The United States Treasury has sanctioned two cryptocurrency exchanges linked to Iran’s financial system, marking the first time Washington has directly targeted digital asset platforms as part of its Iran sanctions program.
In a statement on Friday, the Treasury Department’s Office of Foreign Assets Control (OFAC) said the sanctions are part of a wider move against Iranian officials and networks accused of violently suppressing people at home while using alternative financial channels to get around international sanctions.
Among those sanctioned was Eskandar Momeni Kalagari, Iran’s minister of the interior, who oversees the country’s Law Enforcement Forces. “Treasury will continue to target Iranian networks and corrupt elites that enrich themselves at the expense of the Iranian people,” Treasury Secretary Scott Bessent said.
OFAC also designated Babak Morteza Zanjani, a well-known Iranian businessman previously convicted of embezzling billions of dollars in oil revenue from Iran’s national oil company. According to the Treasury, Zanjani was released from prison and later used by the Iranian state to help move and launder funds, providing financial support to projects tied to the Islamic Revolutionary Guard Corps (IRGC).
The sanctions break new ground by extending to two UK-registered crypto exchanges, Zedcex Exchange Ltd. and Zedxion Exchange Ltd., which US officials say are linked to Zanjani and have processed large volumes of transactions connected to IRGC-linked entities. OFAC said Zedcex alone has handled more than $94 billion in transactions since its registration in 2022.
“This marks OFAC’s first designation of a digital asset exchange for operating in the financial sector of the Iranian economy,” the Treasury said.
Bessent accused Tehran of diverting oil revenues toward weapons programs and militant proxies instead of supporting its population. He said the United States would continue to target networks that exploit digital assets to bypass restrictions and finance illicit activity.
Beyond the crypto-related designations, OFAC also sanctioned senior IRGC commanders and security officials across multiple provinces, citing evidence of live-fire attacks on protesters, forced burials without funerals and widespread intimidation aimed at crushing dissent.
Iran’s central bank used $500 million in USDt to support rial
Last week, blockchain analytics firm Elliptic said Iran’s central bank accumulated more than $500 million worth of Tether’s USDt (USDT) during a period of severe economic stress, likely using the stablecoin to support the collapsing rial or settle international trade.
The accumulation began as the currency lost roughly half its value in eight months, with Elliptic suggesting the bank used USDT on local exchange Nobitex to buy rials, mirroring traditional central bank market operations through crypto.
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Bitcoin’s break below $84,000 tilts the advantage in favor of the bears, opening the doors for a potential fall to $74,508.
Several major altcoins have slipped below their support levels, signaling that the bears are attempting to take charge.
Bitcoin (BTC) remains under pressure as sellers attempt to sustain the price below the $84,000 level. BTC’s fall near $81,000 caused $1.77 billion in liquidations in the past 24 hours, per CoinGlass data.
Several analysts have turned bearish and expect BTC’s downtrend to continue. They anticipate BTC to fall below the crucial $74,500 low, made in April 2025, following US President Donald Trump’s “Liberation Day” tariff announcement.
Crypto market data daily view. Source: TradingView
However, not everyone is bearish on BTC. Swyftx lead analyst Pav Hundal told Cointelegraph that BTC may form a bottom over the next 40 days if history repeats, as BTC bottoms “have historically lagged gold’s relative strength by about 14 months.”
Could BTC and the major altcoins start a relief rally? Let’s analyze the charts of the top 10 cryptocurrencies to find out.
Bitcoin price prediction
BTC turned down sharply from the 20-day exponential moving average (EMA) ($89,165) on Thursday and fell below the $84,000 support.
The $80,600 level is the crucial support to watch out for in the near term. If bears pull the Bitcoin price below $80,600, the BTC/USDT pair may extend the decline to the critical support at $74,508.
Buyers are likely to have other plans. They will attempt to defend the $80,600 level and push the price above the moving averages. If they do that, it shows that the market has rejected the dip below $84,000. The pair may then surge to the $94,789 to $97,924 resistance zone.
Ether price prediction
Ether (ETH) turned down from the moving averages on Thursday and fell below the $2,787 level, indicating selling on minor rallies.
The downsloping 20-day EMA ($2,999) and the relative strength index (RSI) in negative territory indicate an advantage to sellers. The Ether price may slump to the $2,623 level, which is likely to attract buyers. However, if the bears prevail, the ETH/USDT pair is likely to resume the downtrend toward $2,111.
Time is running out for the bulls. They will have to swiftly push the ETH/USDT pair above the moving averages to signal strength. The pair may then climb to the resistance line.
