The so-called Fish-to-Shark cohort added 110,000 BTC over the past 30 days, according to Glassnode.
Institutional crypto platform Anchorage Digital is looking to raise hundreds of millions of dollars of fresh capital as it eyes a potential Initial Public Offering.
The raise would be in the $200 million to $400 million range, while a possible IPO is slated for sometime next year, according to a Bloomberg report on Friday, citing people familiar with the matter who asked to remain anonymous.
Anchorage’s affiliate, Anchorage Digital Bank National Association, became the first federally chartered crypto bank in 2021 and is now well-positioned to lead stablecoin issuance and related services following the passage of the GENIUS Act in July.
Anchorage CEO Nathan McCauley said in September that he planned to double the company’s stablecoin team over the next year to accommodate the expected boom in digital dollars.
“2025 was our year of scale. We made a series of acquisitions, inked major partnerships, and launched new business lines like stablecoin issuance to solidify our lead in institutional crypto,” an Anchorage spokesperson told Bloomberg.
One of those partnerships included Tether, the issuer behind the largest stablecoin, USDT, with the two companies announcing plans in September to launch a USAT token in the US.
Anchorage is expanding its crypto offerings
Anchorage also provides custody, trading, and staking services for banks, hedge funds, and venture capital firms, acting as a regulated bridge for TradFi players to access crypto.
In December, Anchorage also expanded its wealth management arm through the acquisition of Securitize For Advisors and token lifecycle management by integrating Hedgey.
Related: Goldman Sachs CEO says CLARITY Act ‘has a long way to go‘
Anchorage secured $350 million in funding late 2021, led by KKR & Co, with participation from Goldman Sachs, GIC, and Apollo credit funds.
Anchorage’s valuation was marked at over $3 billion at the time.
Other crypto leaders are looking at IPOs in 2026
Meanwhile, one of Anchorage’s crypto custody competitors, BitGo, filed S‑1 IPO paperwork to list on the New York Stock Exchange in September, while crypto trading platform Kraken filed an S-1 in November and is eyeing a public listing in early 2026.
Magazine: One metric shows crypto is now in a bear market: Carl ‘The Moo
Cointelegraph is committed to independent, transparent journalism. This news article is produced in accordance with Cointelegraph’s Editorial Policy and aims to provide accurate and timely information. Readers are encouraged to verify information independently. Read our Editorial Policy https://cointelegraph.com/editorial-policy
Ethereum activated the Fusaka upgrade on Dec. 3, 2025, raising the network’s data availability capacity through Blob Parameter Overrides that incrementally expanded blob targets and maximums.
Two subsequent adjustments raised the target from 6 blobs per block to 10, then to 14, with a maximum ceiling of 21. The goal was to reduce layer-2 rollup costs by increasing throughput for blob data, the compressed transaction bundles that rollups post to Ethereum for security and finality.
Three months into data collection, the results reveal a gap between capacity and utilization. A MigaLabs analysis of over 750,000 slots since Fusaka’s activation shows that the network isn’t reaching the target blob count of 14.
Median blob usage actually declined after the first parameter adjustment, and blocks containing 16 or more blobs exhibit elevated miss rates, suggesting reliability degradation at the edges of new capacity.
The report’s conclusion is direct: no further increases in the blob parameter until high-blob miss rates normalize and demand materializes for the headroom already created.
What Fusaka changed and when it happened
Ethereum’s pre-Fusaka baseline, established through EIP-7691, set the target at 6 blobs per block with a maximum of 9. The Fusaka upgrade introduced two sequential Blob Parameter Override adjustments.
The first was activated Dec. 9, raising the target to 10 and the maximum to 15. The second was activated Jan. 7, 2026, pushing the target to 14 and the maximum to 21.
These changes didn’t require hard forks, and the mechanism allows Ethereum to dial capacity through client coordination rather than protocol-level upgrades.
The MigaLabs analysis, which published reproducible code and methodology, tracked blob usage and network performance across this transition.
It found that the median blob count per block fell from 6 before the first override to 4 afterward, despite the network’s capacity expanding. Blocks containing 16 or more blobs remain extremely rare, occurring between 165 and 259 times each across the observation window, depending on the specific blob count.
The network has headroom it isn’t using.
One parameter discrepancy: the report’s timeline text describes the first override as raising the target from 6 to 12, but the Ethereum Foundation’s mainnet announcement and client documentation describe the adjustment as 6 to 10.
