Crypto World
AI agents want to identify your crypto wallet using social media
Crypto influencers are taking a preprint, non-peer-reviewed research paper as a terrifying warning about a new unlock for AI agents that allegedly grants them power to deanonymize crypto wallets.
Almost all blockchains like Bitcoin and Ethereum employ pseudonymity in wallet addresses, which are usually presented as a string of characters.
Although wallet addresses are just a string of characters, AIs and easy-to-use agentic tools like Claude Cowork and Perplexity Computer are advancing the capabilities of casual users to deanonymize them.
According to their research, new versions of AI are gaining the power to conduct large-scale deanonymization by taking in posts by billions of humans and linking distinct usernames using highly-processed probability scores.
This is akin to making educated inferences that the person behind one username is likely the same person behind another username.
Researchers used Claude tools by the AI giant Anthropic. The paper is a preprint and as such hasn’t been accepted for publication in a peer-reviewed academic journal. However, its conclusions are potentially disturbing and reinforce concerns about crypto privacy.
Exploiting a common opsec error
Unfortunately, many people re-use the same crypto wallet addresses. Although this is bad practice from an operational security (OpSec) and privacy perspective, the commonplace occurrence allows researchers to glean and infer a tremendous amount of information.
Tracing and deanonymizing crypto has been popular for years at Chainalysis, Elliptic, TRM, Crystal, Coinglass, and Arkham.
However, the use of AI agents to easily link wallets to social and internet platforms is the breakthrough.
Users of Claude Cowork or Perplexity Computer are already asking AI to connect crypto wallets to activity elsewhere.
Read more: AI Agent BadCoin fumbles BSC launch, anti-sniping software flags traders
Four stages of AI deanonymization
Researchers automated hours of manual research by building a pipeline with four stages:
- In the “extract” step, AI agents searched for identity-relevant data from social posts that indicated interests and writing style. Importantly, the researchers used raw, unstructured text directly from social networks.
- The “search” step encoded the extracted data to perform “nearest neighbor” queries across tens of thousands of candidate profiles.
- Next, the “reason” phase applied multi-stage, LLM logic using ChatGPT to select the most likely match.
- Finally, the “calibrate” stage asked other AI models to double-check, error-correct, and assign confidence scores. This allowed the researchers to present their inferences as to which usernames across social networks were likely the same person.
Although researchers didn’t focus on crypto wallets specifically — they focused on linking Reddit, Hacker News, and LinkedIn profiles — the implications for crypto are obvious.
Most concerningly, their financial cost per deanonymization attempt was, in many cases, less than $4, putting the capability of deanonymization well within reach of even conservatively funded adversaries.
Mert Mumtaz, CEO of Helius Labs, amplified the research within the crypto community.
Blockchain transactions are visible to anyone. Although crypto is already accustomed to the use of machine learning, heuristics, and clustering algorithms to link wallet addresses to real-world identities by correlating on-chain behavior with off-chain data, this new research demonstrates how off-blockchain data sets like forum posts and social media activity are now exponentially larger in size and trivially automatable.
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Bitrue reported a 212% surge in spot buying for XRP on February 26, with buy orders more than doubling sell pressure.
Bitrue said on February 26 that it recorded a 212% jump in XRP spot buying as institutional investors continued allocating capital through newly launched XRP exchange-traded funds (ETFs).
The exchange linked the spike to roughly $1.1 billion in cumulative ETF inflows, arguing that steady demand from funds and retail traders could tighten available supply in the months ahead.
Spot Buying Jumps as ETF Inflows Build
In a post on X, Bitrue said XRP buy orders on its platform outpaced sell orders by more than two to one.
“We recorded a 212% increase in XRP spot purchase volumes, outpacing the sell side by over 2x,” the exchange posted on X.
It attributed the imbalance to sustained institutional accumulation since the debut of XRP ETFs, which it claims have drawn $1.1 billion in net assets, even though data from SoSoValue showed there have been muted ETF flows in recent days.
However, the derivatives market tells a different story. According to CryptoQuant, XRP futures open interest has fallen across major platforms over the past 90 days, with Binance recording a decrease of 7.7 million XRP and Bybit showing a larger reduction of around 12 million tokens. Furthermore, the three-month moving average for XRP futures volume has dropped to its lowest level since November 2024, settling at approximately $87 billion.
Looking at XRP’s broader market structure, it was trading around $1.44 at the time of writing, up nearly 5% in the last 24 hours and about 2% during the week. Even so, the token is still down more than 23% over the past month and almost 38% across the past year, far below its July 2025 all-time high of $3.65.
Cooling Leverage Meets Steady Spot Demand
The divergence between spot accumulation and falling derivatives activity suggests a shift in market composition rather than uniform bullish momentum. Open interest now stands near $2.37 billion per CoinGlass figures, and the contraction in leveraged positions may reflect traders reducing risk after months of volatility.
