investigative procedures remain active.

OpenAI distributed an internal communication to employees acknowledging both security incidents. The organization confirmed all San Francisco facilities maintained normal operations on Friday, noting enhanced law enforcement and private security measures around company properties.

“During the early hours today, an individual threw a Molotov cocktail targeting Sam Altman’s residence and subsequently issued threats directed at our San Francisco headquarters location,” a company representative stated. “We are grateful that no injuries occurred.”

CEO’s Public Statement Following the Incident

Altman published remarks regarding the attack through his personal blog platform on Friday. He recognized that public skepticism surrounding the artificial intelligence sector frequently stems from “genuine apprehension about the extraordinarily significant implications of this technology.”

“As we engage in this critical discussion, we must reduce inflammatory language and aggressive approaches and aim for fewer explosions affecting fewer residences, both metaphorically and in reality,” he stated.

The violent incident transpired merely days following the New Yorker’s publication of an extensive year-long investigative report examining Altman. The journalistic piece characterized the executive as an ethically questionable figure leading the competitive AI development landscape.

Mounting Scrutiny on OpenAI’s Leadership

The timing coincides with escalating public scrutiny and legal challenges confronting Altman. Elon Musk has initiated legal efforts aimed at removing Altman from his OpenAI position based on allegations of fraudulent conduct.

OpenAI representatives confirmed complete collaboration with ongoing law enforcement inquiries. The San Francisco Police Department indicated that formal charges against the detained individual remained pending as of Friday evening.

The suspect successfully accessed Altman’s residential property without documented security intervention prior to deploying the incendiary device. Law enforcement has withheld public disclosure of the suspect’s identity or any potential motivations behind the attacks.

The post OpenAI CEO Sam Altman’s Residence Hit by Molotov Cocktail Attack in San Francisco appeared first on Blockonomi.

Key Takeaways

Citi Research moved six software companies from Buy to Neutral ratings: Similarweb, Docusign, Autodesk, Nice, CCC, and Veeva

Price target reductions exceeded 40% for multiple companies in the downgrade sweep

Piper Sandler identifies Anthropic’s Claude Managed Agents as existential risk to legacy software providers

Investment firms pivot toward cloud hyperscalers Microsoft and Oracle instead of traditional enterprise software

CNBC’s Jim Cramer confirms hardware-over-software thesis has returned with staying power

In a sweeping move that sent shockwaves through technology markets, Citi Research slashed ratings on six application software companies Friday, moving them from Buy to Neutral. The affected firms include Similarweb, Docusign, Autodesk, Nice, CCC Intelligent Solutions, and Veeva Systems. Share prices declined across the board following the announcement.

Tyler Radke, analyst at Citi, attributed the downgrades to an absence of meaningful near-term catalysts combined with mounting evidence that artificial intelligence is beginning to erode traditional software revenue models. “While we view most of these as quality enterprises potentially well-positioned for the future, they lack compelling 12-month drivers,” Radke explained in his research note.

The firm simultaneously delivered brutal price target cuts. Docusign’s target plummeted from $99 to $50. Veeva experienced a reduction from $291 to $176. Similarweb absorbed the most severe blow, with its target collapsing from $8.50 to just $3.

Radke highlighted a troubling competitive dynamic: privately-held AI enterprises are projected to capture more than $100 billion in incremental revenue in upcoming years. This dwarfs the estimated $50 billion expected from conventional application software providers. Additional headwinds include escalating software optimization expenses and accelerating vendor consolidation trends.

Anthropic’s Agent Platform Intensifies Industry Concerns

Piper Sandler analyst Billy Fitzsimmons identified another catalyst accelerating the software sector’s decline. Anthropic recently unveiled Claude Managed Agents, a preconfigured, customizable agent framework engineered for extended-duration and asynchronous workflows.

Fitzsimmons noted this development fuels apprehension that Anthropic’s agent technology will directly challenge solutions developed by incumbent software vendors. He anticipates sustained negative sentiment toward the software industry extending through year-end at minimum.

Piper Sandler reduced ratings on multiple sector names while expressing preference for businesses that monetize AI computational resources directly. The firm highlighted Microsoft and Oracle as preferred investments, emphasizing their Azure and Oracle Cloud Infrastructure platforms respectively.

Microsoft currently trades at a forward price-to-earnings multiple of 20x based on 2027 projections while producing $77.4 billion in levered free cash flow. Despite a 27% contraction over the preceding six months, Piper Sandler characterizes the valuation as attractive.

Infrastructure Players Benefit from Software Sector Exodus

CNBC’s Jim Cramer drew attention to the expanding performance gap between hardware and software equities Thursday. He observed that the “buy hardware, sell software” positioning that dominated early 2026 trading has made a decisive comeback.

Salesforce declined nearly 3% while Adobe surrendered approximately 4% Thursday. The IGV software ETF, serving as a primary sector benchmark, tumbled more than 4%. CrowdStrike dropped 7.5% despite its cybersecurity focus, primarily due to its inclusion in the fund.

Conversely, hardware manufacturers rallied. Marvell Technology and Intel each advanced close to 5%. Corning, a supplier of data center materials, appreciated 2.85%.

Cramer characterized the dynamic as AI infrastructure providers commanding premium valuations while enterprise software faces treatment as a contracting industry. He suggested this pattern shows limited signs of reversing soon.

Piper Sandler separately highlighted Global-e Online as a favored selection. The company’s business model ties to ecommerce transaction volumes rather than software license counts, with management projecting 29% revenue expansion this year.

The post Software Sector Under Siege: Why Wall Street Is Sounding the AI Alarm appeared first on Blockonomi.

Key Points

Super Micro Computer shares rallied approximately 9% Friday following the Gold Series server announcement.

The new Gold Series features more than 25 ready-to-deploy server configurations designed for AI, cloud computing, and data storage applications.

All systems ship within a three-business-day window and arrive fully equipped with processors, graphics cards, RAM, and storage drives.

Company CEO Charles Liang emphasized the platform reduces delivery timelines and speeds up customer implementation.

Despite Friday’s rally, SMCI remains down 18.3% in 2025 and trades 58.3% beneath its 52-week peak of $60.71.

Super Micro Computer (SMCI) posted a roughly 9% gain Friday after introducing its Gold Series enterprise server portfolio, a ready-to-ship platform designed to accelerate deployment timelines for business clients.

The Gold Series encompasses more than 25 distinct server models selected from Super Micro’s current product catalog. The lineup includes both single-socket and dual-socket architectures, each engineered for artificial intelligence, cloud infrastructure, and storage operations.

Every configuration arrives fully integrated with central processing units, graphics processing units, memory modules, and storage components. According to the company, all orders leave distribution centers within three business days of placement.

CEO Charles Liang positioned the initiative as a velocity-focused strategy. “We make our industry-leading server portfolio available to our customers even faster, significantly shortening lead times and accelerating their time-to-online,” he stated.

Another Significant Swing for a High-Volatility Equity

SMCI has experienced 48 single-day movements exceeding 5% during the past twelve months. Friday’s advance continues this established volatility pattern — notable in magnitude, yet not necessarily indicative of shifting sentiment on the company’s fundamental outlook.

The most recent substantial decline occurred eleven days prior when shares dropped 5.4%. That selloff coincided with escalating geopolitical tensions that pushed both the Dow Jones Industrial Average and Nasdaq Composite into correction territory, each declining over 10% from recent peaks. Climbing crude oil prices and inflation concerns triggered widespread equity market weakness.

Friday’s positive session doesn’t reverse those losses. SMCI continues trading down 18.3% year-to-date.

Current Valuation Context

Trading at $25.30 per share, SMCI sits 58.3% below its 52-week high of $60.71, established in July 2025.

Despite recent volatility, investors with longer holding periods maintain substantial appreciation. A $1,000 investment in Super Micro five years ago would currently be valued at approximately $6,321.

The Gold Series introduction arrives as Super Micro expands its presence in the enterprise artificial intelligence infrastructure market. The emphasis on rapid fulfillment and turnkey configurations indicates the company is pursuing customers prioritizing deployment speed and operational simplicity over customized solutions.

The company did not release revised revenue projections or earnings estimates alongside Friday’s product unveiling.

The post Super Micro (SMCI) Stock Surges 9% on Gold Series AI Server Launch appeared first on Blockonomi.

Key Takeaways

Nasdaq-100 will add SanDisk (SNDK) and remove Atlassian (TEAM) effective April 20, 2026

Wall Street analysts boost price objectives: Jefferies to $1,000, Bernstein to $1,250

The memory stock has exploded 2,640% in twelve months, hovering near $855 peak

Company commits $1 billion to Nanya Technology partnership, securing roughly 3.9% ownership

Strengthening NAND pricing and artificial intelligence applications drive bullish outlook

 

SanDisk (SNDK) has secured a coveted spot in the Nasdaq-100, marking a significant milestone for the memory storage giant. The exchange operator confirmed Friday evening that SanDisk will join the prestigious index when markets open on April 20, 2026, taking the place currently held by Atlassian (TEAM).

This elevation places SanDisk within the exclusive group of the Nasdaq’s 100 biggest non-financial corporations—a designation that carries substantial market implications.

The Nasdaq-100 serves as the foundation for more than 200 investment vehicles, including the widely-held Invesco QQQ Trust. These tracking products collectively manage north of $600 billion worldwide, ensuring that index rebalancing events generate significant automated capital flows.

For SanDisk, inclusion means guaranteed inflows as index-tracking funds recalibrate their portfolios. Conversely, Atlassian will experience programmatic selling as it exits the benchmark. The software collaboration platform makes way as the index composition tilts toward semiconductor and infrastructure companies.

SanDisk’s addition reflects the existing Nasdaq-100 selection criteria, which remain active until April 30, 2026. Market participants are closely monitoring anticipated weighting adjustments before the April 20 implementation.