We use the Ethereum Foundation’s parameters as source: 6/9 baseline, 10/15 after the first override, 14/21 after the second. Nevertheless, we treat the report’s dataset for observed utilization and miss-rate patterns as the empirical backbone.
Miss rates climb at high blob counts
Network reliability measured through missed slots, which are blocks that fail to propagate or attest correctly, shows a clear pattern.
At lower blob counts, the baseline miss rate sits around 0.5%. Once blocks reach 16 or more blobs, miss rates climb to 0.77% to 1.79%. At 21 blobs, the maximum capacity introduced in the second override, the miss rate hits 1.79%, more than triple the baseline.
The analysis breaks this down across blob counts from 10 to 21, showing a gradual degradation curve that accelerates past the 14-blob target.
This degradation matters because it suggests the network’s infrastructure, such as validator hardware, network bandwidth, and attestation timing, struggles to handle blocks at the upper end of capacity.
If demand eventually rises to fill the 14-blob target or push toward the 21-blob maximum, the elevated miss rates could translate into meaningful finality delays or reorg risk. The report frames this as a stability boundary: the network can technically process high-blob blocks, but doing so consistently and reliably remains an open question.
Blob economics: why the reserve price floor matters
Fusaka didn’t only expand capacity. It also changed blob pricing through EIP-7918, which introduces a reserve price floor to prevent blob auctions from collapsing to 1 wei.
Before this change, when execution costs dominated and blob demand stayed low, the blob base fee could spiral downward until it effectively disappeared as a price signal. Layer-2 rollups pay blob fees to post their transaction data to Ethereum, and those fees are supposed to reflect the computational and network costs that blobs impose.
When fees fall to near zero, the economic feedback loop breaks, and rollups consume capacity without paying in proportion. This results in the network losing visibility into actual demand.
EIP-7918’s reserve price floor ties blob fees to execution costs, ensuring that even when demand is soft, the price remains a meaningful signal.
This prevents the free-rider problem where cheap blobs encourage wasteful usage and provides clearer data for future capacity decisions: if blob fees stay elevated despite increased capacity, demand is genuine; if they collapse to the floor, headroom exists.
Early data from Hildobby’s Dune dashboard, tracking Ethereum blobs, shows that blob fees have stabilized after Fusaka rather than continuing the downward spiral seen in earlier periods.
The average blob count per block confirms MigaLabs’ finding that utilization hasn’t surged to fill the new capacity. Blocks routinely carry fewer than the 14-blob target, and the distribution remains heavily skewed toward lower counts.
What the data reveals about effectiveness
Fusaka succeeded in expanding technical capacity and proving the Blob Parameter Override mechanism works without requiring contentious hard forks.
The reserve price floor appears to be functioning as intended, preventing blob fees from becoming economically meaningless. But utilization lags behind capacity, and reliability at the edges of new capacity shows measurable degradation.
The miss rate curve suggests Ethereum’s current infrastructure comfortably handles the pre-Fusaka baseline and the first override’s 10/15 parameters, but begins to strain past 16 blobs.
This creates a risk profile: if layer-2 activity surges and pushes blocks toward the 21-blob maximum regularly, the network could face elevated miss rates that compromise finality and reorg resistance.
Demand patterns offer another signal. Median blob usage falling after the first override, despite increased capacity, suggests that layer-2 rollups aren’t currently constrained by blob availability.
Either their transaction volumes haven’t grown enough to require more blobs per block, or they’re optimizing compression and batching to fit within existing capacity rather than expanding usage.
Blobscan, a dedicated blob explorer, shows individual rollups posting relatively consistent blob counts over time rather than ramping up to exploit new headroom.
The pre-Fusaka concern was that limited blob capacity would bottleneck Layer 2 scaling and keep rollup fees elevated as networks competed for scarce data availability. Fusaka addressed the capacity constraint, but the bottleneck appears to have shifted.
Rollups aren’t filling the available space, which means either demand hasn’t arrived yet or other factors, such as sequencer economics, user activity, and cross-rollup fragmentation, are limiting growth more than blob availability was.
What comes next
Ethereum’s roadmap includes PeerDAS, a more fundamental redesign of data availability sampling that would further expand blob capacity while improving decentralization and security properties.
