ETHfi gains 11% in 24 hours, but bearish signs cause concern

ambcryptoPublished on 2025-09-23Last updated on 2025-09-24

Key Takeaways

Why is ETHfi’s recent rally under threat?

Bearish signals from the Parabolic SAR and MACD suggest sellers are taking control, risking a price drop below key support.

Can buyers prevent a decline?

Spot investors purchased $3.37M worth of ETHfi in 48 hours, showing strong accumulation that could offset bearish pressure.


Ether.fi [ETHfi], the liquid staking protocol, recorded massive price gains in the past day after its third-quarter-to-date report revealed earnings had surged to $12.92 million—the highest level since inception.

The 11% gain recorded within this period is, however, under threat, as bears appear to be tightening their grip on the market.

This development suggests that a potential price decline could remain on the horizon, putting ETHfi at risk of falling.

The key question is whether the asset can hold its ground or succumb to bearish pressure. AMBCrypto analyzes the factors behind the move.

ETHfi at a critical zone

The recent surge in ETHfi has been building on trading activity over the past weeks, as reflected on its 1-day chart.

On the 11th of September, the asset broke out of a bullish consolidation pattern—highlighted in orange—and began trending around its support level, where it has remained for several days.

ETHfi chart.

Source: TradingView

Since then, ETHfi has shown little directional movement, with the price oscillating within defined ranges on the chart.

Under normal conditions, the support level should act as a catalyst for a rally, but that has not been the case.

Instead, ETHfi has continued to struggle at this level, raising doubts about whether buyers have enough strength to push it higher.

Indicators give a warning

ETHfi’s struggles may be an early signal of a potential decline in the coming days, based on technical indicators.

The Parabolic SAR (stop and reverse) has placed dots above the price, a clear sign that sellers currently control the market and are actively distributing.

ETHfi technical indicator.

Source: TradingView

At the same time, the Moving Average Convergence Divergence (MACD) has formed a Death Cross pattern.

This occurs when the blue MACD line crosses below the orange signal line, indicating that bearish sentiment is gaining momentum.

If the Parabolic SAR continues to place dots above the price and the MACD maintains its downward trend, ETHfi could plunge further, breaking below its key support level where it has traded for nearly 14 days.

Spot investors aren’t hold back

Spot investors, however, appear to be showing patience, choosing to accumulate rather than distribute their holdings.

Data from CoinGlass shows that investors have been accumulating ETHfi consistently over the past five days.

In the last 48 hours alone, $3.37 million worth of ETHfi has been purchased, suggesting that investors are increasing their exposure despite the bearish signals.

ETHfi spot exchange netflow.

Source: CoinGlass

If accumulation continues at this pace, the chances of ETHfi dropping below its support level would remain slim.

Instead, sustained buying pressure could create conditions for ETHfi to reverse course and potentially establish a stronger bullish trend on the charts.

Share

Trending Cryptos

Related Reads

Behind the AI Scorecards Lies a Chinese 'Question Setter'

Behind the AI scorecards that dominate industry discussions—benchmarks like MMLU-Pro, MMMU, and MMMU-Pro—stands a Chinese-Canadian researcher: Wenhu Chen. As an assistant professor at the University of Waterloo and founder of the TIGER Lab, Chen has become a key "exam-setter" for evaluating large language and multimodal models. Chen first gained broader recognition with MMLU-Pro, a more challenging and stable update to the popular MMLU benchmark. As top models like OpenAI’s o3 began achieving near-perfect scores on the original MMLU, it became difficult to distinguish their true capabilities. MMLU-Pro introduced more complex reasoning questions, expanded answer choices, and filtered out ambiguous or simple items, effectively reintroducing differentiation among state-of-the-art models. His work on MMMU addressed the evaluation of multimodal models, requiring them to integrate visual information (like charts, diagrams, or tables) with textual knowledge across diverse academic subjects. Even the strongest models initially scored only around 56-59%, highlighting significant room for improvement in genuine multimodal reasoning. MMMU-Pro further refined this by preventing models from bypassing visual cues. Chen’s research focus has long been on complex information understanding and reasoning. His background—including a PhD at UC Santa Barbara, research at Google/DeepMind on Gemini, and now a role in Meta’s superintelligence lab—provides deep insight into model development and their potential weaknesses. His TIGER Lab also builds models (e.g., for video understanding and generation), ensuring his evaluation benchmarks are grounded in practical challenges. While AI headlines often spotlight company leaders and product launches, Chen’s work exemplifies the critical, behind-the-scenes contributions of researchers crafting the rigorous standards that define and drive progress in AI capabilities.

marsbit17m ago

Behind the AI Scorecards Lies a Chinese 'Question Setter'

marsbit17m ago

STRC Unpegged by 11%, Can Strategy's Perpetual Motion Machine Keep Turning?