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From a price standpoint, XRP remains range-bound between $1.38 and $1.48 over the past 24 hours. One market watcher, CasiTrades, flagged resistance around $1.40 and $1.65, with support near $1.11 and $0.87. According to them, a sustained move above those resistance levels would likely require stronger follow-through from ETF inflows and broader market participation.
As such, considering the broader data, Bitrue’s reported spike in spot buying highlights firm exchange-level demand, but the wider data show a market that is rebalancing rather than accelerating.
Nonetheless, the crypto exchange is predicting that growing retail and corporate support could lead to a supply deficit that may push up the Ripple token’s performance enough to beat major rivals this year.
“With support increasing from retail and institutional levels, Bitrue is forecasting a potential supply squeeze, which will likely result in XRP outperforming key competitors over Q2 2026,” wrote Bitrue.
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Ether (ETH) price reached a weekly high of $2,150 on Thursday, which is a key level for large ETH holders, but volatility in the crypto and stock markets continues to catalyze corrections below $2,000.
A daily close above $2,100 remains important because that level aligns with the cost basis and realized price of wallets holding 100,000 or more ETH. Realized price tracks the last moved price of coins, offering a profitability gauge rather than a spot reference.
Since 2020, Ether has traded below this whale cohort’s realized price only a handful of times, most notably during the 2022 bear market. The chart shows that the price has regularly recovered after the realized price level was tested as support.
Futures market analyst Dom described the setup as “a good clean look for the whole market,” pointing to an early-week sweep near the range lows. Dom said that the price tapped the one-month rolling VWAP (volume-weighted average price) and the value area high, the upper boundary of the price range where most of the volume traded over the past month.
The VWAP measures the average traded price weighted by volume. Acceptance over $2,140 may mark a shift in short-term order flow, while failure to retain a higher level keeps the price inside the established range.
Related: Longest Ether dip since 2022 ignored by whales: What’s next for ETH?
$1,800 remains the key price level to watch
CoinGlass data highlighted short liquidations of over $220 million over the past two days, clearing overhead leverage. Now, roughly $2.66 billion in cumulative long liquidation exposure sits near $1,800, forming a liquidity pocket below the price.
Crypto analyst Pelin Ay pointed to a notable shift in funding rates on Binance. ETH funding flipped sharply negative earlier this month as aggressive short positions piled in alongside Ether price weakness. Following Tuesday’s drop below $1,800, the funding rate has since swung back into positive territory at 0.23%, a sign that late shorts were squeezed out of their positions.
However, with the funding rate now elevated, traders’ positioning appears to be tilting toward the long side. If this trade becomes overcrowded, it raises the risk of a potential long squeeze near the $1,800 level once again, especially if the price momentum stalls or reverses.
Market analyst IncomeSharks identified three technical hurdles, including repeat super trend rejections and a channel resistance near $2,250.
The SuperTrend uses volatility, measured by the average true range (ATR), to define the trend direction. When the price trades below the indicator, the line flips red and acts as dynamic resistance. On the chart above, each rebound has been rejected at the red band, signaling that sellers remain in control.
The analyst added that traders should watch whether Ether revisits or finds renewed buying interest near the April lows around $1,500, a level that resides between a weekly demand zone of $1,691 and $1,384, before any sustained move above $2,500 can take shape.
Related: Ethereum reclaims $2K as volatility spike backs ETH price recovery
This article does not contain investment advice or recommendations. Every investment and trading move involves risk, and readers should conduct their own research when making a decision. While we strive to provide accurate and timely information, Cointelegraph does not guarantee the accuracy, completeness, or reliability of any information in this article. This article may contain forward-looking statements that are subject to risks and uncertainties. Cointelegraph will not be liable for any loss or damage arising from your reliance on this information.
Real estate mogul Grant Cardone is preparing to tokenize his firm’s $5 billion real estate portfolio, the latest property heavyweight to explore blockchain-based ownership.
In a Thursday X post, the investor said that Cardone Capital plans to tokenize its holdings to give investors “collateral and liquidity in the secondary markets.” He added that the firm aims to become a market leader in tokenizing assets at scale.
Cardone Capital manages multi-family and commercial properties across the U.S. In January, CoinDesk reported that Cardone was planning to use real estate cash flow to buy bitcoin as part of a long-term crypto strategy. The firm purchased 1,000 BTC in June and has said it intends to add more to its balance sheet
Tokenization is attracting more and more asset managers to turn traditional assets such as bonds, funds, private credit and real estate into tokens on blockchain rails. In the case of real estate, supporters say that tokenization can streamline ownership record-keeping, trading and settlement. However, uneven regulation remains a bottleneck and thin secondary trading can limit liquidity, a report by EY pointed out.