However, the Fusaka results suggest that raw capacity isn’t the binding constraint right now.
The network has room to grow into the 14/21 parameters before needing another expansion, and the reliability curve at high blob counts indicates that infrastructure upgrades may need to catch up before capacity increases again.
The miss rate data provides a clear boundary condition. If Ethereum pushes capacity higher while 16+ blob blocks still show elevated miss rates, it risks introducing systemic instability that could surface during high-demand periods.
The safer path is to let utilization rise toward the current target, monitor whether miss rates improve as clients optimize for higher blob loads, and adjust parameters only once the network demonstrates it can reliably handle edge cases.
Fusaka’s effectiveness depends on the metric. It expanded capacity successfully and stabilized blob pricing through the reserve floor. It didn’t drive immediate utilization increases or solve the reliability challenges at maximum capacity.
The upgrade created headroom for future growth, but whether that growth materializes remains an open question the data hasn’t answered yet.
Mentioned in this article
The Bitcoin price surged through the $96,000 level this afternoon, pushing decisively above a key resistance zone and signaling a renewed wave of bullish momentum after weeks of choppy, range-bound trading.
At the time of writing, the bitcoin price is trading around $96,000 up roughly 4.4% over the past 24 hours, according to market data.
The breakout marks a clear move beyond the upper boundary of January’s consolidation range. Bitcoin price is now hovering near its weekly highs, sitting approximately 5% above its seven-day low near $91,700, as buyers regain control of short-term market structure.
All this is happening as the US Senate Agriculture Committee has delayed its key markup of the Digital Asset Market Structure CLARITY Act until late January. The Senate’s Banking Committee markup is still scheduled for January 15.
Senate Agriculture Committee Chairman John Boozman announced a timeline for advancing crypto market structure legislation, with legislative text set for release by the close of business on Wednesday, January 21, and a committee markup scheduled for Tuesday, January 27, at 3 p.m.
Boozman said the schedule is designed to ensure transparency and thorough review while providing regulatory clarity for crypto markets and supporting consumer protection and U.S. innovation.
The delay signals that Senate leaders may lack the votes to advance the bill amid disagreements over stablecoin rewards, DeFi oversight, and SEC–CFTC authority.
Although the House passed its version in mid-2025, the bill cannot move forward unless both Senate committees approve it.
Despite this, Bitcoin trading activity is rallying alongside the price rally, with 24-hour volume climbing to roughly $55 billion, reflecting renewed participation as price accelerated higher.
Bitcoin’s total market capitalization has risen to approximately $1.92 trillion, reinforcing its dominance within the digital asset market. Circulating supply currently stands at just under 19.98 million BTC, inching closer to the protocol’s fixed 21 million coin cap.
Strategy ($MSTR) stock soars
Shares of Strategy (MSTR) jumped sharply today as well, closing at $172.99 USD with a 6.63% gain today and extending strength in after-hours trading up to $177.00, up +2 after hours, as investors continue to price in the company’s high-risk, bitcoin-linked strategy.
On January 12, Strategy announced they added 13,627 bitcoin for $1.25 billion, lifting its total holdings to 687,410 BTC.
The purchases were made between January 5 and January 11 and funded through the company’s at-the-market offering program, which included sales of Class A common stock (MSTR) and its 10.00% Series A perpetual preferred stock, Stretch (STRC).
Bitcoin price outlook
Tuesday’s surge follows several failed breakout attempts over the last couple of months, when bitcoin repeatedly tested resistance near the mid-$94,000 range before pulling back.
For much of the past month, price action remained compressed between roughly $85,000 and $94,000, prompting analysts to warn that bulls needed a decisive move higher to reassert control. That move now appears to be underway.
If the bitcoin price can sustain acceptance above $96,000, the next major resistance zones sit between $98,000 and $104,000, levels that previously capped upside momentum. A failure to hold current levels, however, could see price retrace toward former resistance turned potential support.
The breakout arrives as investors continue to weigh inflation trends, interest-rate expectations, and escalating political uncertainty tied to U.S. monetary policy.
On the political side, the Department of Justice has opened a criminal investigation into Federal Reserve Chair Jerome Powell. The investigation is intensifying a months‑long feud between the White House and the U.S. central bank
According to Powell, the DOJ served the Federal Reserve with grand jury subpoenas and threatened a criminal indictment tied to his June 2025 testimony about a $2.5 billion plus renovation of Fed office buildings.