BNB price prediction
The failure of the bulls to maintain BNB (BNB) above the 20-day EMA ($890) on Thursday triggered selling, which has pulled the price to the uptrend line.
The bulls are expected to vigorously defend the uptrend line, as a close below it may sink the BNB/USDT pair to the $790 level. A break and close below the $790 support risks starting the next leg of the downtrend to $730.
Contrarily, if the BNB price turns up from the uptrend line, it suggests that the bulls remain buyers on dips. The pair may then reach the $928 to $959 overhead resistance zone, where the bears are expected to step in.
XRP price prediction
XRP (XRP) turned down from the moving averages and fell below the $1.77 level, indicating that the bears remain in control.
The XRP/USDT pair is likely to descend to $1.61, which is a critical level to watch out for. If sellers yank the XRP price below the $1.61 support, the pair risks falling to the support line of the descending channel pattern.
Instead, if the price turns up from $1.61, it is expected to face selling at the moving averages. If buyers overcome the hurdle, the pair may reach the downtrend line. A close above the downtrend line suggests that the bulls are back in the driver’s seat.
Solana price prediction
Solana’s (SOL) range-bound action from $117 to $147 resolved to the downside on Thursday, signaling that the bears are attempting to take charge.
If the Solana price closes below $117, the SOL/USDT pair risks falling to the $95 support. Buyers are expected to mount a strong defense at the $95 level, as a break below it may sink the pair to $79.
The bulls will have to push the price back above the moving averages to suggest that the break below $117 may have been a bear trap. The pair may then ascend to the $147 resistance.
Dogecoin price prediction
Dogecoin (DOGE) closed below the $0.12 support on Thursday, signaling the resumption of the downtrend.
The bulls will attempt to push the Dogecoin price back above the breakdown level of $0.12 but are expected to face solid resistance from the bears. If the price turns down from the $0.12 level or the moving averages, it heightens the risk of a collapse to the Oct. 10, 2025, low of $0.10.
This negative view will be invalidated in the near term if the DOGE/USDT pair turns up and breaks above the moving averages. That suggests solid buying at lower levels, opening the gates for a potential rally to $0.16.
Cardano price prediction
Cardano (ADA) is witnessing a tough battle between the buyers and sellers at the $0.33 level.
If the Cardano price closes below the $0.33 support, the ADA/USDT pair may decline to the support line of the descending channel pattern. The bulls are expected to defend the support line, which is close to the Oct. 10, 2025, low of $0.27.
Contrary to this assumption, if the price turns up from the current level and breaks above the downtrend line, it signals that the bulls are active at lower levels. That opens the doors for a rally to the breakdown level of $0.50.
The bulls will attempt to push the Bitcoin Cash price back above the $563 level but are expected to face solid resistance from the bears. If the price turns down from $563, it suggests that the bears have flipped the level into resistance. That increases the likelihood of a drop to $518 and thereafter to the pattern target of $456.
This bearish view will be negated in the short term if buyers drive the price above the $604 resistance. The BCH/USDT pair may then jump to $631 and subsequently to $670.
Hyperliquid price prediction
Hyperliquid (HYPE) turned down from the breakdown level of $35.50 on Thursday, indicating that the bears are fiercely defending the level.
The 20-day EMA ($26.36) is the critical support to watch out for on the downside. If the price turns up from the 20-day EMA, the bulls will again attempt to propel the HYPE/USDT pair above $35.50. If they succeed, the pair may rally to $44.
Conversely, if the Hyperliquid price breaks below the moving averages, the pair may consolidate from $35.50 to $20.82 for a while longer. The downtrend may resume on a break below $20.82.
Monero price prediction
The failure of the bulls to push Monero (XMR) above the 50-day simple moving average (SMA) ($482) shows that the bears are selling on every minor rise.
The bulls are attempting to defend the $417 support as seen from the long tail on the candlestick. The relief rally is expected to face selling at the moving averages. If the price turns down from the moving averages, the risk of a break below the $417 level increases. The XMR/USDT pair may then nosedive to $360.
Buyers have an uphill task ahead of them. They will have to drive the Monero price above the 20-day EMA ($501) to signal a comeback. The pair may then march toward $546, where the sellers are expected to step in.
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.
At its core, proof-of-reserves is a public demonstration that a custodian holds the assets it claims to hold on behalf of users, typically using cryptographic methods and onchain transparency.
The truth is that proof-of-reserves is not a trust guarantee. It shows whether verifiable assets exist on a platform at a single point in time, but it does not confirm that the platform is solvent, liquid or governed by controls that prevent hidden risk.
But even when executed properly, PoR is often a point-in-time snapshot that can miss what happened before and after the reporting moment.