Other real estate leaders are exploring similar paths. The Trump Organization, the real estate conglomerate of Donald Trump and his family, is tokenizing loan revenue tied to a new Maldives resort project. Barry Sternlicht of Starwood Capital, which manages over $125 billion, recently said his firm is ready to tokenize assets but faces U.S. regulatory barriers.
The tokenized real estate market remains small yet but projected to grow rapidly over the next decade. Deloitte forecasted that $4 trillion in real estate could be tokenized by 2035, growing 27% annually.
Solana price has turned corrective after losing key support near $88, pushing price back into its previous trading range. The shift in market structure now places $78 support at risk as downside pressure builds.
Summary
- Loss of $88 support flips level into resistance
- Price re-enters established trading range structure
- $78 value area low becomes next key downside support
Solana’s (SOL) recent price action signals a transition away from bullish continuation and back into range-bound conditions. After failing to hold above a major technical level, the market has begun rotating lower, reflecting weakening momentum and growing seller control.
The loss of a key support zone has altered short-term structure, increasing the probability that Solana revisits lower range support before any sustained recovery can develop.
Solana price key technical points
- Lost Support: $88 level flips into resistance alongside the value area high.
- Structural Shift: Price has re-entered its previous trading range.
- Downside Target: $78 aligns with the value area low and high timeframe support.
Solana recently lost the important $88 level, which previously acted as a structural support zone. This area also aligned with the value area high, making it a strong technical confluence region. When price loses a value area boundary, it often signals rejection rather than continuation, forcing markets back toward equilibrium within the established range. The failure to hold above this level confirms that buyers were unable to maintain control following the prior recovery attempt.
With the loss of $88 support, Solana has effectively reverted into its previous trading range. Range environments typically trap price action between clearly defined highs and lows, creating rotational market behavior rather than trending movement. In this case, the range low and major support zone sits near $78, which coincides with the value area low and high timeframe demand.
This comes as Step Finance announced it will shut down its Solana-based platforms following a January exploit that drained roughly $40 million, adding to cautious sentiment surrounding the ecosystem.
Currently, price action is hovering near the Point of Control (POC), the level representing the highest volume traded within the range. The POC often functions as equilibrium between buyers and sellers. Solana barely holding this level suggests market indecision, but it also signals vulnerability. A confirmed close below the POC would indicate acceptance at lower prices, significantly increasing the probability of a move toward range support.
From a market structure perspective, the current movement appears corrective rather than impulsive. Corrective phases typically unfold through gradual rotations toward liquidity pools where demand previously emerged. The absence of strong bullish continuation after losing support further reinforces the corrective bias. Without reclaiming $88 resistance, upside momentum remains limited.
Volume dynamics also support the corrective outlook. The recent decline has not been met with strong accumulation signals, suggesting buyers are waiting at deeper value zones rather than defending mid-range prices. This behavior is common within established ranges, where participants prefer to engage at extremes rather than within the middle of consolidation.
If Solana continues to trade below former support turned resistance, price action is likely to gravitate toward the lower boundary of the range. The $78 level therefore becomes a critical area to monitor. A reaction at this support could trigger a relief bounce or range continuation, while a breakdown below it would expose Solana to a broader structural reset. This comes as Zora expanded onto the Solana blockchain with the launch of its new “attention markets” platform, signaling continued ecosystem development despite the current corrective structure.
Despite the short-term weakness, range environments are not inherently bearish. Instead, they represent periods of market balance where liquidity accumulates before the next major expansion. For now, Solana remains confined within this structure, with directional clarity dependent on either reclaiming resistance or testing deeper support.
What to expect in the coming price action
Solana is likely to continue rotating within its established trading range unless bulls reclaim the $88 resistance level. Failure to hold the POC increases the probability of a move toward $78 support, where the next meaningful reaction is expected to occur.
Sonic price remains under heavy selling pressure as an aggressive downtrend continues to dominate market structure. Consecutive lower highs and lower lows now place yearly support at risk of breaking.
Summary
- Aggressive downtrend confirmed by lower highs and lower lows
- Price trades near yearly low below 0.618 Fibonacci extension
- Lack of bullish volume signals continued downside risk
The Sonic (S) token continues to trade within a firmly established bearish trend, with price action showing little evidence of stabilization. Recent market behavior reflects persistent seller control, as rallies into resistance repeatedly fail and lead to further downside continuation.
With momentum weakening and bullish participation absent, the market now approaches a critical inflection point where a new yearly low may soon be confirmed.
Sonic price key technical points:
- Trend Structure: Clear sequence of lower highs and lower lows confirms strong downtrend.
- Key Level: Price trading near yearly low below the 0.618 Fibonacci extension.
- Market Bias: Lack of bullish volume suggests continuation of bearish momentum.
