MYX slides 18% while OI climbs to $25M – Is a squeeze brewing?

ambcryptoPubblicato 2026-02-11Pubblicato ultima volta 2026-02-11

Introduzione

MYX Finance (MYX) has declined 18% amid weak fundamentals and revenue struggles. Perpetual futures activity is driving the downturn, with a negative funding rate of -1.0858% indicating dominant short positioning. However, Open Interest increased by 1% to $25 million, suggesting capital remains in the market rather than fleeing. Exchange-level data shows a divergence: while the overall market is bearish, platforms like Bybit show a majority of long positions. Spot markets also saw $224,000 in net inflows, indicating selective accumulation. Liquidity clusters above the current price may act as short-term magnets for an upward move, creating potential for near-term upside volatility despite the broader bearish trend.

MYX Finance [MYX] faces a deteriorating price outlook as the asset extends its losses. The weakness in price aligns with soft fundamentals, as the protocol struggles to generate sufficient revenue to cover operational costs.

In the near term, derivatives activity is driving market direction. Positioning across perpetual markets, whether dominated by longs or shorts, is shaping MYX’s short-term price trajectory.

Funding Rates signal short dominance

Perpetual futures activity has reinforced downside pressure. Over the past 24 hours, MYX declined 18%, at press time, with momentum accelerating during the move.

At the same time, CoinGlass data showed that the Funding Rate dropped to -1.0858%. A negative rate indicates that short positions are paying longs, reflecting a market skewed toward bearish positioning. Current price action confirms that sellers are exerting control.

Notably, the negative Funding Rate has not triggered capital flight. Open Interest (OI) rose by 1%, adding approximately $250,000 and bringing total outstanding positions to roughly $25 million.

Typically, sharp negative funding coincides with declining OI as traders unwind exposure. In this case, capital remains in the market, suggesting active participation rather than broad liquidation.

Exchange-level divergence in positioning

Despite short dominance at the aggregate level, exchange-specific data reveal divergence.

Long/Short Ratios across Binance, Bybit, KuCoin, and BingX show higher long participation. Bybit leads, with 51% of total perpetual volume attributed to long positions.

Bybit’s positioning carries added weight, given its substantial share of MYX’s Open Interest and trading volume. This divergence suggests that while overall funding skews negative, certain trader cohorts are positioning for a potential rebound.

Spot market flows show signs of selective accumulation. In the past 24 hours, MYX recorded about $224,000 in net capital inflows. Compared to its typical daily buy activity, this marks a notable uptick in demand.

Liquidity clusters define near-term structure

The liquidation heatmap highlights significant liquidity clusters above the current price. Such concentrations often act as short-term magnets, as price tends to move toward areas with dense leveraged positions.

The presence of larger clusters overhead increases the probability of a liquidity-driven upside move. Downside liquidity remains visible below current levels, though the depth is comparatively smaller than the upside clusters.

As a result, while the broader trend remains bearish, the current liquidity structure leaves room for short-term upside volatility driven by derivatives positioning and liquidation dynamics.


Final Thoughts

  • Short sellers account for a significant share of liquidity in the derivatives market.
  • Traders on Bybit, CoinEx, and BingX are increasing long exposure despite elevated downside risk.

Domande pertinenti

QWhat is the current price performance of MYX Finance and by how much has it declined?

AMYX has declined by 18% in the past 24 hours, with the momentum of the drop accelerating.

QWhat does the negative Funding Rate of -1.0858% indicate about market sentiment for MYX?

AThe negative Funding Rate indicates that short positions are paying longs, reflecting a market that is skewed toward bearish (short) positioning and that sellers are in control.

QDespite the negative funding, what happened to Open Interest (OI) and what does this suggest?

AOpen Interest (OI) actually rose by 1%, adding approximately $250,000 to bring the total to $25 million. This suggests capital is remaining in the market for active participation rather than traders broadly liquidating and closing their positions.