STRC, the perpetual preferred stock of MicroStrategy, is experiencing a persistent de-pegging from its target par value of $100, with the discount recently widening to over 11%. This de-anchoring challenges the core design of STRC, which was intended as a stable, income-oriented security operating near $100. As a crucial funding engine for MicroStrategy's Bitcoin acquisition strategy, STRC's price reflects market confidence in the company's entire capital model. The company's "capital flywheel" relies on issuing STRC at or above $100 via an At-the-Market (ATM) program to raise cash for buying Bitcoin, thereby boosting company equity and theoretically supporting STRC's value. A monthly adjustable dividend mechanism was designed to maintain this peg. Despite raising the dividend to 11.5% and increasing payment frequency, the de-pegging persists. Market concerns extend beyond technical factors like leveraged arbitrage unwinding. Analysts point to MicroStrategy's limited cash reserves relative to its ~$1.7 billion annual dividend obligation for preferred shares. While the company counters that its vast Bitcoin holdings could cover decades of payments, this argument hinges on the potential need to sell Bitcoin—a shift from its longstanding "hodl" narrative. The company's recent sale of a small amount of BTC, framed as a test, amplified these liquidity and strategy concerns. If STRC remains discounted, impairing MicroStrategy's ability to raise cheap capital, fears may grow that the company could sell more Bitcoin to meet obligations. This scenario could transform MicroStrategy from a major market buyer into a potential seller, posing significant downside risk for Bitcoin. The re-pegging of STRC is thus a key indicator for the health of MicroStrategy's capital structure and its market impact.

Odaily星球日报31m ago

STRC Unpegged by 11%, Can Strategy's Perpetual Motion Machine Keep Turning?

Odaily星球日报31m ago

Silicon Valley's Most Sought-After New Role Has Emerged

Silicon Valley's New Most Wanted Job: The Rise of the Forward Deployment Engineer The AI industry is witnessing a significant shift. The focus has moved from developing cutting-edge models to deploying them effectively within enterprises. This has made the "Forward Deployment Engineer" (FDE) a critical and highly sought-after role at major firms like OpenAI, Anthropic, and Google. For the past three years, the industry prioritized model scientists. However, companies are now facing a harsh reality: purchasing powerful AI tools does not guarantee productivity gains or organizational change. The biggest hurdle is not the technology itself, but integrating it into complex legacy systems, workflows, and corporate cultures. This includes challenges like data silos, compliance requirements, and internal resistance. The FDE role, pioneered by Palantir Technologies, addresses this "last-mile" problem. FDEs are deployed on-site with clients for extended periods. Their job is to deeply understand the client's specific organizational structure, processes, and pain points, then tailor and implement the AI solution accordingly. They combine skills in technology, project management, and organizational change. A clear signal of this trend emerged in May 2026 when three AI giants made major moves. Anthropic launched a $1.5B joint venture for enterprise deployment. OpenAI formed an independent deployment subsidiary, DeployCo, with over $4B in commitments and acquired a deployment consultancy. Google Cloud's CEO publicly announced a large-scale recruitment drive for FDEs. This shift represents a fundamental change in the software business model: from selling tools to selling guaranteed outcomes. FDEs are the agents of this change, responsible for delivering a working system within the production environment, not just a demo. Real-world cases, such as challenges at Goldman Sachs (compliance barriers) and Target (internal cultural resistance), illustrate that the primary obstacles to AI adoption are organizational, not technical. An FDE's value lies in navigating these human and procedural complexities to facilitate a successful "AI migration." In essence, as core AI technology becomes more accessible and affordable, the true premium is shifting to the human expertise required to understand organizations and drive change—making the FDE role pivotal for the next phase of the AI revolution.

marsbit31m ago

Silicon Valley's Most Sought-After New Role Has Emerged

marsbit31m ago

When the World Cup Collides with Agents: From Web2 to Web3, How Are Wallets Evolving into Agentic Wallets?