Sonic’s corrective phase has evolved into a sustained and aggressive downtrend characterized by repeated bearish retests and continuation moves lower. Each attempt at recovery has been met with selling pressure, reinforcing resistance zones and preventing any meaningful trend reversal. This pattern of failing rallies highlights the dominance of sellers and reflects a market environment where confidence remains weak.
From a technical perspective, the sequence of lower highs and lower lows is one of the clearest signals of bearish market structure. Instead of forming consolidation or accumulation patterns, Sonic has continued to trend downward with consistent momentum. Resistance levels that previously acted as support have flipped decisively into supply zones, creating a cascading effect where price struggles to regain higher ground.
Currently, Sonic trades near the absolute yearly low region while remaining positioned below the 0.618 Fibonacci extension, a level often associated with trend continuation during strong directional markets. A confirmed breakdown below this region would establish a new yearly low and validate the ongoing bearish projection.
Such price behavior typically signals continuation rather than exhaustion, particularly when volume does not show signs of aggressive buying interest.
Volume analysis further strengthens the bearish outlook. Throughout the decline, bullish volume has remained muted, suggesting limited demand at current prices. Reversal scenarios generally require expanding buy-side participation and structural reclaim of key resistance levels. At present, neither condition is visible, indicating that the market has yet to enter a recovery phase.
Market participants should also consider the psychological impact of prolonged downtrends. Extended periods of selling often reduce trader confidence, encouraging defensive positioning and short-term selling on rallies. Until Sonic can reclaim a meaningful high timeframe resistance level, upside attempts are likely to remain corrective rather than impulsive.
This comes as Sonic Labs CEO Mitchell Demeter outlines the key steps layer-1 blockchains must take to remain competitive, underscoring the broader strategic challenges facing the sector amid persistent market weakness.
Despite the weakness, markets rarely move in straight lines indefinitely. Short-term relief bounces may occur as oversold conditions develop; however, such moves would likely function as temporary pauses within the broader bearish structure unless accompanied by strong volume expansion and structural shifts.
From a broader market structure standpoint, Sonic remains trapped in a persistent downtrend where liquidity continues to build below price. As long as resistance levels remain intact, the path of least resistance favors further downside exploration.
What to expect in the coming price action
Unless Sonic reclaims high timeframe resistance and attracts meaningful bullish volume, the probability favors continuation toward new yearly lows. The prevailing bearish structure suggests downside pressure will persist, with any rallies likely serving as corrective retests rather than a confirmed trend reversal.
NVIDIA Stock just delivered a record-breaking Q4 with $68.1 billion in revenue, 73% year-over-year growth, and earnings per share of $1.62 that crushed estimates. JPMorgan, among others, wasted no time raising its price target from $250 to $265.
Yet on February 26, the stock fell nearly 7% from its session high of $197 to under $185. The results are undeniable. But the price action, the money flow, and the institutional behavior tell a very different story. At least, for now.
The Numbers Look Bulletproof, Until You Look Closer
NVIDIA’s Q4 numbers speak for themselves. Revenue hit $68.1 billion, up 73% year-over-year. The data center segment alone pulled in $62.3 billion, making up 91% of total revenue. EPS (Earnings Per Share) of $1.62 beat the $1.53 consensus by nearly 6%.
And the Q1 FY2027 guidance of $78 billion blew past Wall Street’s $72.8 billion estimate — a figure that notably excludes any revenue from China.
JPMorgan analyst Harlan Sur responded by lifting the Nvidia price target from $250 to $265.
But here is what most analysts are not highlighting. NVIDIA’s quarter-over-quarter growth rate is quietly decelerating. Q3 grew 22% over Q2. Q4 grew 19.5% over Q3.
The Q1 guidance implies roughly 14.5% sequential growth. Revenue keeps hitting records, but the pace of acceleration is fading. For a stock priced on growth momentum, this distinction matters. Something big money might be watching.
There is also the question of who is actually driving this revenue. Deepwater Asset Management’s Gene Munster estimates that roughly 70% of Nvidia’s revenue comes from just 8 companies.
CFO Colette Kress confirmed that the top 5 hyperscalers (cloud computing providers) account for slightly over 50% of data center revenue. That level of customer concentration means that even a modest 10-15% reduction in AI capex from a few major buyers could translate into billions in lost quarterly revenue.
It is also worth noting that JPMorgan’s asset management division is itself a significant institutional holder of Nvidia.
This is standard on Wall Street, but it is a context that retail investors should be aware of when evaluating the bullishness behind a price target upgrade.
What Retail NVDA Investors See vs What Institutions Are Doing
On-Balance Volume (OBV), an indicator that tracks cumulative buying and selling pressure by adding volume on up days and subtracting it on down days, tells a positive story on the surface.
OBV has maintained higher highs throughout Nvidia’s 3-month consolidation, suggesting retail-driven buying pressure remains consistently positive. However, it still needs to break past its ascending trendline resistance to confirm genuine broad-based strength.