Wall Street Elevates Expectations

The index announcement arrives amid intensifying bullish sentiment from equity research teams covering SNDK.

Jefferies upgraded its valuation target from $700 to $1,000 while maintaining its Buy recommendation. The investment bank highlighted ongoing customer contract discussions and artificial intelligence infrastructure buildout as factors supporting continued NAND pricing strength and upward earnings adjustments before SanDisk’s quarterly report scheduled for April 30.

Jefferies analyst Blayne Curtis constructed the four-figure price objective using a 10x earnings multiple against projected 2028 earnings per share of $95.26. Curtis also identified forthcoming QLC eSSD deliveries to two major cloud providers as potential catalysts for expanding data center market position.

Bernstein took an even more aggressive stance, escalating its target from $1,000 to $1,250. The firm retained its Outperform rating, emphasizing that NAND flash pricing has exceeded prior expectations as the primary justification.

Morgan Stanley reaffirmed its Overweight stance after recent volatility in semiconductor memory equities, characterizing the pullback as routine consolidation rather than fundamental deterioration. BofA Securities maintained its Buy rating with a $900 valuation, highlighting robust appetite from hyperscale cloud operators and AI inference workloads.

Remarkable Performance and Strategic Investments

SNDK has delivered extraordinary returns. The shares have rocketed 2,640% during the trailing twelve months and currently change hands around $851.77, marginally beneath the 52-week peak of $855. InvestingPro’s Fair Value framework suggests current pricing exceeds intrinsic value.

Consensus estimates project fiscal 2026 earnings per share reaching $42.37, with profitability expected throughout the current year.

On the strategic front, SanDisk disclosed a $1 billion capital commitment to Nanya Technology via private placement. The transaction delivers approximately 139 million Nanya shares to SanDisk, equating to roughly 3.9% of the memory manufacturer’s equity.

SanDisk executives have not issued revised financial guidance in recent investor communications.

The post SanDisk (SNDK) Gains Nasdaq-100 Entry After 2,640% Rally as Wall Street Upgrades Pour In appeared first on Blockonomi.

Key Highlights

Citigroup downgraded DocuSign from Buy to Neutral, reducing its price target dramatically from $99 to $50

Shares declined approximately 6% following the announcement, continuing a multi-day slide

The company’s fiscal 2026 revenue expansion of only 8% raised valuation concerns

Emerging AI-powered competitors pose potential disruption threats to traditional SaaS business models

Year-to-date performance shows DOCU down approximately 34.5%, trading more than 54% below its peak

DocuSign experienced a particularly challenging week as shares tumbled following a significant analyst downgrade. On April 10, Citigroup shifted its rating on the digital signature provider from Buy to Neutral while simultaneously slashing its price objective from $99 down to $50. The dramatic reduction caught investor attention and triggered immediate selling.

The downgrade centered on a fundamental concern: revenue expansion. DocuSign reported fiscal 2026 revenue growth of merely 8%. For a technology company that historically traded at premium multiples, such modest single-digit expansion creates a challenging narrative for investors anticipating stronger performance.

Citi’s research analyst emphasized that the decelerated growth trajectory makes the stock’s previous valuation levels difficult to support. The revised $50 price objective signals a substantially more conservative outlook on the company’s near-term potential.

The Citigroup rating cut didn’t occur in isolation. One trading session prior, DOCU shares had already declined 4.4% as market-wide nervousness intensified.

Some of that previous session’s weakness stemmed from geopolitical developments — news surrounding a ceasefire collapse in Middle Eastern regions unsettled markets and prompted investors to reduce exposure to growth-oriented technology names.

However, another catalyst hit particularly close to the software sector. Anthropic’s introduction of Managed Agents — autonomous artificial intelligence systems capable of executing sophisticated, multi-stage workflows — sparked concerns that conventional SaaS applications might face meaningful competition from AI-first platforms.

Artificial Intelligence Rivals Create Uncertainty

The concern carries substance. Should AI-powered agents successfully replicate functionality currently delivered by specialized software platforms like DocuSign, the total addressable market for such solutions could contract significantly over time.

Notable short seller Michael Burry contributed to the apprehension with a social media comment (later deleted) suggesting Anthropic[[/LINK_END_3]] was undermining Palantir’s business. Though the post was swiftly removed, market participants took notice — amplifying broader concerns regarding established SaaS providers.

It’s notable that DOCU has experienced 16 separate trading sessions with single-day price movements exceeding 5% throughout the past year. The equity clearly responds sharply to developments, with investors rapidly adjusting their valuations.

Current Trading Position

At a price of $42.49 per share, DocuSign currently trades 54.7% beneath its 52-week peak of $93.84, which the stock reached in June 2025.

Since the beginning of the calendar year, shares have declined approximately 34.5%. That represents a substantial contraction in barely more than a fiscal quarter.

For perspective: an investor who allocated $1,000 to DocuSign stock five years ago would currently hold a position valued at roughly $199.

The technical analysis also presents challenges. Daily trading volume has averaged north of 5 million shares, while technical momentum indicators currently flash a Sell signal.

The company’s market capitalization now stands at approximately $8.86 billion, representing a meaningful decrease from levels reached during periods of stronger growth expectations.

Citigroup’s $50 price objective represents the most recent Wall Street analyst adjustment for the security.

The post DocuSign (DOCU) Stock Plunges After Citigroup Slashes Rating and Price Target appeared first on Blockonomi.

Key Takeaways

Zoom (ZM) finished Thursday’s session down 5.7% at $79.24, significantly worse than the S&P 500’s modest 0.11% decline

Enterprise software sector weakness stemmed from concerns that AI agents from Anthropic and OpenAI could threaten traditional business models

Year-to-date, ZM has declined 6.8% and currently trades 19.3% beneath its 52-week peak of $96.22

Analysts anticipate EPS of $1.41 for the coming quarter, representing a 1.4% year-over-year decline, while revenue is expected to reach $1.22 billion

The stock trades at a forward P/E of 14.32, notably below the industry benchmark of 17.88

Zoom (ZM) experienced significant selling pressure on Thursday, shedding 5.7% to settle at $79.24. This steep decline stood in stark contrast to broader market performance — the Nasdaq climbed 0.35% while the S&P 500 edged down a mere 0.11%.

The weakness wasn’t isolated to Zoom alone. Enterprise software stocks across the board faced substantial headwinds as market participants grew increasingly anxious about emerging managed AI agents developed by companies like Anthropic and OpenAI. The fundamental concern centers on a simple question: if AI agents can autonomously perform functions currently handled by enterprise software platforms, what happens to the sector’s pricing power and long-term viability?

Zoom found itself swept up in this broader industry downdraft. Beyond sector-wide pressures, the video communications platform continues wrestling with its own unique challenges — persistent competitive threats and lingering uncertainty about sustainable growth trajectories as pandemic tailwinds fade into memory.

Despite Thursday’s setback, a longer view reveals more encouraging momentum. Over the preceding 30 days, ZM climbed 12.13%, substantially outpacing both the Computer and Technology sector’s 0.88% advance and the S&P 500’s 0.51% uptick. While Thursday’s decline put a dent in that rally, it didn’t completely reverse the recent gains.

It’s worth noting that volatility of this magnitude remains relatively uncommon for Zoom. Throughout the past year, the stock has registered just five daily moves exceeding 5%. When such pronounced swings occur, they typically signal meaningful shifts in market sentiment.

Earnings Performance and Analyst Expectations

The most recent comparable move came five months earlier — but in the opposite direction. ZM surged 13.5% following third-quarter results that exceeded Wall Street expectations on both revenue and earnings. The company posted $1.23 billion in revenue against a consensus estimate of $1.21 billion, marking 4.4% year-over-year growth. Adjusted earnings per share reached $1.52, topping analyst projections of $1.44. Management also boosted full-year adjusted EPS guidance to a midpoint of $5.96.

Those solid results provided meaningful support for the stock. Thursday’s reversal suggests investors are once again questioning the durability of that positive momentum.

Looking forward, Wall Street consensus calls for earnings per share of $1.41 in the upcoming quarter — representing a 1.4% contraction versus the prior-year period. Revenue projections stand at $1.22 billion, implying 4.16% year-over-year expansion. For the full fiscal year, analysts are modeling $5.87 in EPS and $5.06 billion in total revenue.

From a valuation perspective, ZM appears attractively priced. The forward price-to-earnings ratio stands at 14.32, meaningfully below the sector average of 17.88. However, the price-to-earnings-growth (PEG) ratio paints a less compelling picture at 3.23 versus an industry norm of 1.0 — indicating skepticism about whether anticipated earnings expansion warrants the current valuation.

Technical Position and Analyst Ratings

From a year-to-date perspective, ZM has surrendered 6.8%. Trading at $79.24, the stock remains 19.3% below its 52-week high of $96.22, established in January 2026.

Zoom currently carries a Zacks Rank of #3 (Hold), with consensus earnings estimates holding steady over the past month.

The Internet – Software industry occupies the 95th position among the 250-plus industries monitored by Zacks, landing it in the top 39% of all tracked sectors.

The post Zoom (ZM) Stock Plunges 5.7% Amid AI Agent Disruption Concerns appeared first on Blockonomi.

Key Takeaways

On April 20, 2026, SanDisk (SNDK) enters the Nasdaq-100, taking Atlassian’s (TEAM) position

Analyst firms elevate price targets: Jefferies to $1,000 and Bernstein to $1,250

The memory manufacturer’s shares have skyrocketed 2,640% annually, hovering around $851.77 near the $855 peak

A $1 billion strategic investment in Nanya Technology secures SanDisk roughly 3.9% equity stake

Wall Street points to artificial intelligence demand and strengthening NAND pricing as primary growth drivers

The memory storage specialist SanDisk (SNDK) has secured its position among elite tech companies, earning admission to the prestigious Nasdaq-100 index. The exchange operator confirmed Friday evening that the company will take its place in the benchmark before trading begins on April 20, 2026, displacing Atlassian (TEAM) from the roster.