In recent months, the bitcoin price has increasingly traded in response to macro narratives, with many participants viewing it as a hedge against policy instability and long-term currency debasement.
At the time of publication, the bitcoin price is near $96,000.
Felix Pinkston
Jan 12, 2026 10:17
AAVE price prediction shows potential upside to $190 by month-end despite current $164.45 trading level, with technical analysis revealing mixed signals and analyst targets up to $195.
Aave (AAVE) is currently trading at $164.45, down 1.21% in the past 24 hours, as the DeFi lending protocol navigates mixed technical signals. Despite the recent decline, analyst predictions suggest significant upside potential for the remainder of January 2026.
AAVE Price Prediction Summary
• Short-term target (1 week): $175-$180
• Medium-term forecast (1 month): $185-$195 range
• Bullish breakout level: $174.38
• Critical support: $159.08
What Crypto Analysts Are Saying About Aave
Recent analyst coverage presents an optimistic AAVE price prediction outlook for the coming weeks. Rebeca Moen provided bullish commentary on January 3, 2026, stating that “AAVE price prediction shows bullish reversal potential with targets at $185-195 over next 3-4 weeks, supported by oversold RSI recovery and positive MACD momentum.”
Building on this sentiment, Luisa Crawford offered an updated Aave forecast on January 6, 2026, noting that “AAVE price prediction points to $190 upside target by month-end as bullish MACD histogram and RSI recovery from oversold levels signal potential breakout from current $174 level.”
These analyst projections align with technical patterns suggesting AAVE could see substantial gains if it can break above key resistance levels.
AAVE Technical Analysis Breakdown
The current technical picture for AAVE presents a mixed but potentially constructive setup. The RSI reading of 48.24 places AAVE in neutral territory, indicating neither overbought nor oversold conditions. This neutral positioning could provide room for upward movement without immediate technical constraints.
However, the MACD histogram reading of -0.0000 suggests bearish momentum remains present, though the minimal negative value indicates this bearish pressure may be weakening. The MACD line at -1.5169 matches the signal line, suggesting a potential momentum shift could be approaching.
AAVE’s position within the Bollinger Bands shows promise, with the current price at 64% of the distance between the lower and upper bands. This positioning above the middle band (SMA 20 at $159.59) indicates bullish bias, while still providing room to move toward the upper band at $177.01.
The key resistance level sits at $174.38, representing a critical breakout point for bulls. Immediate resistance at $169.41 must first be cleared. On the downside, immediate support at $161.76 should hold, with stronger support at $159.08 aligning closely with the 20-period SMA.
Aave Price Targets: Bull vs Bear Case
Bullish Scenario
In the bullish case, AAVE price prediction models suggest targets between $185-$195 are achievable by month-end. The path higher would likely begin with a break above the immediate resistance at $169.41, followed by a decisive move through the strong resistance at $174.38.
Technical confirmation for the bullish scenario would require the RSI to move above 60, indicating strengthening momentum, and the MACD histogram to turn positive. A close above the upper Bollinger Band at $177.01 would signal strong bullish momentum and open the door to the analyst targets.
The 24-hour trading volume of $9.27 million provides adequate liquidity for such moves, though increased volume would be needed to sustain breakout momentum.
Bearish Scenario
The bearish case for this Aave forecast would see AAVE failing to hold current support levels. A break below the immediate support at $161.76 could trigger further selling toward the strong support at $159.08.
A decisive break below the 20-period SMA at $159.59 would shift the short-term bias negative and could target the lower Bollinger Band at $142.17. The current MACD reading already shows bearish momentum, and further deterioration could accelerate downside moves.
Risk factors include broader crypto market weakness, DeFi sector rotation, and failure to maintain key technical levels.
Should You Buy AAVE? Entry Strategy
For investors considering AAVE positions, the current technical setup offers several entry opportunities. Conservative buyers might wait for a pullback to the $161.76 support level, providing a better risk-reward ratio for targeting the $185-$195 analyst projections.
More aggressive traders could enter on a confirmed break above $169.41 with a stop-loss below $159.08. This strategy aligns with the bullish AAVE price prediction while managing downside risk.
Position sizing should account for the daily Average True Range of $8.33, indicating significant intraday volatility. Risk management remains crucial given the mixed technical signals.