The most recent 13F filings (quarterly reports large investors must file with the SEC revealing their positions) for Q4 2025 show a dramatic shift in institutional sentiment.
Net institutional money flow surged to approximately $149 billion in purchases against $36 billion in sales — a net inflow of roughly $113 billion. That is a massive improvement from Q3, where institutions bought $38 billion and sold $34 billion, leaving a net inflow of just $4 billion.
Yet despite this wall of institutional money entering NVDA in Q4, the stock barely moved — trading sideways for most of the period. That suggests institutions were accumulating, but supply from insiders and earlier holders absorbed the demand. NVIDIA director Mark Stevens sold approximately $40 million in shares in December.
Bank of America, while slightly increasing its equity stake, closed out both its call and put options positions entirely — neutralizing its directional bets.
Institutions are clearly positioned. But the hedging and the flat price despite massive inflows suggest they are bracing for something. The next section explores what that might be.
The Risk Hiding in the Charts
The Chaikin Money Flow (CMF), an indicator that measures whether money is flowing into or out of a stock based on where the price closes within its daily range weighted by volume, reveals what the earnings headline does not.
Since February 5, as the right shoulder of Nvidia’s inverse head and shoulders pattern formed, CMF climbed steadily alongside the price. It rose all the way into the February 25 earnings breakout when Nvidia briefly touched $197.
Then on February 26, as the stock reversed sharply to $185, CMF plunged.
That sudden collapse suggests the money flowing in during the rally was speculative positioning — not committed institutional capital — and it evaporated the moment the breakout failed. And based on what we discussed earlier, revenue deceleration could be a reason.
The monthly VWAP (Volume Weighted Average Price, which approximates where institutions have built their positions) reinforces this. NVIDIA had been trading above its monthly VWAP since breaking out on February 17.
The last time Nvidia broke below the monthly VWAP was on January 30, which led to a correction of approximately 8.5% by early February.
As of February 26, the stock has once again fallen below this line. This means recent institutional buyers are now underwater, which historically triggers further selling as stop losses unwind.
The technical breakdown has context. Michael Burry flagged today that Nvidia’s supply commitments have ballooned to levels that mirror Cisco before the dot-com bust — a company that wrote down billions when demand didn’t meet expectations.
CFO Kress acknowledged Nvidia has locked in inventory “further out in time than usual.” Bulls like BofA’s Vivek Arya argue this secures Nvidia’s dominance. But CMF collapsing and VWAP breaking on the same day suggests the market isn’t waiting to find out who’s right.
The NVIDIA Stock Price Levels That Decide What Happens Next
The charts, the money flow, and the institutional positioning all point to the same conclusion — $195 is where conviction gets tested, a level highlighted later on the chart. But first, the risk.
On the daily chart, a hidden bearish divergence has formed between November 10 and February 25. During this period, the NVIDIA stock price made a lower high while the Relative Strength Index (RSI), a momentum indicator, made a higher high
It is a signal that upward momentum is quietly fading even as the stock appears to hold its range.
Since that November divergence started developing, Nvidia has been locked between $169 and $199. It couldn’t break out of this consolidation despite multiple attempts — including the inverse head-and-shoulders breakout on February 25, which failed within 24 hours.
The Fibonacci extension levels from the pattern now frame what comes next. On the downside, $183 at the 0.5 level is the immediate support. Below that, $180 at the 0.382 level becomes critical — a break there exposes $170, the right shoulder low, and $169, the head. Those levels would invalidate the pattern entirely.
On the upside, the neckline at $195 remains the key resistance and the conviction tester. A clean daily close above it, which the NVIDIA stock failed to do yesterday, is needed to reactivate the pattern.
That could push it towards the projected target at $226, the full head-to-neckline measurement.
The next extension at $235 brings it closer to JPMorgan’s $265 target. The path exists on paper.
But as the money flow, the hidden bearish divergence, and today’s 7% rejection all confirm, this is a market that’s not buying it yet.
Licensing Expansion to Cover Dealers and Custodians
The government will introduce a bill this year to license digital asset dealers and custodians. The proposal will expand regulation beyond trading platforms and bring more service providers under formal supervision. As a result, authorities aim to close regulatory gaps and strengthen operational standards.
Officials structured the reforms under Hong Kong’s second digital asset policy statement. The framework seeks to balance innovation with clear compliance obligations across the market. At the same time, regulators intend to reinforce market integrity and financial stability.
The Securities and Futures Commission will oversee key parts of the expanded regime. It plans to broaden approved products and services for professional participants. In addition, the regulator will launch an accelerator program to support compliant financial technology development.
Stablecoin Licensing and Market Liquidity Measures
Authorities have confirmed that Hong Kong has implemented a licensing system for fiat-referenced stablecoin issuers. The first batch of licenses will be granted next month under the new framework. Consequently, the city will move from regulatory planning to live market authorization.