This placement positions SanDisk within the exclusive circle of the top 100 largest non-financial enterprises trading on the Nasdaq exchange — a designation with significant market implications.

The Nasdaq-100 serves as the foundation for more than 200 investment vehicles, most notably the popular Invesco QQQ Trust. Collectively, these financial instruments command over $600 billion in total assets worldwide, ensuring that SanDisk’s index entry will spark substantial automated purchases from index-tracking funds.

Conversely, Atlassian confronts inevitable selling momentum as the same passive investment vehicles rebalance their portfolios. The software-as-a-service provider exits as the index composition tilts toward hardware and foundational technology companies.

The addition adheres to the present Nasdaq-100 selection framework, which remains operational until April 30, 2026. Market observers are closely monitoring anticipated index weighting adjustments before the April 20 implementation.

Wall Street Elevates Price Expectations

This benchmark inclusion arrives during a period of heightened analyst optimism surrounding SNDK.

Investment bank Jefferies upgraded its valuation target from $700 to $1,000 while maintaining its Buy recommendation. The research team highlighted continuing negotiations for extended supply agreements and artificial intelligence-fueled demand as factors supporting additional NAND memory price appreciation and favorable earnings adjustments before SanDisk’s April 30 quarterly results.

Analyst Blayne Curtis at Jefferies calculated the $1,000 projection using a 10x earnings multiple against a projected 2028 EPS figure of $95.26. The analysis also noted anticipated QLC eSSD deliveries to two major customers in upcoming quarters as a potential catalyst for expanding Data Center market position.

Bernstein demonstrated even greater confidence, increasing its target from $1,000 to $1,250. The firm retained its Outperform designation, emphasizing NAND pricing exceeding previous forecasts as the central factor.

Morgan Stanley reaffirmed its Overweight stance following recent volatility in memory semiconductor equities, characterizing the pullback as normal market adjustment rather than deteriorating business fundamentals. BofA Securities preserved its Buy rating with a $900 objective, highlighting robust demand from cloud computing giants and AI processing workloads.

Extraordinary Returns and Strategic Investments

SNDK has delivered exceptional shareholder returns. Shares have appreciated 2,640% during the trailing twelve months and presently change hands near $851.77, marginally beneath the 52-week maximum of $855. According to InvestingPro’s Fair Value framework, current pricing suggests the stock trades above intrinsic value.

Fiscal 2026 earnings per share consensus stands at $42.37, with the Street projecting SanDisk will achieve profitability during the current fiscal period.

From a strategic perspective, SanDisk disclosed a $1 billion capital allocation to Nanya Technology via private share placement. This transaction delivers approximately 139 million Nanya shares to SanDisk, equating to roughly 3.9% of total shares outstanding.

Company executives refrained from issuing revised financial guidance throughout recent discussions with the investment community.

The post SanDisk (SNDK) Stock Surges 2,640% as Nasdaq-100 Addition Looms appeared first on Blockonomi.

Key Highlights

Shares of Broadcom (AVGO) climbed 4.69% to reach $371.46 following announcements of long-term AI chip supply agreements with Google and Anthropic

Company insiders offloaded approximately $14.8 million worth of shares during the rally, with President S. Ram Velaga selling $10.6M and President Charlie Kawwas selling $3.45M

First-quarter results exceeded Wall Street projections with earnings per share of $2.05 versus the anticipated $2.03, while revenue of $19.31 billion marked a 29.5% annual increase

Wall Street maintains a generally optimistic outlook with a consensus price target of $435.30 and “Moderate Buy” rating; Barclays maintains a $500 target

Some analysts express caution as Seaport Global downgraded shares and Seaport Research assigned a “Neutral” stance due to valuation worries

On April 10, 2026, Broadcom announced it had secured multi-year agreements to supply AI chips to both Google and Anthropic. The announcement propelled AVGO shares up $16.55, representing a 4.69% gain, closing at $371.46. Trading volume surged to nearly 30 million shares, exceeding the typical 26.4 million average.

These agreements establish Broadcom as a critical provider of specialized AI accelerators and networking silicon to two leading hyperscale cloud operators. Market analysts suggest this development reinforces the company’s standing as a fundamental player in AI infrastructure.

Barclays maintains a $500 valuation target for the shares. Both Rosenblatt and KeyCorp similarly project $500, while Benchmark sets its sights at $485. Across 33 Wall Street analysts, the consensus recommendation stands at “Moderate Buy” with an average 12-month price objective of $435.30.

However, not all analysts share this enthusiasm. Seaport Global reduced its rating on the stock, and Seaport Research assigned a “Neutral” recommendation. Their reservations primarily focus on current valuation levels and uncertainties regarding long-term margin preservation as contract terms become more transparent.

Executive Share Sales During Rally

As shares climbed, three company executives executed significant stock sales.

Charlie Kawwas, who leads the Semiconductor Solutions Group, divested 10,000 shares at $345.23 per share, collecting $3.45 million. This transaction reduced his holdings by 1.25%, leaving him with 787,184 shares valued at approximately $271.8 million.

S. Ram Velaga, heading the Infrastructure Software Group, sold 30,215 shares totaling $10.64 million. Board member Justine Lien also divested 2,018 shares for $712,354. The combined value of these three transactions reached approximately $14.8 million.

While insider selling during price increases isn’t uncommon, the magnitude and coordination of these sales attracted market observers’ attention.

Financial Performance Remains Solid

Broadcom’s most recent quarterly results, published on March 4, delivered earnings per share of $2.05, surpassing the $2.03 Wall Street estimate. Revenue totaled $19.31 billion compared to the consensus forecast of $19.10 billion—representing a 29.5% year-over-year expansion.

The company posted a net profit margin of 36.57% and generated a return on equity of 38.61%. A quarterly dividend of $0.65 was distributed on March 31, yielding 0.7%.

Wall Street projects full-year earnings per share of $5.38. The stock currently trades at a price-to-earnings multiple of 72.55 with a PEG ratio of 0.73.

Shares have traded between $161.61 and $414.61 over the past twelve months. Current pricing sits above the 50-day moving average of $325.37 while remaining below the 200-day moving average of $342.86.

Major Institutional Accumulation

Among institutional investors, Vanguard, State Street, Geode Capital, T. Rowe Price, and Norges Bank all expanded their positions during the fourth quarter. Vanguard’s stake exceeds 482 million shares with a market value of $167 billion. Institutional investors and hedge funds collectively control 76.43% of outstanding shares.

Recent filings suggest Israel Englander and Ken Fisher have both increased their AVGO exposure in recent weeks.

The company’s current market capitalization stands at approximately $1.76 trillion.

The post Broadcom (AVGO) Surges Nearly 5% on Major AI Chip Contracts as Insiders Dump $14.8M in Shares appeared first on Blockonomi.

TLDR

Tesla’s Q1 2026 vehicle deliveries reached 358,000 units, marking a 6% yearly increase but falling short of the 365,000 analyst consensus

TSLA shares have declined 29% from record highs amid weakening EV demand, tax credit expiration, and intensifying competition

Bank of America resumed coverage with a $460 target price, highlighting Tesla’s camera-based robotaxi technology as a scalable competitive edge

Morgan Stanley calculates Tesla’s cost-per-mile advantage at $0.81, significantly undercutting Waymo’s $1.43 and conventional rideshare’s $1.71

Tesla’s Energy Storage division substantially underperformed — delivering 8.8 GWh against expectations of 14.4 GWh, representing a 40% gap

Tesla’s first-quarter 2026 delivery report showed 358,000 vehicles handed over to customers, representing a 6% improvement versus the prior year but narrowly missing Wall Street’s 365,000-unit forecast. This marked the second straight quarter where actual deliveries trailed analyst projections.

The electric vehicle manufacturer has encountered substantial headwinds. The elimination of federal tax incentives, escalating competitive pressures, and CEO Elon Musk’s controversial political involvement have all dampened consumer appetite. Throughout 2025, Tesla relinquished its position as the globe’s leading EV manufacturer, with deliveries, revenue, and profitability all trending downward.

TSLA shares currently trade 29% beneath their all-time peak. Yet two prominent Wall Street institutions have issued optimistic assessments — and their focus centers on future opportunities rather than recent performance.

Bank of America analyst Alexander Perry resumed coverage in March with a $460 valuation target, suggesting approximately 33% appreciation potential from the current $345 price level. This target aligns with the median forecast among 56 analysts tracking the stock, per The Wall Street Journal data.

Perry’s fundamental thesis revolves around autonomous vehicle technology. Tesla presently operates robotaxi services in only two American cities — Austin and San Francisco — placing it considerably behind Alphabet’s Waymo, which maintains operations across 11 cities. However, Perry identifies Tesla’s camera-exclusive methodology as the critical distinguishing factor.

Most autonomous taxi providers employ a combination of cameras, lidar sensors, and radar systems. Tesla relies exclusively on cameras. While technically more challenging, this approach dramatically reduces costs. The strategy eliminates expensive sensor installations and removes the requirement to pre-map urban environments with lidar before entering new markets.

“Tesla’s camera-only approach is technically harder but much cheaper and leverages a consumer-fleet data engine. Tesla’s strategy should allow it to scale more profitably compared to robotaxi competitors,” Perry said.

Cost Advantage Could Be Decisive

Morgan Stanley analyst Andrew Percoco reinforces this perspective. His analysis estimates Tesla’s robotaxi operating cost at $0.81 per mile, contrasted with $1.43 for Waymo and $1.71 for conventional rideshare services. He anticipates this metric will decrease further once Cybercab manufacturing achieves scale.