Conclusion
The AAVE price prediction for January 2026 remains constructive despite current neutral momentum. Analyst targets of $185-$195 appear achievable if AAVE can break through key resistance levels and confirm the bullish reversal patterns identified in recent technical analysis.
While the current $164.45 price level presents mixed signals, the combination of neutral RSI positioning, potential MACD momentum shift, and favorable Bollinger Band placement supports a cautiously optimistic Aave forecast. Traders should monitor the key $174.38 resistance level for confirmation of the bullish scenario.
Disclaimer: This AAVE price prediction is for educational purposes only and should not be considered financial advice. Cryptocurrency investments carry significant risk, and past performance does not guarantee future results.
Image source: Shutterstock
Artificial intelligence is a formidable force that drives the modern technological landscape without being limited to research labs. You can find multiple use cases of AI across industries albeit with a limitation. The rising use of artificial intelligence has called for attention to AI security risks that create setbacks for AI adoption. Sophisticated AI systems can yield biased results or end up as threats to security and privacy of users. Understanding the most prominent security risks for artificial intelligence and techniques to mitigate them will provide safer approaches to embrace AI applications.
Unraveling the Significance of AI Security
Did you know that AI security is a separate discipline that has been gaining traction among companies adopting artificial intelligence? AI security involves safeguarding AI systems from risks that could directly affect their behavior and expose sensitive data. Artificial intelligence models learn from data and feedback they receive and evolve accordingly, which makes them more dynamic.
The dynamic nature of artificial intelligence is one of the reasons for which security risks of AI can emerge from anywhere. You may never know how manipulated inputs or poisoned data will affect the internal working of AI models. Vulnerabilities in AI systems can emerge at any point in the lifecycle of AI systems from development to real-world applications.
The growing adoption of artificial intelligence calls for attention to AI security as one of the focal points in discussions around cybersecurity. Comprehensive awareness of potential risks to AI security and proactive risk management strategies can help you keep AI systems safe.
Want to understand the importance of ethics in AI, ethical frameworks, principles, and challenges? Enroll now in the Ethics Of Artificial Intelligence (AI) Course!
Identifying the Common AI Security Risks and Their Solution
Artificial intelligence systems can always come up with new ways in which things could go wrong. The problem of AI cyber security risks emerges from the fact that AI systems not only run code but also learn from data and feedback. It creates the perfect recipe for attacks that directly target the training, behavior and output of AI models. An overview of the common security risks for artificial intelligence will help you understand the strategies required to fight them.
Many people believe that AI models understand data exactly like humans. On the contrary, the learning process of artificial intelligence models is significantly different and can be a huge vulnerability. Attackers can feed crafted inputs to AI models and force it to make incorrect or irrelevant decisions. These types of attacks, known as adversarial attacks, directly affect how an AI model thinks. Attackers can use adversarial attacks to slip past security safeguards and corrupt the integrity of artificial intelligence systems.
The ideal approaches for resolving such security risks involve exposing a model to different types of perturbation techniques during training. In addition, you must also use ensemble architectures that help in reducing the chances of a single weakness inflicting catastrophic damage. Red-team stress tests that simulate real-world adversarial tricks should be mandatory before releasing the model to production.
Artificial intelligence models can unintentionally expose sensitive records in their training data. The search for answers to “What are the security risks of AI?” reveals that exposure of training data can affect the output of models. For example, customer support chatbots can expose the email threads of real customers. As a result, companies can end up with regulatory fines, privacy lawsuits, and loss of user trust.
The risk of exposing sensitive training data can be managed with a layered approach rather than relying on specific solutions. You can avoid training data leakage by infusing differential privacy in the training pipeline to safeguard individual records. It is also important to exchange real data with high-fidelity synthetic datasets and strip out any personally identifiable information. The other promising solutions for training data leakage include setting up continuous monitoring for leakage patterns and deploying guardrails to block leakage.
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Poisoned AI Models and Data
The impact of security risks in artificial intelligence is also evident in how manipulated training data can affect the integrity of AI models. Businesses that follow AI security best practices comply with essential guidelines to ensure safety from such attacks. Without safeguards against data and model poisoning, businesses may end up with bigger losses like incorrect decisions, data breaches, and operational failures. For example, the training data used for an AI-powered spam filter can be compromised, thereby leading to classification of legitimate emails as spam.