Regulators will work with approved issuers to develop controlled and compliant use cases. Officials aim to integrate stablecoins into payment and settlement activities within clear risk parameters. Meanwhile, authorities will monitor issuance structures and reserve management standards.
The Securities and Futures Commission will also take steps to deepen digital asset market liquidity. It will expand the scope of eligible instruments and services available to professional market participants. Therefore, policymakers expect stronger capital flows and improved price discovery across platforms.
Hong Kong’s broader strategy reflects rising global competition among financial centers. Several jurisdictions have advanced stablecoin and tokenization rules in recent years. In response, Hong Kong has accelerated its regulatory timetable to maintain regional leadership.
Tokenized Bonds and OECD Reporting Framework
Tokenization forms another core pillar of the government’s digital asset strategy. Authorities will issue guidance allowing debenture holder registers to operate on distributed ledger systems. This clarification will support legal certainty for tokenized bond structures.
Officials will also explore electronic signatures for bond issuance documents. In parallel, authorities will examine the digitalization of bearer bonds within existing legal boundaries. These measures aim to modernize debt markets while preserving regulatory oversight.
Hong Kong has already experimented with tokenized green bond issuance in recent years. Those pilot projects demonstrated operational feasibility and settlement efficiency. Building on that experience, policymakers now seek broader institutional adoption.
At the same time, the government will amend the Inland Revenue Ordinance. The changes will implement the OECD Crypto-Asset Reporting Framework and the updated Common Reporting Standard. A bill is expected in the first half of this year.
The new reporting rules will strengthen cross-border tax transparency for digital asset transactions. Authorities intend to align Hong Kong with global standards on financial disclosure. Therefore, the reforms will address tax compliance while supporting market credibility.
Together, the licensing expansion, stablecoin approvals, and tokenization guidance mark a coordinated policy push. The measures integrate regulation, innovation, and tax reporting into a unified framework. As implementation begins, Hong Kong positions itself as a structured and competitive global digital asset hub.
The AI-driven data-center expansion is increasingly financed through debt, and lenders are weighing risk and opportunity in the AI-infrastructure and crypto-mining nexus. TheEnergyMag’s latest newsletter tracks roughly $33 billion in long-term senior notes raised over the past 12 months, excluding convertible debt, underscoring how traditional lenders view capture risk and growth potential in this space. In parallel, debt markets show widening spreads: AI- and crypto-linked issuers typically pay 7%–9% coupons, versus 4%–5% for regulated utilities. The momentum comes as Nvidia reports robust AI demand, while Bitcoin miners map a path toward dozens of gigawatts of new power capacity to support AI workloads.
Key takeaways
- AI data-center issuers have raised about $33 billion in long-term senior notes over the past year, excluding convertible debt, illustrating the scale of capital chasing AI compute capacity tied to crypto operations.
- Debt pricing shows a notable spread: AI/crypto-linked papers are typically priced around 7%–9% coupon, compared with 4%–5% for traditional regulated utilities.
- Recent placements include CoreWeave at 9.25% in May 2025 and 9% in July 2025, Applied Digital at 9.2% in November 2025, TeraWulf at 7.75%, and Cipher Mining at 7.125% and 6.125% as part of diversified AI-infrastructure financing.
- Nvidia’s fourth-quarter results underline sustained AI demand as a macro driver for data-center investments, with net income at about $43 billion and revenue near $68.1 billion, up sharply year over year.
- Bitcoin miners are targeting roughly 30 gigawatts of new power capacity to run AI workloads, a figure that would nearly triple current capacity and signal a coordinated push into AI-centric compute.
Tickers mentioned: $BTC
Sentiment: Neutral
Market context: The move to finance AI infrastructure via high-yield debt sits at the intersection of AI demand, crypto mining expansion, and a debt market that increasingly values long-dated, growth-oriented assets with offtake risk. As lenders price risk, capital flows reveal how investors are balancing the prospect of AI-driven compute with the volatility and energy-intense nature of crypto operations.
Why it matters
The current financing environment highlights a broader redefinition of what counts as infrastructure in the digital era. Projects that blend AI compute with crypto mining—whether repurposed data centers or greenfield AI data-hub builds—are increasingly treated as growth credits rather than traditional utility-style assets. This shift matters for developers and investors because it widens the pool of potential capital, but at a higher financing cost reflective of perceived tail risks, project complexity, and energy demand. The elevated coupons imply lenders are pricing in uncertainties around offtake arrangements, energy supply contracts, and regulatory risk, even as long-term demand for AI workloads remains a tailwind for data-center-heavy businesses.