Percoco additionally identifies the robotaxi deployment as creating a reinforcing cycle: expanded ride volume produces enhanced real-world operational data, which refines Tesla’s artificial intelligence systems, which advances the Full Self-Driving (FSD) capabilities offered to traditional vehicle purchasers, which stimulates demand in the primary automotive business.

Musk has indicated the autonomous transportation network could extend to “dozens of major cities” encompassing between one-quarter and one-half of the United States by year’s conclusion. Morgan Stanley forecasts Tesla will secure 25% of U.S. autonomous transportation trips annually by 2032, trailing Waymo’s projected 34% market share.

Energy Storage Was the Real Miss

While automotive delivery figures dominated headlines, Tesla’s Energy Storage division experienced a challenging quarter. Megapack installations totaled merely 8.8 GWh, a 40% shortfall compared to the 14.4 GWh consensus projection. This represented Tesla’s first year-over-year contraction in storage deployments since 2022.

Analysts characterize this as an isolated occurrence, attributing it to the irregular timing inherent in large-scale utility agreements and project schedules. Nevertheless, this metric warrants continued monitoring.

Morgan Stanley has revised its full-year 2026 delivery projection to 1.60 million vehicles, still indicating a 2.2% year-over-year decrease. The firm’s extended-term framework anticipates a mid-teens volume compound annual growth rate through 2030, propelled by upcoming model introductions including a prospective “Model YL” and a refreshed Cybertruck.

The post Tesla (TSLA) Stock: Wall Street Banks Bet Big on Robotaxi Despite Delivery Weakness appeared first on Blockonomi.

Key Takeaways

The WLFI token plunged 12% to reach an all-time low since its 2025 debut

The project leveraged its native WLFI tokens as collateral for stablecoin loans on the Dolomite platform

This borrowing activity exhausted Dolomite’s USD1 liquidity pool, preventing other users from accessing withdrawals

Tron’s Justin Sun saw his locked WLFI position decline by more than $11 million within 24 hours

Treasury repurchase operations are currently underwater by approximately 48%

The World Liberty Financial token experienced a sharp 12% decline over a 24-hour period, reaching its lowest valuation since its 2025 introduction. The digital asset traded around $0.0818, compounding weekly declines of 15% and monthly losses totaling 17%.

World Liberty Financial (WLFI) Price

The dramatic price movement followed a CoinDesk investigation revealing that WLFI had pledged billions of its proprietary governance tokens as collateral within the Dolomite lending infrastructure. Using this collateral base, the initiative secured substantial stablecoin loans, including USDC and its proprietary USD1 token, totaling tens of millions of dollars.

Blockchain intelligence from Arykham verified that a project-controlled wallet deposited 5 billion WLFI tokens as collateral on Dolomite, facilitating approximately $75 million in stablecoin borrowings. Subsequently, more than $40 million of these borrowed assets were moved to Coinbase Prime.

Day 44: We're seeing insane levels of crime once again.

Yesterday, Trump family's crypto project deposited 5% of $WLFI's total supply on Dolomite and borrowed $75 million in stablecoins against it.

5% of WLFI's token supply is worth roughly $500M.

Then, just a few hours… pic.twitter.com/ACqGXpvckg

— Ethan DeFi (@EthanDeFi_) April 8, 2026

This substantial borrowing activity maxed out Dolomite’s available lending capacity, creating a liquidity crisis that temporarily prevented other protocol participants from accessing their deposited capital.

Project Team Addresses Growing Concerns

World Liberty Financial published a detailed response thread on X, characterizing the criticism as baseless fearmongering. The organization emphasized that liquidation risks remain minimal.

“In the event of significant market volatility against our position, we maintain the capability to supply additional collateral,” the team explained. However, skeptics noted that pledging more WLFI tokens to support existing WLFI-backed positions—particularly on a platform where a WLFI advisor holds leadership—compounds circular risk rather than mitigating it.

We are one of the largest suppliers and borrowers on WLFI Markets.
Yes, we supplied WLFI as collateral and borrowed stablecoins. No, we are nowhere near liquidation — and frankly, even if markets moved dramatically against us, we'd simply supply more collateral. That's not a…

— WLFI (@worldlibertyfi) April 9, 2026

Adding to the controversy, Dolomite co-founder Corey Caplan simultaneously serves in an advisory capacity for World Liberty Financial, intensifying questions about potential conflicts of interest among industry observers.

According to project disclosures, WLFI allocated $65.58 million toward repurchasing 435.3 million tokens across six months, achieving an average acquisition price of $0.1507. With current market prices hovering near $0.078, these buyback initiatives represent unrealized losses of roughly 48%.

Significant Losses for Justin Sun

Justin Sun, the founder of Tron, witnessed his immobilized WLFI holdings depreciate by over $11 million in a single trading session. Sun initially committed $30 million to World Liberty Financial during late 2024, subsequently expanding his stake to approximately $75 million.

Following the movement of roughly $9 million in WLFI from Sun’s wallet last year, World Liberty Financial blacklisted his address, effectively freezing his token holdings. According to blockchain analytics provider Bubblemaps, Sun currently possesses approximately 545 million frozen WLFI tokens valued at roughly $45 million—representing a decline exceeding $80 million from previous valuations.

An additional 3 billion WLFI tokens remain in an intermediary wallet following treasury operations conducted on April 2 and April 7, presently valued at approximately $234 million.

Technical indicators show the Relative Strength Index approaching 30, nearing oversold conditions, while the MACD reflects persistent bearish momentum. Immediate support is positioned at $0.079, with potential downside objectives at $0.075 and $0.070 should selling intensity persist.

The post WLFI Token Plunges to Record Low Amid Dolomite Collateral Controversy appeared first on Blockonomi.

TLDR:

Attackers socially engineered OVHcloud support to remove hardware 2FA, enabling full account access within an hour.

The phishing site used an Inferno Drainer kit and ran live for roughly four hours on March 30, 2026.

ICANN’s five-day domain transfer lock gave Steakhouse Financial time to cancel an outbound transfer filed by the attacker.

Steakhouse vaults on Morpho operated independently throughout; no depositor funds were at risk at any point.

A social engineering attack briefly redirected Steakhouse Financial’s website to a phishing page on March 30, 2026. 

Attackers manipulated the domain registrar’s support team to strip account security protections. The phishing site ran for roughly four hours before the team reclaimed control. No user funds were lost, and no onchain contracts were touched.

How Attackers Broke Into Steakhouse Financial’s Domain Registrar

The attacker called OVHcloud, the domain registrar used by Steakhouse Financial, and posed as the account owner. They provided enough personal information to pass OVH’s phone-based identity check. 

An OVH support agent then removed the hardware-based two-factor authentication on the account.

Within seconds of logging in, the attacker ran automated scripts. These deleted every second-factor device on the account and enrolled their own. The speed pointed to a pre-planned operation.

The attacker then redirected the domain’s nameservers to servers under their control. 

They pointed the site’s A records to a cloned version of the Steakhouse website hosted on Hostinger. That cloned site carried a wallet drainer linked to Inferno Drainer, a known drainer-as-a-service operation.

Let’s Encrypt TLS certificates were obtained within minutes. This made the phishing site appear legitimate to standard browsers. Wallet extensions from Phantom, MetaMask, and Rabby flagged the site as malicious independently and quickly.

https://t.co/0VlJ5n0yAM

— Steakhouse Financial (@SteakhouseFi) April 10, 2026

Steakhouse Financial Regained Control Within Hours, Funds Remained Safe

Steakhouse Financial’s team spotted the unauthorized email-change notification at 08:47 UTC and contacted OVH immediately. The phishing site went live around 09:59 UTC. 

The team posted a public warning on X at 10:34 UTC, under 30 minutes after the site became operational.

The Security Alliance (SEAL) was brought in at 11:25 UTC while the attack was still active. The team worked across multiple parallel tracks. These included account recovery, DNS forensics, and transfer cancellation.

The attacker had filed an outbound domain transfer. ICANN’s five-day transfer timelock gave the team time to cancel it.

The team contacted Hostinger directly to reject the transfer on the receiving end. Hostinger later confirmed the offending account was frozen and closed.

By 12:56 UTC, the team had reclaimed the OVH account. DNS was fully restored by approximately 13:55 UTC. Steakhouse Financial confirmed all domains were safe to use by April 1.

The company has since migrated to a registrar supporting hardware-key MFA and registrar-level locks. A continuous DNS monitoring system now watches all Steakhouse domains in real time. According to the post-mortem published by Steakhouse Financial on X, a full vendor security review process is now being established across all supply-chain vendors.

Adrian Cachinero Vasiljevic, the partner responsible for operations at Steakhouse Financial, issued a personal apology. He stated that identifying this attack vector was his responsibility and committed to driving the security hardening work going forward.

The post Steakhouse Financial Confirms DNS Hijack, Says No User Funds Were Lost appeared first on Blockonomi.

If you have ever left a Telegram signal group feeling burned — prices already moved by the time the alert hit your phone, the caller quietly deleted the post, and you were left holding a bag — you already understand the core problem that AI bots for crypto trading are designed to solve. Speed, discipline, and 24/7 execution. No emotion. No deleted posts.

But ‘AI trading bot’ has become one of the most over-marketed phrases in crypto. Every platform claims intelligence. Few deliver genuine quantitative edge. And almost none tell you what actually separates a bot that compounds your portfolio from one that quietly bleeds it.

This guide cuts through the noise. We cover how AI trading bots work under the hood, what the best bot for crypto trading looks like for your specific situation, how to evaluate profitability claims honestly, and what institutional-grade risk management actually means in practice — the kind most retail bots skip entirely.

We also share what 30 days of live simulation across multiple strategies revealed, because real performance data matters more than vendor dashboards.