QWhich exchange shows a majority of long positions for MYX perpetual futures, according to the Long/Short Ratios?

ABybit leads with 51% of its total perpetual volume attributed to long positions.

QAccording to the liquidation heatmap, where are the significant liquidity clusters located and what is their likely effect?

ASignificant liquidity clusters are located above the current price. These concentrations often act as short-term magnets, increasing the probability of a liquidity-driven upside move as price tends to gravitate toward areas with dense leveraged positions.

Letture associate

TechFlow Intelligence Bureau: Chip Stocks Lose Trillions in a Single Day, Bitcoin Falls Below $60,000, US-Iran Conflict Escalates

**Daily Tech & Markets Roundup: AI Advances, Market Turmoil, and Geopolitical Tensions** **AI / LLMs**: Anthropic's internal report on AI self-improvement sparked serious discussions about Recursive Self-Improvement (RSI). Meanwhile, debate continues on AI coding tools after Claude was accused of introducing bugs into the rsync codebase. In positive news, DeepSeek V4 Flash impressed in local deployment tests, and GitHub Copilot now supports custom endpoints for local models. A surprising research turn suggests removing chain-of-thought prompting can sometimes improve LLM performance. **Crypto / Web3**: Bitcoin plunged below $60,000, with its RSI hitting levels last seen during the COVID-19 crash, driven by strong U.S. jobs data reviving interest rate hike fears. Discussions highlight Ethereum DeFi's continued lack of a smooth consumer payment layer. **Chips / Hardware**: Chip stocks suffered a massive sell-off, with the Philadelphia Semiconductor Index posting its worst single-day drop in six years, erasing over a trillion dollars in value. Marvell, Micron, AMD, and Intel were among the biggest losers. **Tech Companies**: A leaked Microsoft document revealing goals to make Copilot "addictive" drew criticism. LinkedIn founder Reid Hoffman left Microsoft's board to focus full-time on his AI agent startup, Manus. Google was revealed to be paying SpaceX $920 million monthly for AI training compute. **Markets & Macro**: A blowout U.S. jobs report (172k vs. 80k expected) crushed hopes for near-term rate cuts, sending Treasury yields soaring and triggering a broad market sell-off. CEOs from Kraft, McDonald's, and Whirlpool simultaneously warned U.S. consumers are exhausting their savings. **Geopolitics**: U.S.-Iran tensions escalated with missile/drone interceptions and U.S. strikes on Iranian radar sites, keeping the critical Strait of Hormuz largely closed since late February and posing ongoing oil supply risks. **The Bottom Line**: The strong jobs data acted as a single trigger for correlated sell-offs across equities, crypto, and chips. Underlying the volatility is a stark contradiction between robust employment data and warnings of consumer weakness, alongside geopolitical risks that could reignite inflation, leaving markets to price in a fraught macro outlook with no clear "soft landing" path.

marsbit2 h fa

TechFlow Intelligence Bureau: Chip Stocks Lose Trillions in a Single Day, Bitcoin Falls Below $60,000, US-Iran Conflict Escalates