Without a credible view of liabilities, PoR cannot prove solvency, which is what users actually need during periods of withdrawal stress.
Did you know? On Dec. 31, 2025, Binance’s CEO wrote that the platform’s user asset balances publicly verified through proof-of-reserves had reached $162.8 billion.
What PoR proves and how it is usually done
In practice, PoR involves two checks: assets and, ideally, liabilities.
On the asset side, an exchange shows that it controls certain wallets, usually by publishing addresses or signing messages.
Liabilities are trickier. Most exchanges take a snapshot of user balances and commit it to a Merkle tree, often a Merkle-sum tree. Users can then confirm that their balance is included using an inclusion proof, without everyone’s balances being made public.
When done properly, PoR shows whether onchain assets cover customer balances at a specific moment.
Did you know? Binance lets each user independently verify their inclusion in its PoR snapshot. Through its verification page, Binance generates a cryptographic proof based on a Merkle tree of user balances, allowing users to confirm that their account was counted without revealing anyone else’s data or balances.
How an exchange can “pass PoR” and still be risky
PoR can improve transparency, but it shouldn’t be relied on as the sole measure of a company’s financial health.
Of course, a report on assets without full liabilities does not demonstrate solvency. Even if onchain wallets appear strong, liabilities can be incomplete or selectively defined, missing items such as loans, derivatives exposure, legal claims or offchain payables. That can show funds exist without proving the business can meet all of its obligations.
Also, a single attestation does not reveal what the balance sheet looked like last week or what it looks like the day after the report. In theory, assets can be temporarily borrowed to improve the snapshot, then moved back out afterward.
Next, encumbrances often do not show up. PoR typically cannot tell you whether assets are pledged as collateral, lent out or otherwise tied up, meaning they may not be available when withdrawals spike.
Liquidity and valuation can also be misleading. Holding assets is not the same as being able to liquidate them quickly and at scale during periods of stress, especially if reserves are concentrated in thinly traded tokens. PoR does not address this issue; clearer risk and liquidity disclosures might.
PoR isn’t the same as an audit
A lot of the trust problem comes from a mismatch in expectations.
Many users treat PoR like a safety certificate. In reality, many PoR engagements resemble agreed-upon procedures (AUPs). In these cases, the practitioner performs specific checks and reports what was found without providing an audit-style opinion on the company’s overall health.
Indeed, an audit or even a review is designed to deliver an assurance conclusion within a formal framework. AUP reporting is narrower. It explains what was tested and what was observed, then leaves interpretation to the reader. Under International Standard on Related Services (ISRS) 4400, an AUP engagement is not an assurance engagement and does not express an opinion.
Regulators have highlighted this gap. The Public Company Accounting Oversight Board has warned that PoR reports are inherently limited and should not be treated as proof that an exchange has sufficient assets to meet its liabilities, especially given the lack of consistency in how PoR work is performed and described.
This is also why PoR drew increased scrutiny after 2022. Mazars paused work for crypto clients, citing concerns about how PoR-style reports were being presented and how the public might interpret them.
What’s a practical trust stack, then?
PoR can be a starting point, but real trust comes from pairing transparency with proof of solvency, strong governance and clear operational controls.
Start with solvency. The real step up is showing assets versus a complete set of liabilities, ensuring assets are greater than or equal to liabilities. Merkle-based liability proofs, along with newer zero-knowledge approaches, aim to close that gap without exposing individual balances.
Next, add assurance around how the exchange actually operates. A snapshot does not reveal whether the platform has disciplined controls such as key management, access permissions, change management, incident response, segregation of duties and custody workflows. This is why institutional due diligence often relies on System and Organization Controls (SOC)-style reporting and similar frameworks that measure controls over time, not just a balance at a single moment.
Make liquidity and encumbrance visible. Solvency on paper does not guarantee that an exchange can survive a run. Users need clarity on whether reserves are unencumbered and how quickly holdings can be converted into liquid assets at scale.
Anchor it in governance and disclosure. Credible oversight depends on clear custody frameworks, conflict management and consistent disclosures, especially for products that introduce additional obligations such as yield, margin and lending.
PoR helps, but it can’t replace accountability
PoR is better than nothing, but it remains a narrow, point-in-time check (even though it’s often marketed like a safety certificate).
On its own, PoR does not prove solvency, liquidity or control quality. So, before treating a PoR badge as “safe,” consider the following:
Are liabilities included, or is it assets only? Assets-only reporting cannot demonstrate solvency.
What is in scope? Are margin, yield products, loans or offchain obligations excluded?
Is it reporting a snapshot or ongoing? A single date can be dressed up. Consistency matters.