You must adopt a multi-layered strategy to combat such attacks on artificial intelligence security. One of the most effective methods to deal with data and model poisoning is validation of data sources through cryptographic signing. Behavioral AI detection can help in flagging anomalies in the behavior of AI models and you can support it with automated anomaly detection systems. Businesses can also deploy continuous model drift monitoring to track changes in performance emerging from poisoned data.
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Synthetic Media and Deepfakes
Have you come across news headlines where deepfakes and AI-generated videos were used to commit fraud? The examples of such incidents create negative sentiment around artificial intelligence and can deteriorate trust in AI solutions. Attackers can impersonate executives and provide approval for wire transfers through bypassing approval workflows.
You can implement an AI security system to fight against such security risks with verification protocols for validating identity through different channels. The solutions for identity validation may include multi-factor authentication in approval workflows and face-to-face video challenges. Security systems for synthetic media can also implement correlation of voice request anomalies with end user behavior to automatically isolate hosts after detecting threats.
One of the most critical threats to AI security that goes unnoticed is the possibility of biased training data. The impact of biases in training data can go to an extent where AI-powered security models cannot anticipate threats directly. For example, fraud-detection systems trained for domestic transactions could miss the anomalous patterns evident in international transactions. On the other hand, AI models with biased training data may flag benign activities repeatedly while ignoring malicious behaviors.
The proven and tested solution to such AI security risks involves comprehensive data audits. You have to run periodic data assessments and evaluate the fairness of AI models to compare their precision and recall across different environments. It is also important to incorporate human oversight in data audits and test model performance in all areas before deploying the model to production.
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Final Thoughts
The distinct security challenges for artificial intelligence systems create significant troubles for broader adoption of AI systems. Businesses that embrace artificial intelligence must be prepared for the security risks of AI and implement relevant mitigation strategies. Awareness of the most common security risks helps in safeguarding AI systems from imminent damage and protecting them from emerging threats. Learn more about artificial intelligence security and how it can help businesses right now.
The Zcash protocol remains unaffected despite the governance clash and restructuring with Bootstrap.
The reiteration of the payment company‘s plans not to pursue a public offering followed a $500 million fundraise in November, leading to a $40 billion valuation for Ripple.
Ripple Labs president Monica Long has ruled out an IPO for the company, saying it was in a “really healthy position” without going public.
In a Tuesday interview with Bloomberg, Long addressed rumors that Ripple was planning to go public after the company reached a $40 billion valuation in November. The Ripple president said the company was focused on growth following the $500 million fundraise headed by Citadel Securities and Fortress Investment Group that led to its valuation.
“Currently, we still plan to remain private,” said Long, expanding on her comments in November after the fundraise. “Often the strategy driving an IPO is to get the access to the investors and the liquidity of the public markets […] We’re in a really healthy position to continue to fund and invest in our company’s growth without going public.”
The comments from Long going into 2026 came months after the US Securities and Exchange Commission announced it would wind down its enforcement actions against Ripple, fueling speculation about an IPO. Long has repeatedly denied reports that Ripple was pursuing a public offering.
Related: SEC now fully Republican, set for pro-crypto rulemaking in 2026
At the time of writing, the price of XRP (XRP) was $2.20, having dropped by about 6% in the previous 24 hours. The token is the fourth largest cryptocurrency by market capitalization.
OCC grants US bank trust approval for Ripple and others
In December, the US Office of the Comptroller of the Currency (OCC) conditionally approved applications from Circle and Ripple for national trust bank charters. BitGo, Fidelity Digital Assets and Paxos also received conditional approval to convert their existing state-level trust companies into federally chartered national trust banks.
Ripple’s application said its charter would “not be a stablecoin issuer” for its US dollar-pegged coin, Ripple USD (RLUSD), while the other companies will provide a variety of digital asset custody services to users. Of the applicants, BitGo has announced plans to go public, and Circle launched an IPO in May.
Magazine: How crypto laws changed in 2025 — and how they’ll change in 2026
After a year of steady decline, the “memecoin dominance” ratio, a key metric tracking the sector’s share of the total altcoin market, has abruptly reversed course from historic lows.
This came as the total capitalization of meme assets reclaimed the $50 billion mark and tokens such as PEPE, BONK, and FLOKI posted outsized double-digit gains to start the year.