QUICK VERDICT: AI bots for crypto trading make sense if you want structured, repeatable execution without watching charts all day. The most profitable crypto trading bot isn’t necessarily the one with the highest advertised return — it’s the one that survives drawdowns, adapts to changing market regimes, and operates within a risk framework you actually understand. Set-and-forget is a myth; strategic automation is the reality.

Key Takeaways

Best overall for passive income seekers: Platforms with pre-built, institutional-grade quantitative strategies requiring minimal configuration

Best for active traders upgrading to automation: Multi-exchange terminals with signal routing, DCA, and grid bots

Critical reality check: AI bots optimise around historical patterns — when market regimes shift, performance can degrade rapidly without human oversight

Institutional edge: True institutional-grade risk management includes position-level stops, portfolio-level drawdown limits, volatility-adjusted sizing, and regime detection — most retail bots provide only the first two

Telegram signals vs. automation: Signal-based trading has an average latency of 2–8 minutes from publication to execution; automated bots execute in milliseconds

The ‘trading while I sleep’ promise is achievable — but only with the right infrastructure, strategy diversification, and monitoring protocols

How AI Trading Bots Work: The Real Mechanism

Understanding how AI trading bots work isn’t optional — it’s the difference between deploying a strategy intelligently and hoping a dashboard number goes up.

At their core, all AI bots for crypto trading operate on a loop:

Phase What Actually Happens 1. Data Ingestion Price feeds, order book depth, volume, funding rates, on-chain metrics, and sometimes social sentiment are pulled in real time 2. Signal Generation The strategy layer — rule-based logic, machine learning models, or a hybrid — identifies conditions that match a trade setup 3. Risk Validation Position size is calculated against portfolio risk limits; stop-loss and take-profit levels are pre-set before order submission 4. Order Execution API call dispatched to the exchange; slippage, fee impact, and liquidity depth are factored into fill expectations 5. Monitoring & Feedback Live positions are tracked; trailing stops adjust; the strategy layer re-evaluates at each new candle or tick

What ‘AI’ Actually Means on Most Platforms

Genuine machine learning in a crypto trading context means the model was trained on labelled historical data, can identify non-obvious patterns, and updates its parameters as new data arrives. In practice, most consumer-facing platforms use lighter implementations:

Rule-based automation marketed as AI (if RSI < 30, then buy)

Natural language prompt-to-config tools (GPT wrapper that converts your English description into pre-set parameters)

Scoring and ranking systems that filter marketplace strategies by momentum or volatility metrics

True adaptive ML models that retrain on rolling windows and adjust position sizing — rarer, and more associated with institutional or quantitative platforms

In practice, what this looks like is: a platform labels its parameter-suggestion tool ‘AI Assistant’, while a genuine quant platform runs ensemble models that weight momentum, mean-reversion, and volatility signals simultaneously and size positions based on Kelly Criterion or similar frameworks. Both call themselves AI. Only one is.

The Quantitative Strategy Taxonomy: What Types of Strategies Do Bots Actually Run?

Most reviews stop at ‘grid bot’ and ‘DCA’. Here is the full spectrum relevant to AI bots for crypto trading:

Strategy Type How It Works Best Market Condition Grid Trading Places buy/sell orders at fixed price intervals, profiting from oscillation within a range Sideways / ranging market DCA (Dollar Cost Averaging) Buys at regular intervals regardless of price, averaging down into dips Long-term accumulation in any market Momentum / Trend Following Enters positions in the direction of established price momentum using moving averages or breakout signals Strong trending markets Mean Reversion Bets that prices revert to a statistical mean after deviating significantly — often using Bollinger Bands or Z-score High-volatility, range-bound Statistical Arbitrage Exploits price discrepancies between correlated assets or the same asset across exchanges Any — market-neutral Market Making Simultaneously posts bid and ask orders to profit from the spread, providing liquidity to the market High-liquidity pairs, low-volatility Sentiment-Driven Uses NLP models to parse news, social media, and on-chain signals, taking positions ahead of anticipated price moves Event-driven / news cycles

Most retail bots support grid and DCA. Institutional-grade platforms like SaintQuant layer multiple strategy types simultaneously — running momentum strategies in trending conditions and mean-reversion strategies in choppy markets — and use regime detection to weigh between them dynamically. This is the quantitative edge that separates consistent alpha from lucky streaks.

What AI Bots Cannot Do — The Honest Section Most Guides Skip

A GPS suggests the fastest route and reroutes when traffic changes. But it cannot predict a sinkhole that opens 10 minutes from now. AI bots for crypto trading work the same way.

Black swan events (exchange hacks, regulatory bans) are not in the training data — models extrapolate poorly in genuinely novel conditions

Liquidity crises distort execution — during a flash crash, your stop-loss triggers at a price far worse than intended because there are no buyers at your target level

Strategy decay is real — an edge that worked in 2021 may be fully arbitraged away by 2024 as more capital chases the same signal

Hallucination risk in prompt-based tools — GPT-powered config generators can confidently recommend inappropriate parameters; always validate against backtests

Regulatory grey zones — automated trading on unlicensed platforms carries legal exposure in some jurisdictions, including Australia, where ASIC scrutinises crypto trading product providers

Telegram Signals vs. AI Bots for Crypto Trading: Why Most Traders Make the Switch

If you have spent time in paid Telegram signal groups, the pattern is familiar: a call goes out, you scramble to execute manually, prices are already moving, and slippage eats your entry. The caller posts a win screenshot. You got a worse fill.

Factor Telegram Signals AI Trading Bots Execution Speed 2–8 min average (manual entry) Milliseconds (API execution) Consistency Human execution errors frequent Rules followed exactly every time Emotional Bias High — FOMO, hesitation, revenge trading Zero — no emotional override Risk Management Caller-defined, often inadequate Configurable at position and portfolio level Transparency No audit trail, results cherry-picked Full trade history, verifiable logs Overnight Coverage Signals stop when caller sleeps Operates 24/7 without interruption Cost $50–$500/month for signal groups $15–$120/month for bot platforms Accountability None — deleted posts, no recourse Verifiable backtest and live performance data

The core problem with Telegram signals isn’t the strategy — sometimes the underlying analysis is sound. The problem is the delivery mechanism. By the time a signal reaches 10,000 subscribers and most of them execute manually, the market has already adjusted to the front-runners. Automation closes that gap entirely.

The Best AI Bots for Crypto Trading: Platform-by-Platform Review

Rather than ranking by advertised returns — which are meaningless without knowing the strategy, market period, and risk taken — we evaluate platforms across six dimensions: AI capability depth, strategy breadth, risk management quality, ease of use, exchange coverage, and pricing transparency.

1. SaintQuant — Best for Passive Income Seekers and Automated Quantitative Strategies

Best for: Users seeking institutional-grade quant strategies without building from scratch

SaintQuant stands apart from template-based bot platforms because it was built as a quantitative trading infrastructure — not a consumer interface layered on top of simple rules. With 150,000+ users and 10+ live strategies running simultaneously, the platform applies AI-driven strategy selection across different market regimes: momentum strategies when trends are clear, mean-reversion strategies when markets oscillate, and defensive positioning when volatility spikes into danger territory.

In practice, what this looks like is: rather than asking you to configure a grid bot and hope the range holds, SaintQuant’s regime-detection layer identifies whether the current market favours trend-following or range-bound strategies, then weights portfolio allocation accordingly — automatically, without manual intervention.

10+ live quantitative strategies across multiple asset classes and market conditions

Institutional-grade risk management: position-level stops, portfolio drawdown limits, volatility-adjusted position sizing

AI-powered regime detection that shifts strategy weighting based on market conditions

24/7 automated execution — the closest thing to genuinely trading while you sleep

Transparent, verifiable strategy performance history — not curated screenshots

Risk note: No strategy performs consistently across all market conditions. SaintQuant’s diversification across 10+ strategies mitigates single-strategy risk, but crypto markets can produce drawdowns no model anticipates. Risk-adjusted returns require ongoing monitoring even with automated systems.

Start with a $99 trial credit and see SaintQuant’s strategies in action — no deposit, no pressure.

2. 3Commas — Best for Multi-Exchange Active Traders

Best for: Traders who want hands-on control with structured entry/exit workflows across multiple exchanges

3Commas offers a SmartTrade terminal that centralises order management, DCA automation, and TradingView signal routing. Its AI features surface parameter suggestions — trend and volatility analysis feeding into entry recommendations — but these are decision aids, not autonomous strategies.

SmartTrade workspace: manage entries, exits, and stops from one interface

DCA and grid bots with configurable scaling rules

TradingView alert-to-order routing for external signal integration

AI assistant that proposes entries and risk settings for review before launch

Pricing from $12.42/month (annual); demo trading available

Who should skip it: Anyone expecting a fully passive experience. 3Commas rewards active management — it reduces the operational burden but doesn’t eliminate the need for oversight.

3. Cryptohopper — Best for Strategy Marketplace Users

Best for: Traders who want access to a marketplace of pre-built strategies and automatic strategy rotation

Cryptohopper’s Algorithm Intelligence layer scores strategies using trend strength, volatility, and volume metrics, then rotates the active strategy automatically. The Marketplace lets you subscribe to external signals and strategies, while the Strategy Designer lets you build custom if-then logic. Copy trading adds a social dimension with configurable risk controls.

Algorithm Intelligence: scores and rotates strategies based on market conditions

Marketplace: subscribe to strategies, templates, and signals

Visual Strategy Designer: build rule-based strategies without coding

Paper trading and backtesting available before going live

Pricing: Free Pioneer tier; Explorer from $24.16/month (annual)

Who should skip it: Traders seeking a stable, single-strategy system. Cryptohopper’s strength is rotation and variety — if you want simplicity, look elsewhere.