Are reserves unencumbered? “Held” is not the same as “available during stress.”
What kind of engagement is it? Many PoR reports are limited in scope and should not be read like an audit opinion.
Decentralized GPU networks are pitching themselves as a lower-cost layer for running AI workloads, while training the latest models remains concentrated inside hyperscale data centers.
Frontier AI training involves building the largest and most advanced systems, a process that requires thousands of GPUs to operate in tight synchronization.
That level of coordination makes decentralized networks impractical for top-end AI training, where internet latency and reliability cannot match the tightly coupled hardware in centralized data centers.
Most AI workloads in production do not resemble large-scale model training, opening space for decentralized networks to handle inference and everyday tasks.
“What we are beginning to see is that many open-source and other models are becoming compact enough and sufficiently optimized to run very efficiently on consumer GPUs,” Mitch Liu, co-founder and CEO of Theta Network, told Cointelegraph. “This is creating a shift toward open-source, more efficient models and more economical processing approaches.”
Training frontier AI models is highly GPU-intensive and remains concentrated in hyperscale data centers. Source: Derya Unutmaz
From frontier AI training to everyday inference
Frontier training is concentrated among a few hyperscale operators, as running large training jobs is expensive and complex. The latest AI hardware, like Nvidia’s Vera Rubin, is designed to optimize performance inside integrated data center environments.
“You can think of frontier AI model training like building a skyscraper,” Nökkvi Dan Ellidason, CEO of infrastructure company Ovia Systems (formerly Gaimin), told Cointelegraph. “In a centralized data center, all the workers are on the same scaffold, passing bricks by hand.”
That level of integration leaves little room for the loose coordination and variable latency typical of distributed networks.
“To build the same skyscraper [in a decentralized network], they have to mail each brick to one another over the open internet, which is highly inefficient,” Ellidason continued.
AI giants continue to absorb a growing share of global GPU supply. Source: Sam Altman
Meta trained its Llama 4 AI model using a cluster of more than 100,000 Nvidia H100 GPUs. OpenAI does not disclose the size of the GPU clusters used to train its models, but infrastructure lead Anuj Saharan said GPT-5 was launched with support from more than 200,000 GPUs, without specifying how much of that capacity was used for training versus inference or other workloads.
Inference refers to running trained models to generate responses for users and applications. Ellidason said the AI market has reached an “inference tipping point.” While training dominated GPU demand as recently as 2024, he estimated that as much as 70% of demand is driven by inference, agents and prediction workloads in 2026.
“This has turned compute from a research cost into a continuous, scaling utility cost,” Ellidason said. “Thus, the demand multiplier through internal loops makes decentralized computing a viable option in the hybrid compute conversation.”
Decentralized GPU networks are best suited to workloads that can be split, routed and executed independently, without requiring constant synchronization between machines.
“Inference is the volume business, and it scales with every deployed model and agent loop,” Evgeny Ponomarev, co-founder of decentralized computing platform Fluence, told Cointelegraph. “That is where cost, elasticity and geographic spread matter more than perfect interconnects.”
In practice, that makes decentralized and gaming-grade GPUs in consumer environments a better fit for production workloads that prioritize throughput and flexibility over tight coordination.
Low hourly prices for consumer GPUs illustrate why decentralized networks target inference rather than large-scale model training. Source: Salad.com
“Consumer GPUs, with lower VRAM and home internet connections, do not make sense for training or workloads that are highly sensitive to latency,” Bob Miles, CEO of Salad Technologies — an aggregator for idle consumer GPUs — told Cointelegraph.
“Today, they are more suited to AI drug discovery, text-to-image/video and large scale data processing pipelines — any workload that is cost sensitive, consumer GPUs excel on price performance.”
Decentralized GPU networks are also well-suited to tasks such as collecting, cleaning and preparing data for model training. Such tasks often require broad access to the open web and can be run in parallel without tight coordination.
This type of work is difficult to run efficiently inside hyperscale data centers without extensive proxy infrastructure, Miles said.
When serving users all around the world, a decentralized model can have a geographic advantage, as it can reduce the distances requests have to travel and multiple network hops before reaching a data center, which can increase latency.
“In a decentralized model, GPUs are distributed across many locations globally, often much closer to end users. As a result, the latency between the user and the GPU can be significantly lower compared to routing traffic to a centralized data center,” said Liu of Theta Network.
Theta Network is facing a lawsuit filed in Los Angeles in December 2025 by two former employees alleging fraud and token manipulation. Liu said he could not comment on the matter because it is pending litigation. Theta has previously denied the allegations.