The surge is forcing institutional managers and retail traders alike to confront a critical question: Is this a fleeting spasm of post-holiday speculation, or the early bellwether for a broader market rotation?
Data from market intelligence firm CryptoQuant highlights the severity of the shift. Following the “memecoin mania” that peaked in November 2024, the sector’s dominance within the altcoin market began a long slide.
At its height, meme tokens accounted for 11% of the total altcoin market capitalization, a ratio of 0.11. By December 2025, that figure had collapsed to just 3.2% (0.032), a historical floor.
However, analysts note that the last time the ratio touched these levels, it preceded a massive expansion in speculative liquidity that eventually dragged the broader altcoin complex higher.
Speculative investors are now viewing the current bounce from that bottom as a potential leading indicator.
If the trend sustains, it suggests that the market’s appetite for risk is returning faster than anticipated, potentially setting the stage for a new altcoin season that could influence blockchain activity and listing standards throughout 2026.
A signal from the noise
According to data from analytics platform Santiment, the collective market capitalization of meme coins jumped more than 20.8% in the first week of the year, pushing the sector’s total value above $45.3 billion.
CoinGecko data puts the figure even higher, estimating the total value of the “joke economy,” spanning dog and frog themes and political satire, at roughly $51.6 billion.
The rally has been led by familiar names that dominated previous cycles. In the past seven days alone, PEPE and the self-deprecatingly named USELESS token have each surged 54%. MOG climbed 38%, while the Solana-based heavyweight BONK added 34%.
Even legacy assets like Dogecoin and Shiba Inu have joined the fray, with Shiba Inu jumping 13% on Sunday amid renewed trading frenzy.
Santiment analysts attributed the timing of the bounce to a classic contrarian signal. The rally began shortly after Christmas, precisely when “FUD” (fear, uncertainty, and doubt) about speculative assets reached its peak among retail traders.
As sentiment hit rock bottom and casual traders wrote off the sector, smart money appeared to step in, capitalizing on the capitulation to accumulate positions at discounted valuations.
For fund managers who spent 2025 shifting allocations toward “quality”, the resurgence of the meme sector presents a dilemma.
The move tests how far the industry is willing to lean back into leverage. Ignoring the rally risks missing the first leg of a risk-on phase, while chasing it requires re-entering the most volatile assets in the digital ecosystem.
The ETF multiplier
Unlike previous meme cycles driven almost entirely by offshore exchanges and decentralized swaps, the 2026 rebound has a regulated dimension.
The approval and launch of complex crypto exchange-traded funds (ETFs) in the US have created new transmission channels for speculative mania to reach traditional brokerage accounts.
Bloomberg Intelligence ETF analyst Eric Balchunas noted that some of the best-performing products to start the year were leveraged memecoin ETFs.
Specifically, the 21Shares 2x Long Dogecoin ETF (TXXD) has logged standout performance, indicating that demand for meme exposure is not limited to crypto-native “degens” using on-chain wallets.
This institutionalization of the “joke economy” changes the stakes for the broader market. When billions of dollars flow into meme-themed assets, the impact ripples outward.
It influences listing decisions at major centralized exchanges, which rely on trading fees from high-volume tokens to subsidize other operations. It also exerts pressure on asset managers to broaden their product pipelines.
If a $50 billion asset class begins to set the cycle’s tempo, the industry’s infrastructure is forced to adapt to the liquidity demands of assets once dismissed as ephemeral gags.
Meanwhile, the sector is also diversifying internally. CoinGecko data breaks down the $51.6 billion meme economy into distinct sub-sectors, revealing a complex hierarchy.
“The Boy’s Club” (Matt Furie-inspired characters like PEPE) and “Frog-Themed” tokens now command 10.9% and 10.7% of the meme market, respectively, challenging the historical dominance of “Dog-Themed” coins, which sit at roughly 6.1%.
Newer categories like “PolitiFi” (political finance tokens) and “AI Memes” have carved out multi-billion dollar niches, suggesting the sector is evolving its own internal rotation dynamics.
Top AI Agents Crypto Assets by Market Cap
Infrastructure wars reignite
The resurgence of memecoins is also acting as a stress test and a growth driver for the underlying blockchain networks, particularly Solana and Coinbase’s layer-2 network, Base.
On Solana, the “memecoin launchpad” ecosystem has hit a three-month high in activity. Metrics for daily volume, tokens launched, and “daily token graduations,” coins that gain enough traction to move from launchpads to decentralized exchanges, are all spiking.