World Cup as a Catalyst for Agentic Wallets: From Web2 to Web3 This article explores how the World Cup provides a real-world scenario for observing the evolution of digital wallets from simple asset managers towards "Agentic Wallets"—intelligent, AI-powered interfaces. Using the example of prediction markets like Polymarket, it illustrates how AI Agents can lower the barrier to Web3 interaction. Instead of navigating complex DApps, users can express intent in natural language (e.g., "I think Portugal will win") within platforms like Discord or web pages. The Agent then interprets this intent, finds the relevant market, and seamlessly guides the user through the on-chain transaction via their wallet. The core shift is from wallets as mere "function menus" for signing transactions to "intent interpreters" that understand user goals. The article highlights parallel developments in traditional finance, such as Mastercard's "Agent Pay" and WeChat Pay's AI tests, which focus on granting AI controlled, authorized, and auditable payment capabilities. This underscores a broader trend of AI entering the financial layer. However, the article emphasizes that the primary challenge for Agentic Wallets in Web3 is not automation but establishing clear security boundaries. Unlike traditional systems with chargebacks, on-chain transactions are often irreversible. Therefore, future wallets must ensure users retain ultimate control and comprehension. They need to transparently communicate an Agent's permissions, spending limits, authorized durations, and provide easy ways to pause or revoke access. The World Cup experiments represent early steps toward wallets that are not just applications but ubiquitous, intelligent interfaces that simplify Web3 while keeping users securely in control.

marsbit1h ago

When the World Cup Collides with Agents: From Web2 to Web3, How Are Wallets Evolving into Agentic Wallets?

marsbit1h ago

Options Don't Work in DeFi? Vitalik Might Not Agree

For years, the prevailing view has been that options struggle to gain traction in DeFi due to complexity, fragmented liquidity, and lack of natural demand compared to products like perpetual futures. However, a recent algorithmic stablecoin design proposed by Vitalik Buterin presents a different perspective, using options not as a standalone trading product, but as foundational infrastructure for other financial instruments. In this design, one unit of ETH is split into two components: a "stable" side (P) that retains value up to a specified strike price, and an "upside" side (N) that captures all appreciation above that strike. Combined, they always equal one ETH, eliminating debt, margin, and liquidation risks inherent in typical collateralized debt position (CDP) stablecoins. The stable component essentially mimics the payoff of a covered call option. To function as a stablecoin, this structure requires continuously rolling deep in-the-money calls, which introduces challenges like rollover slippage, predictable transaction flow vulnerable to front-running, and persistent liquidity needs. A core hurdle is finding consistent buyers for the leveraged ETH upside exposure (N). While it offers leverage without funding rates or liquidation, it must compete with simpler alternatives like direct call options or perpetuals. The system's scalability depends on a sustained demand for this specific form of leverage. The author draws parallels to their experience with Rysk, where earlier versions of DeFi options protocols struggled. The breakthrough came with Rysk V12, which aligns incentives: asset holders generate yield by selling covered calls against their holdings, while market makers efficiently acquire the desired option exposure. This demonstrates that options can find product-market fit when embedded as a risk distribution and pricing engine within structured products, stablecoins, or yield-generating assets, rather than marketed as a complex direct trading instrument. Vitalik's proposal reinforces this architectural approach—using fully collateralized, non-custodial, and physically settled options as a fundamental building block. The real opportunity for options in DeFi may lie not in becoming the next perpetual swap, but in powering the next generation of on-chain financial products.

marsbit2h ago

Options Don't Work in DeFi? Vitalik Might Not Agree

marsbit2h ago

Trading

Spot
Futures

Hot Articles

Ether.fi Explained

Ether.fi aims to further engage in the staking ecosystem by building its own AVS.

28.2k Total ViewsPublished 2024.03.28Updated 2024.03.28

Ether.fi Explained

How to Buy ETHFI

Welcome to HTX.com! We've made purchasing ether.fi (ETHFI) simple and convenient. Follow our step-by-step guide to embark on your crypto journey.Step 1: Create Your HTX AccountUse your email or phone number to sign up for a free account on HTX. Experience a hassle-free registration journey and unlock all features.Get My AccountStep 2: Go to Buy Crypto and Choose Your Payment MethodCredit/Debit Card: Use your Visa or Mastercard to buy ether.fi (ETHFI) instantly.Balance: Use funds from your HTX account balance to trade seamlessly.Third Parties: We've added popular payment methods such as Google Pay and Apple Pay to enhance convenience.P2P: Trade directly with other users on HTX.Over-the-Counter (OTC): We offer tailor-made services and competitive exchange rates for traders.Step 3: Store Your ether.fi (ETHFI)After purchasing your ether.fi (ETHFI), store it in your HTX account. Alternatively, you can send it elsewhere via blockchain transfer or use it to trade other cryptocurrencies.Step 4: Trade ether.fi (ETHFI)Easily trade ether.fi (ETHFI) on HTX's spot market. Simply access your account, select your trading pair, execute your trades, and monitor in real-time. We offer a user-friendly experience for both beginners and seasoned traders.

3.0k Total ViewsPublished 2024.03.29Updated 2026.06.02

How to Buy ETHFI

Discussions

Welcome to the HTX Community. Here, you can stay informed about the latest platform developments and gain access to professional market insights. Users' opinions on the price of ETHFI (ETHFI) are presented below.

活动图片