Frontier AI training will remain centralized for the foreseeable future, but AI computing is shifting away to inference, agents and production workloads that require looser coordination. Those workloads reward cost efficiency, geographic distribution and elasticity.
“This cycle has seen the rise of many open-source models that are not at the scale of systems like ChatGPT, but are still capable enough to run on personal computers equipped with GPUs such as the RTX 4090 or 5090,” Liu’s co-founder and Theta tech chief Jieyi Long, told Cointelegraph.
With that level of hardware, users can run diffusion models, 3D reconstruction models and other meaningful workloads locally, creating an opportunity for retail users to share their GPU resources, according to Long.
Decentralized GPU networks are not a replacement for hyperscalers, but they are becoming a complementary layer.
As consumer hardware grows more capable and open-source models become more efficient, a widening class of AI tasks can move outside centralized data centers, allowing decentralized models to fit in the AI stack.
Bitcoin’s MVRV Z-score printed record lows on a rolling two-year basis, making BTC price more “undervalued” than at the pit of past bear markets.
Bitcoin (BTC) may be “close to the end” of its correction as a classic BTC price metric beats records.
Key points:
Bitcoin’s MVRV Z-score is at record lows on two-year rolling time frames.
The “wild” data is leading to predictions of an imminent BTC price recovery.
Analysis says that the precious metals rally is “done for now.”
MVRV Z-score says Bitcoin is “undervalued”
In an X post Friday, crypto trader, analyst and entrepreneur Michaël van de Poppe confirmed the lowest-ever readings for Bitcoin’s MVRV Z-score.
“This is a phenomenal chart,” he told followers about the data, sourced from crypto analyst James Easton.
Easton agreed that the chart now looks “wild,” having fallen to the lowest levels ever recorded.
MVRV refers to market value versus realized value, and measures the price at which the BTC supply last moved (realized cap) relative to the value of all BTC in existence (market cap).
The Z-score divides that ratio by the standard deviation of market cap, giving clear “overvalued” and “undervalued” ranges for Bitcoin at a given point in time.
“The current Z-Score of $BTC is lower than during the bear market bottom in 2015, 2018, COVID crash 2020 and 2022,” Van de Poppe noted about rolling two-year time frames.
“That’s how deep we’re in the bear market, and yes, we’re close to the end of it.”
Bitcoin MVRV Z-Score. Source: Glassnode
Raw data from onchain analytics platform Glassnode puts the Z-score at its lowest levels since October 2023. At the time, BTC/USD traded at around $30,000.
The last time that the “live” Z-score dipped into its green “undervalued” zone was at the end of the last bear market in 2022.
Precious metals prep key BTC price “trigger”
Bitcoin price action fell to new two-month lows this week amid a sudden sell-off across risk assets and precious metals.
Earlier, Cointelegraph reported on a prediction that the period around the January monthly close would see Bitcoin put in a long-term floor, similar to the end of previous bear markets.
Reacting, Van de Poppe said that both gold and silver were “done for now.”
“The markets are dropping massively, as they are down 10-15% the past 24 hours,” he wrote on X.
“I’m not saying: the bull is over. No, far from it. But it will consolidate, and that’s also the trigger you’d like to see for Bitcoin.”
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.
BNB Chain pushes 0 Fee Carnival deadline to Feb 28, covering gas for USDC, USD1, and U transfers across major exchanges and wallets. Over $4.5M saved so far.
BNB Chain has extended its zero-fee stablecoin initiative through February 28, 2026, marking the fourth consecutive extension of a program that has now covered over $4.5 million in user gas fees since launch.
The “0 Fee Carnival” eliminates gas costs for USDC, USD1, and U transactions across withdrawals, wallet transfers, and cross-chain bridges on BNB Smart Chain and opBNB.
Exchange Partners Offering Free Withdrawals
Nine centralized exchanges now support gas-free stablecoin withdrawals to BSC, with minimum thresholds varying by platform. Binance leads with the broadest coverage: USD1 and USDC on BSC (minimum $10), USDC on opBNB ($20 minimum), and U on BSC ($5 minimum).
Bitget, MEXC, and Ourbit offer USD1 and USDC withdrawals with $10 minimums. Bitmart supports both BSC and opBNB withdrawals at a $20 threshold. BingX and LBank provide USDC withdrawals with no stated minimum, while HTX has committed to zero-fee USD1 withdrawals permanently.
Wallet-to-Wallet Transfer Limits
Thirteen wallets now sponsor direct transfers on BSC, including Binance Wallet, Trust Wallet, Bitget Wallet, SafePal, and TokenPocket. The terms differ by asset: USD1 and U get unlimited free transfers, while USDC is capped at two free transactions daily. All transfers require a $0.10 minimum.