marsbit2 h fa

It Took Me a Year to See the Bitter Truth About Agent Payments

After a year building infrastructure for the Agent economy, engaging with major players like Stripe, Visa, and Coinbase, the author shares a sobering analysis of the current state of Agent payments. The core finding is a stark lack of genuine, immediate demand across most envisioned use cases. The article breaks down four key market segments: 1. **Agent-to-Merchant (Consumer Shopping):** For most product categories (e.g., clothing, electronics), conversational AI shopping is a step backwards from visual e-commerce interfaces. While agents excel at understanding needs, they can't replace side-by-side product comparison. Real merchant interest is defensive "Agent Engine Optimization," not driven by current customer demand. Potential exists for high-frequency, low-decision purchases (like food delivery) or navigating complex store UIs, but these require massive B2C distribution channels dominated by giants like Amazon. 2. **Agent-to-API (Developer Services):** Developers already have subscriptions and billing relationships for APIs (compute, data). Prepaid balances solve micro-payment issues for low transaction volumes. A deeper structural problem is that major SaaS vendors' business models rely on enterprise contracts, resisting granular pay-per-call pricing. While protocols like MPP and x402 serve the long tail of niche services, this market is small and developers are historically low-willingness-to-pay. 3. **Agent-to-Agent:** This remains largely theoretical with minimal transaction volume. While it represents a long-term bet on a fundamentally new transaction infrastructure (sub-second, micro-penny to million-dollar, multi-party settlements), it does not constitute a present market. 4. **Agent-to-Finance:** This is the only category with existing, paying demand. Integrating AI into financial workflows (trading, portfolio management) is a natural evolution and enables new capabilities like autonomous rebalancing. However, competition favors established, regulated institutions. The "real problem" is not moving money between agents, but the broader challenge of **coordination**—orchestrating work between agents and humans, verifying outcomes, and settling results. Payment is just one component of settlement, which is itself part of coordination. Companies that solve the coordination layer will subsume payment, not the other way around. While well-funded incumbents build defensively for a long-term future, startups must find where the market is today—which, for the author's team, lies outside these four categories in an area of real, growing, and underserved activity.

marsbit3 h fa

It Took Me a Year to See the Bitter Truth About Agent Payments

marsbit3 h fa

It Took Me a Year to See the Hard Truth About Agent Payments

**Title: It Took Me a Year to See the Hard Truth About Agent Payments** Over the past year, I've worked on infrastructure for the Agent economy, engaging with major players like Stripe, Visa, Coinbase, and numerous startups. The findings reveal a stark reality: genuine, widespread demand for Agent-based payments does not yet exist. **Key Observations:** * **Agent-to-Merchant (Shopping):** The user experience for AI shopping often falls short, especially for visual product discovery. While AI excels at understanding needs, conversational interfaces can't yet replace browsing and comparing multiple products visually. Current merchant interest is largely defensive ("Agent Engine Optimization") for a future that hasn't arrived. High-frequency, low-friction purchases (like food delivery) are potential fits, but lack open APIs and face high AI inference costs. Simpler, more affordable, or cross-language interactions for complex UIs are a niche opportunity but require massive consumer distribution to scale. * **Agent-to-API (Developer Tools):** Developer payment needs for APIs (computing, data, models) are already met through subscriptions and prepaid credits. The core challenge is not payment friction but supplier economics: most large SaaS providers prefer enterprise contracts over micropayments for API calls. Protocols like MPP and x402 suit the long-tail of smaller services but cater to a developer market historically reluctant to pay for these tools. Major infrastructure needs at the top of the stack are already being addressed. * **Agent-to-Agent (Machine Commerce):** This is a long-term vision with almost no current transaction volume. While a future with high-speed, high-frequency, multi-party machine-to-machine transactions would require novel infrastructure, it remains theoretical. The market is not here yet. * **Agent-to-Finance:** This is the only category with clear, present demand. Financial professionals and DeFi users already pay for tools, and AI augmentation is a natural evolution. Autonomous AI agents can enable entirely new financial strategies. However, competition is fierce from established, regulated incumbents who can more easily layer AI onto their existing products. **The Core Insight:** Companies, especially giants with long time horizons, are building defensively for a potential future of mass machine commerce. For them, early investment is a low-cost hedge. For startups, the current market reality is different. The primary challenge isn't just moving money between agents (payments). The larger, unsolved problem is **orchestration** – coordinating work between agents and humans, verifying outcomes, and then settling. Payment is just a part of settlement, which is just a part of orchestration. Companies that solve the orchestration problem will subsume payments, not the other way around. After a year of building, we see the real, growing, and underserved market opportunity lies in this broader domain of orchestration.

链捕手3 h fa

It Took Me a Year to See the Hard Truth About Agent Payments

链捕手3 h fa

Trading

Spot
Futures
活动图片