4. Pionex — Best for Beginners Entering Automation

Best for: Crypto newcomers who want built-in bots with minimal setup friction

Pionex is an exchange with bots built in — no API connection required, no separate subscription for bot access. PionexGPT accepts plain-English prompts and converts them into bot configurations with suggested parameters. The trade-off is limited strategy depth and no cross-exchange capability.

No separate bot subscription — fee-based model (0.05% spot)

PionexGPT: type ‘build a grid for BTC with a 2% stop loss’ and receive a configured strategy

Core strategies: grid, DCA, infinity grid, signal following

Demo trading available; simple onboarding for non-technical users

Who should skip it: Advanced traders who need cross-exchange routing, custom logic, or portfolio-level risk management beyond basic stops.

5. Bitsgap — Best for Multi-Exchange Terminal Users

Best for: Traders active on multiple exchanges who want unified management

Bitsgap connects to 15+ exchanges and consolidates bot management into a single terminal. Its AI Assistant suggests bot parameters and portfolio configurations. COMBO futures bots and advanced Smart Trade order management make it more capable than beginner platforms, though the AI layer is primarily a recommendation engine rather than an autonomous decision-maker.

Unified terminal: manage bots across Binance, Bybit, OKX, Coinbase, Kraken and more

AI Assistant: suggests configurations and portfolio allocations

Demo mode and backtesting before live deployment

Pricing from $18/month (annual)

6. HaasOnline — Best for Developers and Advanced Quantitative Traders

Best for: Developers and quant traders who want scripting-level control over strategy logic

HaasOnline’s differentiator is HaasScript — a full visual and code editor for building custom strategies, market-making bots, arbitrage logic, and scalping systems. This isn’t AI in the consumer sense; it’s a professional quant environment. The ceiling is high, but so is the learning curve.

HaasScript: visual + code editor for custom strategy development

Supports market making, arbitrage, scalping, and complex conditional logic

Built-in backtesting and paper trading on historical data

Pricing from $23/month (annual)

Who should skip it: Non-technical users. HaasOnline requires meaningful time investment to use effectively.

7. Coinrule — Best for No-Code Rule Builders

Best for: Beginners and non-programmers who want visual if-then automation

Coinrule uses simple conditional logic (‘if RSI drops below 30, buy 5% of portfolio; set stop-loss at -8%’) with a library of templates to accelerate setup. AI Trading adds adaptive optimisation that learns from execution data. Demo exchange testing is available before live deployment.

No-code if-then rule builder with pre-built templates

AI Trading: adaptive optimisation layer that learns from live execution

Supports 10+ exchanges including Binance, Bybit, OKX, Coinbase

Pricing: Free Starter; Investor from $29.99/month

Full Platform Comparison: AI Bots for Crypto Trading

Platform True AI Depth Strategy Types Risk Mgmt Quality Beginner Friendly Price/mo Best For SaintQuant ★★★★★ Quant multi-strategy Institutional ★★★★☆ Varies Passive income / automation 3Commas ★★★☆☆ DCA, Grid, Signal Moderate ★★★☆☆ From $12 Active multi-exchange traders Cryptohopper ★★★☆☆ Rules, Marketplace Moderate ★★★★☆ From $24 Marketplace / strategy rotation Pionex ★★☆☆☆ Grid, DCA Basic ★★★★★ 0.05% fee Crypto newcomers Bitsgap ★★★☆☆ Grid, DCA, COMBO Moderate ★★★☆☆ From $18 Multi-exchange terminal HaasOnline ★★☆☆☆ Custom / Script Advanced (manual) ★★☆☆☆ From $23 Developers / quant traders Coinrule ★★☆☆☆ Rule-based Basic-Moderate ★★★★★ Free / $30 No-code beginners

What ‘Trading While I Sleep’ Actually Requires

The ‘built an AI bot that trades crypto for me while I sleep’ dream is real — but it requires more infrastructure than most guides admit. Here is what genuinely hands-off automated trading demands:

Strategy diversification: A single bot running one strategy is not passive income — it’s a concentrated bet. True passive automation runs multiple uncorrelated strategies simultaneously.

Portfolio-level risk limits: Per-position stops are necessary but insufficient. You need a maximum portfolio drawdown threshold that halts all bots if breached — preventing a bad strategy from wiping gains from good ones.

Exchange health monitoring: API connections fail. Exchanges go down for maintenance. A properly configured system sends alerts when connectivity is lost and halts execution gracefully rather than leaving orphaned positions.

Regular strategy review: Even robust quant strategies require periodic review — monthly at minimum. Markets evolve; edges erode; parameter drift happens.

Realistic return expectations: Sustainable automated crypto trading targets 15–40% annualised returns with controlled drawdowns. Anything promising 200%+ monthly is either taking extreme leverage risk or fabricating results.

Institutional-Grade Risk Management vs. Retail Bot Defaults

The phrase ‘institutional-grade risk management’ gets thrown around liberally. Here is what it actually means in a crypto bot context:

Risk Layer Retail Bot Default Institutional Grade Position Stop-Loss Fixed % stop (e.g., -5%) Volatility-adjusted stop (e.g., 2× ATR) Position Sizing Fixed $ or % per trade Kelly Criterion or volatility-weighted sizing Portfolio Drawdown Rarely implemented Hard halt if portfolio drops >X% from peak Regime Detection None — strategy runs regardless ML model detects trend/range/crisis regimes and adjusts Correlation Management Not considered Strategies are de-correlated to avoid simultaneous drawdowns Slippage & Fee Modelling Ignored in backtests Built into all performance calculations Strategy Decay Monitoring Manual (if at all) Automated performance degradation alerts

How to Choose the Right AI Bot for Crypto Trading: A Decision Framework

Use these four filters in sequence to eliminate platforms that don’t fit your situation before investing time in setup:

Filter 1: Define Your Involvement Level

High involvement (daily monitoring, manual intervention): 3Commas, HaasOnline, Bitsgap

Medium involvement (weekly review, strategy selection): Cryptohopper, Coinrule

Low involvement (monthly review, pre-built strategies): SaintQuant, Pionex

Filter 2: Match Strategy to Your Market View

Bullish long-term accumulator: DCA-focused platforms (Pionex, Coinrule)

Range-bound market trader: Grid bots (3Commas, Pionex, Bitsgap)

No strong market view, want diversification: Multi-strategy quant platforms (SaintQuant)

Advanced directional trader: HaasScript custom momentum strategies

Filter 3: Assess Your Technical Capability

No coding, minimal configuration: Pionex, Coinrule

Comfortable with settings and parameters: 3Commas, Cryptohopper, Bitsgap

Developer or quant background: HaasOnline

Want institutional infrastructure without building it: SaintQuant

Filter 4: Evaluate Risk Management Quality

Before committing capital, ask the platform provider three questions: How does the strategy perform during a -30% market drawdown? What is the maximum portfolio-level loss limit? Can you show me a verified trade history, not just a backtest?

If any of these questions produce vague answers or redirect you to a marketing dashboard, treat that as a red flag.

Backtesting AI Trading Bots: What the Numbers Actually Mean

Every platform shows backtest results. Few explain how easy they are to manipulate — intentionally or accidentally.

The Four Ways Backtests Lie

Lookahead bias: The strategy uses data that wouldn’t have been available at the time of the trade signal

Survivorship bias: Only successful historical periods are tested; the strategy is tuned to past winners

Overfitting: Parameters are optimised so precisely to historical data that the strategy fails on any new data it hasn’t seen

Ignoring costs: Fees, slippage, and funding rates can turn a 40% backtest return into a 12% live return

Minimum Reliability Checklist Before Going Live

Backtest covers at least 2 years of data, including at least one major drawdown period

Out-of-sample testing: strategy was tested on data completely excluded from the optimisation process

Fees and slippage included in all calculations

Paper trading results match backtest results within 15% variance

Sharpe ratio above 1.0 (risk-adjusted return per unit of volatility)

Maximum drawdown is one you could sustain emotionally and financially

Security Essentials for AI Bots for Crypto Trading

API key exposure is the primary attack surface for all bot platforms that connect via API. The risks are real: several major platforms have experienced API key-related breaches affecting user accounts.

Non-Negotiable Security Practices

Trade-only permissions: Never enable withdrawal permissions on API keys used by bots — ever

IP allow-listing: Restrict API key usage to the bot platform’s specific IP range where the exchange supports it

Separate exchange accounts: Consider a dedicated exchange account for bot trading, separate from your primary holdings

Key rotation: Regenerate API keys quarterly or after any suspected security incident

Two-factor authentication: Enable on both the exchange and bot platform accounts

Withdrawal address whitelisting: Restrict exchange withdrawals to pre-approved wallet addresses only

Monitor for unusual activity: Set exchange alerts for any large or unexpected withdrawal attempts

Practical Setup Guide: How to Deploy an AI Trading Bot Safely

This workflow applies regardless of which platform you choose:

Step 1: Account and API Setup (Day 1)

Create bot platform account and complete KYC if required

Create or designate a trading-only exchange account

Generate API keys with trade-only permissions (no withdrawals)

Apply IP allow-listing if the exchange supports it

Connect API to bot platform and verify connection status

Step 2: Strategy Selection and Configuration (Days 1–3)

Select strategy type based on your market view and involvement level

Configure position size — start with 10–20% of intended allocation maximum

Set stop-loss at both position level and portfolio level

Run backtest with fees and slippage included

Validate backtest against an out-of-sample period

Step 3: Paper Trading Validation (Days 4–14)

Run strategy in paper trading mode for a minimum of 7–14 days

Compare live execution to backtest expectations — flag any variance >15%

Monitor for connectivity issues, missed signals, and fill quality

Adjust parameters if necessary and re-validate before going live

Step 4: Live Deployment (Day 15 onwards)

Deploy with 25–50% of intended capital allocation for the first month

Set monitoring alerts for connectivity loss, unexpected drawdowns, and unusual order activity

Review performance weekly for the first month

Scale allocation only after live performance validates backtest expectations

Frequently Asked Questions: AI Bots for Crypto Trading

Is using an AI bot for crypto trading profitable?