The program excludes DApp interactions and swaps—only direct wallet-to-wallet sends qualify.
Bridge Fees Eliminated
Celer cBridge and Meson.fi are covering cross-chain bridge costs for USDC moving to BSC from Ethereum, Arbitrum, Polygon, Avalanche, and Optimism. Meson.fi also supports Tron as a source chain. Celer offers zero bridge fees outright, while Meson provides 100% rebates.
Why This Matters for Users
Gas fees remain a persistent friction point for stablecoin utility. With USDC’s market cap sitting at $71.64 billion, even small percentage savings on frequent transfers add up. For traders moving funds between exchanges or DeFi protocols, eliminating the $0.50-$2.00 typical BSC gas cost per transaction creates meaningful savings over time.
BNB Chain has run this program continuously since late 2025, suggesting the network views subsidized stablecoin movement as a strategic priority for ecosystem growth. The open invitation for additional wallets, exchanges, and bridges to join indicates further expansion is likely before the February deadline.
Ether (ETH) could see another sharp drop after losing the support level at $2,800, with technical charts and onchain data suggesting the downtrend will continue.
Key takeaways:
Ether’s descending and symmetrical triangle setups converge at $2,100.
Ether is at levels that have previously preceded deeper price corrections, based on onchain data.
Ether’s chart technicals converge at $2,100
The ETH/USD pair has dropped by over 10% in the last three days, dipping below the key support at $2,800.
Ether has not traded below this level since Dec. 3, 2025, and losing it suggests lower ETH price levels could be in the cards.
A bearish divergence from the relative strength index, which has dropped to 34 from 68 in early January, shows weakening price momentum.
Meanwhile, Veteran trader Peter Brandt said the “burden of proof” was on the bulls after the ETH/USD pair broke below the lower trendline of a symmetrical triangle.
Brandt’s chart points to more downside risk, particularly after the price dropped below the $2,800 mark.
ETH/USD daily chart. Source: Peter Brandt
The measured target of the pattern, calculated by adding the width of the triangle to the breakout point, is $2,100, representing a 22% decline from the current price.
As Cointelegraph reported, the area between $3,000 and $2,800 was a key support zone for Ether, and losing it has put ETH at risk of further losses.
Ethereum mirrors past pre-bear market setups
Onchain data also reveals similarities between the current ETH market setup and previous bear cycles.
Ether’s net unrealized profit/loss (NUPL) indicator has transitioned from “anxiety (yellow)” to the “fear zone (orange),” a position that is typically associated with the start of bear markets.
The NUPL measures the difference between the relative unrealized profit and the relative unrealized loss of ETH holders.
In previous market cycles, the transition to fear has accompanied extended price drawdowns, as shown in the chart below.
ETH: Net Unrealized Profit/Loss. Source: Glassnode
Meanwhile, chart technicals show that the 111-day moving average (MA) is currently trading below the 200-day MA. Similar crossovers triggered the start of deeper ETH price drawdowns during the 2018 and 2022 bear markets, as shown in the chart below.
Ether’s 111-day MA vs. 200-day MA. Source: Glassnode
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.
Opinion by: Robert Schmitt, founder and co-CEO at Cork
DeFi has entered its institutional phase. As large investors dip their toes into crypto ETFs and digital asset treasuries (DATs), the ecosystem is gradually evolving into an institutional-grade financial system in its own right, with the introduction of new financial instruments and digital counterparts of well-established ones.
DeFi’s current growth exposes mounting risks that could lead to trust roadblocks. For institutions to confidently onboard, the ecosystem must implement stronger risk guardrails and resilient infrastructure.
It’s worth exploring the main areas where risk is concentrated, how TradFi handles similar challenges, and the guardrails DeFi needs to safely scale institutional participation.
Breaking down DeFi’s biggest risk
Let’s start with protocol risk. DeFi’s composability is both its strength and its Achilles heel. The interlinking of LSTs, lending markets and perpetuals increases systemic dependency. A single exploit can cascade across protocols.
Followed by reflexivity risk, consider how staking derivatives and looping strategies create positive feedback loops that magnify market swings. As prices rise, collateral expands and leverage increases.
When prices fall, however, liquidations accelerate in the same manner, without coordinated circuit breakers.
Lastly, duration risk as lending and staking markets mature may become increasingly critical, given the need for predictable access to liquidity. Institutions need to understand the types of duration risks present in the markets they participate in. Not many are aware that the advertised withdrawal timelines for many protocols actually depend on solver incentives, strategy cooldowns and validator queues.