The Nvidia earnings backdrop reinforces how AI compute can catalyze investment waves across adjacent sectors. Nvidia’s fourth-quarter performance—net income of about $43 billion and revenue of $68.1 billion, with year-over-year profit growth approaching the mid-to-high double digits—signals robust demand for AI accelerators and the compute capacity that data centers must deliver. While Nvidia is not a crypto-specific company, its results illuminate the demand side of AI infrastructure that, in turn, informs how lenders price risk for related projects. In parallel, Bitcoin miners’ plans to pursue roughly 30 gigawatts of new power capacity for AI workloads suggest a deliberate alignment between hash-rate economics and AI compute needs, potentially shaping energy markets and grid usage for years to come.
The financing narrative also underscores why some observers view the AI-infrastructure supercycle as broader than crypto alone. The sector’s access to capital hinges on how easily developers can secure long-duration debt with credible offtake, and how regulators and utilities respond to aggregate energy demand. The mix of blue-chip AI demand signals and crypto-driven compute pipelines paints a picture of a market that is increasingly comfortable funding ambitious buildouts—yet only under terms that reflect the complexity and risk of these multi-use facilities.
For readers tracking the intersection of AI, crypto, and infrastructure finance, the core takeaway is clarity: lenders are increasingly differentiating between steady, regulated load and growth-oriented, asset-light models that rely on AI-driven demand. That distinction translates into a bifurcated debt market where some projects on the frontier of AI infrastructure can access capital at high yields, while others with less certain offtake or regulatory clarity may see more muted appetite. The practical implication is a potential deceleration in some buildouts if the cadence of funding slows or if risk pricing tightens further, even as marquee projects with visible AI demand and confirmed long-term offtake can attract funding dollars more readily. The convergence of AI compute, crypto mining, and energy capacity decisions therefore remains a critical lens for investors navigating 2026 funding cycles.
Links and references from the reporting track the contours of this evolution. For instance, recent bonds tied to AI infrastructure were highlighted by TheEnergyMag’s analysis, which cites deals ranging into the 7%–9% coupon band. The same narrative is echoed in a presentation from Janus Henderson Investors, drawing on research from BofA Global Research, that underscores selective issuance in the high-yield space for 2026. At the project level, public disclosures and industry reporting have highlighted strategic moves by miners and AI infrastructure players, including stakes and capacity expansions in U.S. sites and AI-driven data-center deployments, which you can corroborate through industry updates linked below.
Related coverage includes a Canaan-led expansion in Texas mining sites and a Google-backed stake in Cipher Mining as part of broader AI-deal strategies that tie mining assets to compute demand. These developments illustrate how the collateral base for crypto-related data centers is expanding beyond traditional power contracts to include AI workloads and software-defined infrastructure. The broader takeaway is that the convergence of AI and crypto compute is reshaping both the risk-return profile and the capital allocation frameworks for data-center projects across the sector.
For readers seeking the underlying documents and official statements shaping these conclusions, the linked materials offer direct insight into issuer terms, credit ratings, and the strategic narratives driving these financing choices. The discussion remains dynamic: as AI adoption accelerates, lenders will recalibrate risk premia, and developers will adapt by locking in offtake commitments, hedging energy costs, and exploring hybrid models that blend traditional infrastructure with growth-oriented, AI-enabled compute.
What to watch next
- Upcoming bond issuances by AI-infrastructure developers and crypto-mining operators, including pricing, term sheets, and offtake arrangements.
- Regulatory developments affecting data-center expansions, energy usage, and crypto mining operations that could influence debt pricing and project viability.
- Updates on AI workload adoption by mining-centric or multi-use data centers, with potential implications for energy demand and grid resilience.
- Further commentary from chipmakers and AI platforms on demand trajectories and capital expenditure plans that could influence future risk pricing.
Sources & verification
- TheEnergyMag newsletter tracking about $33 billion in long-term senior notes tied to AI data-center and related projects: https://www.minerweekly.com/p/33-billion-bonds-ai-arms-race?
- Janus Henderson Investors article on high-yield bonds outlook citing BofA Global Research: https://www.janushenderson.com/en-ch/investor/article/high-yield-bonds-outlook-increasing-selectivity-in-2026/
- Canaan’s stake expansion in Texas mining sites: https://cointelegraph.com/news/canaan-buys-49-stake-texas-bitcoin-mining-sites-40m
- Google’s stake in Cipher Mining as part of an AI deal: https://cointelegraph.com/news/google-acquires-5-4-stake-in-bitcoin-mining-company-cipher-mining-in-ai-deal
AI infrastructure financing reshapes risk in crypto data centers
The 2026 US midterm elections are increasingly viewed as a potential catalyst tied to liquidity cycles and broader crypto market recovery.
The US midterm elections scheduled for Q4 2026 are increasingly being discussed as a potential macro catalyst for financial markets.
This includes crypto, amid expectations of changing liquidity conditions.