It can be, but profitability is not guaranteed and depends heavily on strategy quality, market conditions, risk management configuration, and ongoing oversight. The most profitable crypto trading bot is the one that survives drawdowns with your capital intact while generating consistent risk-adjusted returns — not the one with the highest advertised percentage gain.

How do AI trading bots work differently from traditional rule-based bots?

Traditional rule-based bots execute fixed instructions (if X happens, do Y). AI-enhanced bots incorporate machine learning models that identify patterns in historical data, adapt parameters as conditions change, and weight signals based on regime detection. In practice, the line between the two is blurry — many platforms label rule-based tools as AI.

Can I genuinely build an AI bot that trades crypto for me while I sleep?

Yes — but ‘while you sleep’ doesn’t mean ‘without any oversight’. Genuinely automated trading requires multiple uncorrelated strategies, portfolio-level risk limits, connectivity monitoring, and monthly strategy reviews. Platforms like SaintQuant are specifically designed for this use case, with pre-built quantitative strategies and institutional-grade risk infrastructure so you don’t need to build it yourself.

What is the best AI bot for crypto trading for beginners?

Pionex is the lowest-friction entry point for beginners, with built-in bots and no subscription fees. For beginners who want more sophisticated outcomes with less configuration, SaintQuant’s pre-built quantitative strategies offer institutional-grade performance without requiring users to configure strategy logic from scratch.

What is a realistic return from an AI crypto trading bot?

Sustainable, risk-adjusted returns from quantitative crypto strategies typically range from 15–40% annualised across full market cycles, including drawdown periods. Claims of 100%+ monthly returns almost always involve extreme leverage, survivorship bias in reporting, or outright fabrication. Consistent alpha over multiple years is the benchmark that matters.

Closing Thoughts: The Most Profitable Crypto Trading Bot Is the One You’ll Actually Use Correctly

AI bots for crypto trading are genuinely powerful tools. They enforce discipline where human psychology fails. They execute in milliseconds when manual trading takes minutes. They run while you sleep, through weekends, through market hours across every timezone.

But they don’t create an edge that doesn’t exist in the underlying strategy. A poorly configured bot executes a bad strategy faster. A well-configured bot on a robust quantitative platform executes a sound strategy consistently — and that consistency, compounded over time, is where the real edge lives.

The key distinction to hold onto: the question isn’t which bot has the most impressive dashboard. It’s which platform has the risk infrastructure, strategy quality, and transparency to deliver consistent alpha across multiple market regimes — not just in bull markets.

SaintQuant was built with exactly that question in mind. With 150,000+ users, 10+ live quantitative strategies, and institutional-grade risk management running 24/7, it’s the platform designed for investors who want automated performance without building a quant fund from scratch.

The post AI Bots for Crypto Trading: The Complete 2026 Guide to Automated Profits Without the Guesswork appeared first on Blockonomi.

TLDR:

トライデントのRLUSDガーナパイロットは、より迅速な決済と低い送金摩擦を提供する2.1M MSMEを対象としています。

この展開により、安定コインとセディビジネス決済フローを支えるために、RLUSD/GHS流動性プールが追加されます。

自動税金レールは、ブロックチェーン決済を直接ガーナの収益徴収システムに組み込みます。

2026年中頃が目標のローンチウィンドウであり、規制当局の承認とシステムの準備状況が保留されています。

トライデントデジタルテックホールディングスは、2026年中頃に予定されているブロックチェーン決済および税金のパイロットを通じて、リップルRLUSDインフラをガーナに導入する計画です。

Key Takeaways

Tehran is reportedly exploring digital currency payment options for vessels transiting the Strait of Hormuz

This waterway accounts for approximately one-fifth of worldwide petroleum transport

Blockchain analysis firm Chainalysis identifies this as potentially unprecedented for state-controlled maritime passages

Industry experts suggest stablecoins might be favored over Bitcoin given liquidity considerations and Iran’s historical crypto usage patterns

Maritime companies accepting these payments could face significant regulatory consequences under international sanctions regimes

Reports emerged this week indicating Iran may implement cryptocurrency-based fees for oil tankers navigating through the Strait of Hormuz, a strategically vital maritime corridor. The Financial Times first reported the development on Wednesday, attributing the information to a representative from Iran’s Oil, Gas and Petrochemical Products Exporters’ Union.

https://twitter.com/arkham/status/2042186892465320414?s=20

This narrow passage facilitates the movement of roughly 20% of worldwide petroleum supplies. According to reports, Iran’s Islamic Revolutionary Guard Corps would oversee the fee collection mechanism.

The proposed system would require vessel operators to provide ownership documentation and cargo information prior to fee negotiations. Initial pricing is reported to begin around $1 per barrel, with payment options including Chinese yuan or digital currencies.

Galaxy’s research director Alex Thorn indicated that varying accounts point to possible payment methods including stablecoins or Chinese yuan beyond just Bitcoin. He confirmed Galaxy is actively tracking blockchain networks for evidence of such transactions.

https://twitter.com/coinbureau/status/2042830276913713610?s=20

Thorn’s analysis places potential toll charges in a range from $200,000 to $2 million per vessel. The Financial Times report specified ships would receive mere seconds to complete Bitcoin transfers.

Technical Implementation Questions Remain

Such an abbreviated payment timeframe points toward potential Lightning Network utilization. This second-layer [[LINK_START_0]]Bitcoin[[LINK_END_0]] solution enables near-instantaneous transactions, circumventing the typical 10-minute block confirmation delays.

Yet Thorn highlighted that the highest recorded Lightning transaction stands at $1 million. This capacity limitation may prove insufficient for premium-tier tolls. His assessment suggests Iran would more likely distribute QR codes or Bitcoin wallet addresses following transit authorization approval.

Cryptocurrency proponents emphasize that BTC operates without central issuance and cannot be frozen, contrasting with stablecoins like USDT or USDC that remain subject to smart contract-level blacklisting.

Chainalysis released analysis on April 10 characterizing this development as potentially historic. The blockchain intelligence company stated successful implementation would mark the first documented instance of a sovereign nation requiring cryptocurrency for passage through internationally significant waters.

Stablecoin Payment More Probable, Experts Say

Notwithstanding Bitcoin-focused headlines, Chainalysis indicated Tehran may actually favor stablecoins. The firm referenced Iran’s established track record utilizing stablecoins for petroleum transactions, arms procurement, and large-scale sanctions circumvention.

Stablecoins provide superior liquidity and price stability compared to [[LINK_START_1]]Bitcoin[[LINK_END_1]], rendering them more suitable for substantial commercial exchanges.

International shipping corporations face legitimate compliance exposure. Transferring funds to IRGC-associated wallets could prompt enforcement measures under U.S. Treasury Department sanctions frameworks, irrespective of payment denomination.

Chainalysis emphasized that blockchain forensics capabilities have become indispensable for monitoring these financial flows and supporting global risk management efforts.

The post Iran’s Crypto Toll Plan Could Transform the Strait of Hormuz appeared first on Blockonomi.

Key Takeaways

The Kingdom of Bhutan has slashed its Bitcoin reserves from approximately 13,000 BTC to just 3,774 BTC since October 2024

State-controlled wallets have transferred more than $233 million in Bitcoin during 2026

No significant mining inflows exceeding $100,000 have been detected in Bhutan’s wallets for over 12 months

Druk Holding and Investments, managing Bhutan’s sovereign assets, has declined to provide public statements

The Himalayan nation stands alone among sovereign Bitcoin holders in actively liquidating its position

The government of Bhutan has offloaded approximately 70% of its Bitcoin portfolio since reaching peak holdings of nearly 13,000 BTC in October 2024. Current reserves sit at roughly 3,774 BTC, representing a market value of about $272.5 million.

THE DRAGON KING IS SELLING BITCOIN

The Fifth Dragon King of Bhutan, Druk Gyalpo Jigme Khesar Namgyel Wangchuck, just sold $18M of BTC.

Bhutan has sold approximately $180M Bitcoin since the start of the year. pic.twitter.com/IedWLUK8D0

— Arkham (@arkham) April 10, 2026

According to blockchain intelligence firm Arkham Intelligence, Bhutan’s Royal Government transferred an additional 250 BTC—valued at approximately $18 million—to a freshly established wallet address this week. This transaction followed a Thursday movement of roughly 319.7 BTC worth $22.68 million.

Cumulatively, the kingdom has relocated more than $233 million worth of Bitcoin from its identified treasury addresses throughout 2026. Approximately $162.6 million flowed into unidentified wallets, while remaining funds moved through addresses historically associated with liquidations via Galaxy Digital and OKX exchange platforms.

Bhutan’s cryptocurrency accumulation stemmed from a hydroelectric-powered mining initiative operated under Druk Holding and Investments, the nation’s sovereign investment vehicle. The program leveraged abundant renewable energy resources to mine Bitcoin while bypassing conventional banking systems.

Evidence Points to Mining Shutdown

Blockchain monitoring reveals no Bitcoin deposits exceeding $100,000 have entered Bhutan’s tracked addresses for more than twelve months. This pattern strongly indicates the mining program has either dramatically scaled back or ceased operations completely.

Druk Holding and Investments has remained silent despite numerous inquiries from journalists, ignoring email correspondence and phone attempts throughout the past week.

The profitability landscape for Bitcoin mining has fundamentally transformed. During Bhutan’s peak mining period, Bitcoin prices exceeded $90,000 while network difficulty remained comparatively moderate. Today, Bitcoin hovers around $72,000 amid record-high mining difficulty levels.