The institutional supercycle
DeFi’s next challenge is not more yield or higher TVL. DeFi’s next challenge is building trust. To bring the next trillion in institutional capital onchain, the ecosystem needs standardized risk guardrails and a new discipline around risk management.
The past two years of DeFi have been defined by institutional adoption. Regulated institutional products have gained massive TVL. The two most successful ETF launches in the last two years (out of 1,600 ETFs) were BlackRock’s iShares BTC and ETH ETFs. Net flows into ETH ETFs are going vertical.
Likewise, digital asset treasury companies attract capital from institutions. Recently, ETH DATs have absorbed roughly 2.5 percent of the ETH supply. The largest DAT, Bitmine Immersion, with Wall Street legend Tom Lee as chairperson, has accumulated over $9 billion of ETH in less than two months, driven by institutional demand for ETH exposure.
Stablecoins have become crypto’s product market fit amid new regulatory clarity. They now move nearly as much money each month as Visa, and their total value locked (TVL) across protocols approaches $300 billion.
Similarly, the theme of tokenization has gained momentum, as evidenced by the rapid growth of tokenized Real World Assets (RWAs). Major institutions are tokenizing products, including Robinhood Europe, which is tokenizing its entire stock exchange, and BlackRock, which is tokenizing its T-bill BUIDL product.
Both stablecoins and RWA tokenization growth are driving the narrative that the future of the financial system will be on Ethereum. This, in turn, is driving the institutional adoption of ETFs and DATs.
The case for standardized risk management
According to a recent report by Paradigm, risk management comes in second as a cost category for institutional finance. This is because it is properly understood as an operational pillar that goes beyond checking a compliance checkbox. While traditional finance has not eliminated risk altogether, it has certainly systematized risk to the furthest extent.
In contrast, DeFi treats risk as a variable that varies from protocol to protocol. Each smart contract, vault and strategy defines and discloses risk differently — if at all. The result is idiosyncratic risk management and a lack of comparability across protocols.
TradFi has built shared frameworks, such as clearinghouses and rating agencies, as well as standardized disclosure norms, to address these types of risks and their real-world analogies. DeFi needs its own versions of those institutions: open, auditable and interoperable standards for quantifying and reporting on risk.
DeFi does not have to abandon experimentation to become a more mature ecosystem, but it could definitely benefit from formalizing it. The current risk framework established by DeFi protocols will not suffice moving forward.
If we are determined to break through the next wave of institutional adoption, however, we can follow the risk management principles established for financial instruments in traditional finance.
Opinion by: Robert Schmitt, founder and co-CEO at Cork.
This opinion article presents the contributor’s expert view and it may not reflect the views of Cointelegraph.com. This content has undergone editorial review to ensure clarity and relevance, Cointelegraph remains committed to transparent reporting and upholding the highest standards of journalism. Readers are encouraged to conduct their own research before taking any actions related to the company.
This opinion article presents the contributor’s expert view and it may not reflect the views of Cointelegraph.com. This content has undergone editorial review to ensure clarity and relevance, Cointelegraph remains committed to transparent reporting and upholding the highest standards of journalism. Readers are encouraged to conduct their own research before taking any actions related to the company.
AAVE price prediction shows potential recovery to $190-195 range by February 2026, though current technical indicators suggest caution with RSI at 36.78 and price near lower Bollinger Band.
Recent analyst forecasts paint a cautiously optimistic picture for AAVE’s medium-term prospects. According to Caroline Bishop’s January 27 analysis, “AAVE Price Prediction Summary: Short-term target (1 week): $157-162; Medium-term forecast (1 month): $190-195 range; Bullish breakout level: $157.68; Critical support: $149.32.”
Peter Zhang reinforced this bullish Aave forecast on January 26, noting that “AAVE shows potential recovery toward analyst targets of $190-195 by February 2026, despite current bearish momentum.” Similarly, Zach Anderson’s January 24 assessment highlighted that “Aave (AAVE) trades at $156.65 with analysts eyeing $190-195 by February 2026, though bearish MACD and oversold conditions suggest near-term caution around $151 support.”
These predictions suggest consensus among analysts for a potential 33-36% upside move from current levels, though technical headwinds remain a concern.
AAVE Technical Analysis Breakdown
AAVE’s current technical picture presents mixed signals that investors should carefully consider. Trading at $142.96, the token has experienced a sharp -7.28% decline in the past 24 hours, with the price action confined to a range between $155.17 and $139.81.
The RSI reading of 36.78 indicates AAVE is approaching oversold territory but hasn’t reached extreme levels yet, suggesting potential for further downside before a reversal. The MACD histogram at -0.0000 confirms bearish momentum, though the convergence suggests the selling pressure may be waning.