Asset Prices, Not Politics
According to a macro thesis by market participant ‘Egrag Crypto,’ early signals from betting markets point to relative Republican weakness, which could raise incentives for market-friendly economic conditions heading into the election window.
The framework outlines a three-phase timeline, which begins with a broader market correction in early 2026, during which criticism is expected to intensify toward Federal Reserve Chair Jerome Powell.
This is followed by mid-2026 pressure for a change in monetary stance, which could potentially result in liquidity easing as policymakers respond to economic and political constraints. Under this scenario, markets could enter a recovery phase in the second half of 2026, aligning with the election period.
The thesis argues that rising asset prices tend to improve public sentiment rapidly, supported by factors such as dividend income, potential tax relief for small businesses, and broader “feel-good” economic conditions. They further suggest that the Federal Reserve often becomes a focal point for blame during downturns, which, in turn, allows political narratives to shift as liquidity conditions improve.
As such, the view validates the idea that market structure and liquidity trends may play a leading role in shaping political outcomes, rather than political developments acting as the primary driver of markets.
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“Structure first. Politics later. Markets always lead.”
2024 Flashback
In 2024, the cryptocurrency market saw significant price rallies following Donald Trump’s election victory. Bitcoin rose to record highs on investor optimism about a potentially more crypto-friendly regulatory environment and pro-crypto lawmakers in Congress.
However, by early 2026, much of the post-election upside had been eroded. Bitcoin, for one, retreated toward $60,000, and broader crypto sentiment cooled amid macro pressures and fading Trump-driven euphoria.
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Bitcoin (BTC) has rebounded 7.45% over the past two days after dropping to $62,400 on Tuesday, below a key onchain price support. Despite the bounce, holders who bought between six months and two years ago remain at an average cost of $74,500, a level that now stands as a potential inflection level.
As BTC moves higher, the concentration of supply around $74,500 stands as a key test for the current trend; a decisive reclaim of that level may signal demand and a shift in short-term market structure.
Why $74,500 matters to Bitcoin bulls
Bitcoin’s realized price tracks the average onchain acquisition cost for a given UTXO age band. For coins aged 18 to 24 months, that level stands near $64,200.
Crypto analyst Anıl noted that Bitcoin tested this threshold and reclaimed it by the daily close on Tuesday, keeping the zone intact for now.
Cost basis levels act as psychological pivots and when the price trades below them, investors face unrealized losses and the risk of distribution increases. A sustained position above the band tends to reduce investor stress and encourages BTC re-accumulation.
Expanding the lens to BTC UTXOs aged six months to two years captures investors from the prior cycle’s consolidation and breakout phases. The realized price for these cohorts is near $74,500, which is well above the current price.
The cohort’s MVRV ratio, which compares market value to realized value, now sits at 0.88. A reading below 1 signals that the group is, on average, holding at a loss.
As Bitcoin fell below $74,500, investors who bought between six months and two years ago moved into unrealized losses, turning that level into an important profitability threshold.
A sustained move back above $74,500 places much of this group back in aggregate profit, which may ease sell-side pressure from holders looking to exit near their breakeven price.
BTC long-term supply climbs to 3-month high
Onchain supply data from CryptoQuant shows that the long-term holder balance is back near 14 million BTC (13.96 million) after falling to a multi-year low on November 21, 2025. The recovery in the aged supply points to continued coin dormancy despite recent volatility.
If investors who bought between six months and 2 years ago choose to hold and absorb selling near their average entry price, the supply sitting between $74,500 and $100,000 may thin out more quickly.
A sustained rally above $74,500 may push a large portion of these coins back into profit, potentially shifting focus toward liquidity near $100,000.
Related: GD Culture Group board authorizes Bitcoin treasury sales
BTC realized cap and capital flows remain flat
An uptick in BTC’s realized cap, which measures the aggregate value of coins based on their last onchain movement price, may also signal a trend shift.
The metric is holding near cycle highs, though its rate of expansion has slowed. The realized cap net position change has compressed toward neutral or 0%, signaling that capital inflows are negligible.
While the realized cap remains near all-time highs, it is trending lower, indicating a slowing pace of new capital entering at the higher cost basis levels.
Historically, late bear market phases tend to show flat, or contracting realized cap, while early recoveries begin with stabilization before acceleration. A renewed expansion in the net position change back toward the 2–4% range may provide clearer confirmation that fresh capital is re-entering and that accumulation is on the rise.
Related: Bitcoin’s upcoming $10.5B options expiry may end bear market: Here’s how
This article does not contain investment advice or recommendations. Every investment and trading move involves risk, and readers should conduct their own research when making a decision. While we strive to provide accurate and timely information, Cointelegraph does not guarantee the accuracy, completeness, or reliability of any information in this article. This article may contain forward-looking statements that are subject to risks and uncertainties. Cointelegraph will not be liable for any loss or damage arising from your reliance on this information.
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