The halving event further reduced block rewards to just 3.125 BTC per block. Combined, these market conditions have squeezed profit margins for smaller-scale mining enterprises.

Another consideration involves electricity export opportunities—selling surplus hydropower to India may now yield superior returns compared to powering cryptocurrency mining infrastructure.

Institutional Buyers Continue Accumulating

Bhutan’s divestment strategy contrasts sharply with behavior among other major stakeholders. Strategy recently acquired 4,871 BTC for $330 million last weekend, expanding its total position to 766,970 BTC.

U.S.-based spot Bitcoin exchange-traded funds accumulated approximately 50,000 BTC throughout March alone. Meanwhile, the Ethereum Foundation staked $93 million in Ether within a 24-hour period rather than liquidating assets.

Bhutan represents the sole sovereign entity currently engaged in visible Bitcoin position reduction.

Bitcoin was trading above $72,000 at press time, registering gains exceeding 1.3% over the preceding 24-hour period. The cryptocurrency remains roughly 43% beneath its peak valuation of approximately $126,000 achieved in October 2025.

Bhutan’s residual 3,774 BTC holding now amounts to less than Strategy’s typical weekly purchase volume.

The post Bhutan Liquidates 70% of Bitcoin Portfolio Over 18 Months Amid Mining Slowdown appeared first on Blockonomi.

重要なポイント

Coinbaseのブライアン・アームストロングは1月の反対を撤回し、今ではCLARITY法案を支持しています

スコット・ベッセント財務長官は、即時の議会行動を求めるウォール・ストリート・ジャーナルの意見記事を執筆しました

上院銀行委員会は4月が終了する前に法案の投票を予定しています

中心的な論争はステーブルコインの利回りプログラムに関するもので、Coinbaseのような取引所がユーザーにリターンを提供できるかどうかです

シンシア・ルミス上院議員は、これは2030年までの最も早い通過の最終機会であることに注意を促しました

TLDR

BTC escaped a bear pennant formation, climbing to a six-week peak of $73,300

Key resistance territory identified by Glassnode sits in the $78,000-$80,000 range

Prediction markets on Polymarket now show 26% probability of BTC hitting $80,000 this month

Institutional Bitcoin ETF buyers accumulated 3,350 BTC valued at $240 million on Friday alone

Geopolitical developments including U.S.-Iran détente and improving macro sentiment drove BTC up almost 9% weekly

Bitcoin surged beyond the $73,000 threshold on Friday, touching a six-week peak at $73,300 following a decisive breakout from what technical analysts had identified as a bear pennant formation on daily timeframes. The advance occurred alongside elevated trading volumes, suggesting genuine buying conviction rather than thin market manipulation.

Bitcoin (BTC) Price

The cryptocurrency pierced through the pennant’s upper boundary near $70,000, delivering a 7% single-session gain. During this advance, BTC successfully recaptured multiple significant moving average levels, notably the 200-week exponential moving average positioned at $68,350 and the 50-day exponential moving average sitting at $70,580.

Technicians have also spotted a symmetrical triangle developing on daily charts. Should this pattern complete its typical trajectory, the projected upside target reaches approximately $87,000—representing roughly 20% appreciation from current pricing. Additionally, the Relative Strength Index displays bullish divergence, indicating momentum has been gradually accumulating throughout the previous two months.

#btc/usd

Bitcoin is poised to break out from the descending triangle pattern on the 4H chart
If confirmed, we could see $BTC surge toward $81,500

Crypto Traders-join Telegram https://t.co/oRAVD0i3ly
. pic.twitter.com/XdpyjHiPpS

— Whales_Crypto_Trading (@WHALES_CRYPTOt) April 10, 2026

The immediate technical obstacle for Bitcoin sits at the 100-day exponential moving average hovering near $75,400. Failure to overcome this barrier could compromise the strength of the present breakout attempt.

What Onchain Data Says About $80K

Glassnode analytics establishes a more defined upper boundary for the near-term advance. The analytics firm’s risk assessment tools highlight substantial resistance clustering between the true market mean around $78,000 and the short-term holder acquisition cost basis approximating $80,000.

“Any rally into this zone is likely to encounter meaningful distribution pressure from recent buyers seeking to exit at or near breakeven,” Glassnode said in its latest Week Onchain report.

Their Entity-Adjusted URPD metrics indicate BTC has penetrated a comparatively sparse zone spanning $72,000 to $82,000, featuring diminished supply overhead throughout that corridor. Nevertheless, over 1.3 million BTC were accumulated within the $82,000-$85,000 band, potentially establishing a formidable ceiling.

Market observer Ali Charts highlighted on X that $75,300 functions as a “magnet” for Bitcoin pricing, observing substantial liquidity concentration positioned just beyond $72,000. He suggested a movement toward $75,300 might eliminate approximately $80 million in short positions, potentially initiating a liquidation cascade.

$75,300 is a magnet for Bitcoin $BTC!

Bitcoin has reclaimed the $72,000 level, and the focus is now shifting to the massive liquidity pool sitting just above it. The shorts are trapped, and the "exit door" is getting very narrow.

A move to $75,300 would wipe out approximately… pic.twitter.com/2UHROLM3GQ

— Ali Charts (@alicharts) April 10, 2026

ETF Demand and Macro Backdrop

Regarding institutional participation, Bitcoin Archive documented on X that spot Bitcoin ETF products absorbed 3,350 BTC worth $240 million during a single trading session. These investment vehicles collectively control 721,090 BTC, representing approximately $56.75 billion in aggregate value.

Bitcoin ETFs bought 3,350 BTC worth $240M yesterday.

ETFs now hold 721,090 BTC worth $56.75 Billion. pic.twitter.com/tuSNw64wCT

— Bitcoin Archive (@BitcoinArchive) April 11, 2026

Broader macroeconomic circumstances also turned favorable for Bitcoin’s trajectory this week. Diplomatic progress toward a U.S.-Iran ceasefire agreement lifted risk-sensitive assets across markets, propelling BTC toward a weekly appreciation approaching 9%—marking its strongest weekly performance since October 2025.

March Consumer Price Index data registered 3.3%, primarily attributable to a substantial 10.9% spike in energy sector costs. Core inflation measurements, however, advanced merely 0.2% month-over-month.

On decentralized prediction platform Polymarket, participants currently assign a 26% probability to BTC achieving $80,000 during April, representing a 5% increase over the preceding 24 hours. Meanwhile, the likelihood of reaching $75,000 stands at 76%.

Bitcoin ETF products maintained holdings of 721,090 BTC valued at $56.75 billion as of Friday’s close.

The post Bitcoin (BTC) Surges Past $73K as ETFs Pour in $240M During Friday Rally appeared first on Blockonomi.

要約:

日本はRapidusの支援を163億ドルに引き上げ、2027年の2nm AIチップ生産の期限を固定しています。

新しい資金は富士通に関連する設計作業を支援し、日本の国内AI半導体スタックを強化します。

北海道のファウンドリーの進捗が省庁の審査をクリアし、6315億円の国家支援が解放されました。

Rapidusの計画は、AIコンピューティングの成長をサプライチェーンの安全性と主権チップの生産に結びつけています。

日本はRapidusに6315億円を追加し、世界最大の国家支援半導体ベットの一つを深化させました。

TLDR:

Arizona must pause criminal charges against CFTC-regulated prediction markets after the federal TRO order.

The CFTC says federal law grants exclusive authority over event contracts and market enforcement.

Connecticut and Illinois now face similar federal lawsuits over state prediction market restrictions.

The ruling strengthens legal momentum for federally supervised crypto-linked trading platforms.

A federal judge in Arizona temporarily halted the state’s criminal case against federally regulated prediction markets on Friday. The order came after the Commodity Futures Trading Commission asked the court to stop Arizona’s enforcement push. 

The ruling preserves the status quo while a broader federal preemption fight moves forward. It also sharpens the legal divide between state gambling rules and federal event contract oversight.

CFTC Arizona TRO Freezes State Prediction Markets Charges

The U.S. District Court for the District of Arizona granted the temporary restraining order on April 10. The court barred Arizona from continuing criminal proceedings against CFTC-regulated designated contract markets.

According to the CFTC filing, the agency moved earlier this week for emergency relief. That motion followed its original complaint seeking to block Arizona from enforcing state law.

The dispute centers on whether federal law preempts state gambling and criminal statutes. The CFTC argues the Commodity Exchange Act gives it exclusive authority over event contracts.

Chairman Michael S. Selig said the order keeps the legal status quo intact while the court reviews jurisdictional questions. The agency also tied the case to broader concerns around state interference in federally supervised markets.

Arizona became the first state to pursue criminal counts tied to prediction market listings, including contracts offered by Kalshi. The restraining order now pauses that path, at least temporarily.

Federal Prediction Markets Fight Expands Beyond Arizona

The Arizona action forms part of a wider CFTC legal campaign. Last week, the agency filed related complaints against Connecticut and Illinois.

Those cases seek declaratory judgments confirming exclusive federal control over event contracts. The CFTC also wants permanent injunctions blocking states from enforcing overlapping laws.

The timing matters for crypto-linked prediction markets as well. Platforms like Polymarket and Kalshi increasingly overlap with digital asset users, stablecoin settlement, and onchain market infrastructure.

Recent court decisions have already strengthened the federal side. Earlier this week, an appeals court blocked New Jersey from shutting down Kalshi’s sports markets.

Friday’s Arizona TRO adds another legal marker in the same direction. For traders and exchanges, the immediate effect is procedural, but the broader question remains federal control over fast-growing prediction markets.

The post CFTC Wins Arizona TRO as Prediction Markets Criminal Case Pauses appeared first on Blockonomi.