This activity revives the “fee war” narrative, where competing chains battle to become the preferred venue for high-frequency speculative trading.
Last year, platforms like Pump.fun and LetsBonk drove massive revenue for the Solana network; the early 2026 data suggests this trend is re-accelerating.
This dynamic has drawn commentary from industry leaders who view the phenomenon as more than just gambling.
Jesse Pollak, lead developer for Coinbase’s Base network, argued that these assets serve a functional purpose in the crypto economy. Pollak described memes as “coordination points for community” that bring people together and create a context for collective creation.
“We need more memecoins because we need more creativity, community, and collective action,” Pollak said, framing the assets as a top-of-funnel mechanism that onboards users who eventually migrate to other on-chain applications.
For the blockchain networks themselves, the stakes are tangible. A sustained meme rally drives demand for the network’s native token (used to pay gas fees), tests network throughput, and attracts liquidity providers.
The centralization paradox
Despite the narratives of community and decentralized fun, available data reveal significant risks regarding concentration.
While the price action suggests a broad-based frenzy, ownership of the top assets remains heavily centralized.
Santiment data on Shiba Inu, one of the sector’s stalwarts, shows that the 10 largest wallets control nearly 63% of the total supply. The single largest wallet holds approximately 41% of the supply, a position currently valued at roughly $3.3 billion.
This level of concentration is not unique to Shiba Inu, as many high-flying tokens in the “Solana Meme” and “Frog-Themed” categories exhibit similar distributions.
This creates a perilous environment for late-arriving retail investors. With liquidity concentrated in the hands of a few “whales,” the risk of a coordinated sell-off remains high.
CryptoQuant analysts cautioned that while the setup mirrors previous pre-bull run signals, “it is still very early to say for sure” if the trend will hold.
For speculative investors, the current moment represents a high-risk, high-reward signal. The bounce from historical lows in dominance suggests the market is waking up, but the market’s structure, which is heavily concentrated and driven by leverage, remains fragile.
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Fedi will release its full software stack as open source on Jan. 3, completing a pledge made at launch in 2024.
The company said all Fedi software has now transitioned to the Affero General Public License (AGPL), following an interim period under a business source license.
The change makes Fedi’s codebase publicly available under a copyleft license that requires derivative works to remain open, according to a spokesperson from Fedi.
The date carries weight in Bitcoin history. Jan. 3 marks the anniversary of the Bitcoin genesis block, mined in 2009. Fedi said the timing reflects its focus on community ownership and grassroots financial infrastructure.
When Fedi launched, it said it aimed to become a “freedom technology” by giving control back to users and communities. The move to open source fulfills that commitment, the company said, and removes the risk of vendor lock-in for groups that rely on the software.
Fedi is used by communities to build local financial and social systems. Its app combines encrypted messaging, bitcoin payments, and additional services through Mini App extensions. Wallet infrastructure is powered by the Fedimint protocol, which allows groups to operate shared bitcoin custody using federated trust models.
The AGPL license is designed to ensure that improvements remain public, even when the software is used in hosted or networked services. Supporters say this aligns development incentives with user interests.
Fedi executives have highlighted the licensing shift in recent public appearances, including a BitcoinMENA pre-show segment featuring CEO Obi Nwosu.
With the transition complete, Fedi joins a growing group of Bitcoin-native projects returning to fully open development as adoption spreads beyond early adopters and into community-scale use cases.
Fedi: From Chaumian e-cash to federated bitcoin mints
Fedimint is built on ideas first proposed by cryptographer David Chaum in the early 1980s. Chaumian e-cash allows users to transact without revealing identity or transaction history to the issuer. Earlier versions of digital cash failed to gain adoption due to centralization, since a single mint controlled issuance and redemption. That structure created trust and censorship risks.
Bitcoin solved the double-spend problem by decentralizing transaction validation across a global network of nodes. It removed the need for a trusted mint but introduced tradeoffs. Transactions are public, and throughput remains limited.
Fedimint attempts to bridge those models. It uses Bitcoin as the reserve asset while distributing custody across a federation of independent operators, known as guardians. No single party controls funds or transaction data. This structure reduces censorship risk while preserving user privacy.
Fedi’s goal is to let communities deploy shared financial infrastructure without reliance on banks or centralized platforms.