Perhaps most telling is AAVE’s position within the Bollinger Bands. With a %B reading of 0.0313, the token is trading very close to the lower band at $141.70, indicating oversold conditions. The middle band at $161.89 represents the 20-period moving average, which now serves as significant resistance.
Key support and resistance levels reveal a clear technical roadmap. Immediate resistance sits at $152.15, followed by stronger resistance at $161.34. On the downside, immediate support is found at $136.79, with stronger support at $130.62.
Aave Price Targets: Bull vs Bear Case
Bullish Scenario
The bull case for AAVE price prediction centers on a successful bounce from current oversold levels. If AAVE can reclaim the $157.68 breakout level identified by analysts, it would signal the beginning of a recovery phase toward the $190-195 target range.
Technical confirmation would come from RSI climbing back above 50, MACD turning positive, and volume expansion on any upward moves. The 20-day moving average at $161.89 would need to be reclaimed to validate the bullish thesis, potentially opening the path to test the upper Bollinger Band at $182.08 as an interim target.
Bearish Scenario
The bear case remains compelling given current technical deterioration. A break below the critical support at $136.79 could trigger accelerated selling toward the $130.62 level. More concerning would be a failure to hold the analyst-identified support at $149.32, which could invalidate the near-term bullish outlook.
Risk factors include continued selling pressure in the broader DeFi sector, potential liquidations if key support levels break, and the significant gap between current price and analyst targets requiring a 33%+ rally.
Should You Buy AAVE? Entry Strategy
For investors considering AAVE, the current technical setup suggests a staged approach. The first potential entry point lies around current levels ($142-145), given the proximity to the lower Bollinger Band and analyst-identified support zones.
A more conservative entry strategy would wait for confirmation of a bounce from the $136.79 support level, with a stop-loss placed below $130.62. Aggressive traders might consider entering on any break above $152.15 with volume confirmation, targeting the $161-165 resistance zone.
Risk management remains crucial given AAVE’s 14-day ATR of $8.86, indicating significant daily volatility. Position sizing should account for potential 6-8% daily moves in either direction.
Conclusion
This AAVE price prediction presents a cautiously optimistic outlook despite current technical weakness. While analyst targets of $190-195 by February 2026 represent substantial upside potential, the path higher faces significant technical hurdles.
The convergence of oversold conditions, analyst support, and key technical levels around $142-149 suggests a potential inflection point. However, investors should remain vigilant for any breakdown below critical support levels that could invalidate the bullish Aave forecast.
Disclaimer: Cryptocurrency price predictions are speculative and subject to high volatility. This analysis is for informational purposes only and should not be considered financial advice. Always conduct your own research and consider your risk tolerance before investing.
Unclaimed Ether (ETH) from the infamous 2016 hack on The DAO will be redirected into a new security fund aimed at strengthening the network, says Ethereum advocate Griff Green.
“There’s a lot of money just sitting in random contracts that were supposed to be returned to people who were affected by the hack,” Green said in an interview on Thursday with Unchained podcast host Laura Shin, reiterating plans to launch the security fund.
The DAO was a decentralized autonomous organization that an anonymous hacker exploited in June 2016 to siphon more than $50 million worth of Ether at the time.
The incident led to a hard fork of the Ethereum blockchain to recover the funds, splitting the community and ultimately creating two separate chains: Ethereum and Ethereum Classic.
Griff Green spoke to Laura Shin on the Unchained podcast on Thursday. Source: Unchained
Green explained that the hard fork returned a lot of the Ether held in The DAO to tokenholders, but the claims process was not straightforward. Green said that certain “edge cases” were handled through a multisignature wallet he joined, involving around $6 million.
While more than 80% of those funds have since been claimed, the remaining balance is now worth around $200 million. “We’re going to stake them and use the revenue to actually support Ethereum security,” he said.
Making Ethereum safer than a bank is the goal
“It makes sense that The DAO is now going to be focused on security,” Green said.
“We really want to stick to our guns with The DAO and live up to the name of The DAO, so we’re going to focus on DAO-style distributions,” he said.
Green said that while The DAO has an “incredible” pool of developers capable of identifying security projects to support, the priority will be on security distribution methods, including retroactive funding, quadratic funding, conviction voting, and ranked-choice voting, with the aim of strengthening the broader ecosystem.
“I really want to see The DAO security fund come to a place where people feel that it’s safer to store assets on Ethereum than in a bank,” Green said.
“The DAO really kickstarted the security industry in Ethereum,” Green added, noting that before the hack, there was effectively no audit market, but afterward, smart contract audits became widespread.
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