AVAX’s rally odds – Here’s why traders should look out for liquidity

ambcryptoPublicado em 2026-02-11Última atualização em 2026-02-11

Resumo

Despite a quiet broader market, the Avalanche (AVAX) ecosystem has demonstrated significant on-chain strength. It recorded $135 million in monthly net inflows, ranking fourth for both weekly and daily inflows. Most notably, active addresses surged over 242% since early January, surpassing 1.6 million, indicating deep network engagement even as the price fell. Technically, AVAX found support between $8.85–$11.86, with the RSI deeply oversold and the MACD showing a bullish crossover, suggesting a potential local bottom. However, a true price reversal requires a confirmed increase in trading volume. A key factor is the concentration of upside liquidation liquidity between $10–$12, which could be a target for market makers and a potential catalyst for increased volatility. The data presents a tension between strong underlying adoption and bearish price action, setting the stage for a possible move driven by liquidity dynamics.

The AVAX ecosystem has continued to attract investor attention over the last few weeks, despite a quiet market. For example – On 10 February, activity across the sector slowed down significantly.

However, for its part, Avalanche remained as active as ever. In fact, the chain recorded $135 million in monthly net inflows and led the way among the market’s blockchains.

Addiitonally, its inflow trends stood out clearly too. Weekly inflows climbed to $60 million, while daily inflows totaled $7 million. Thanks to the same, Avalanche was ranked fourth in terms of both weekly and daily net inflows.

Hence, the question – Are more significant market moves ahead?

Active Addresses surprise for AVAX

That’s not all either. Avalanche’s [AVAX] active addresses have surged by over 242% since early January, surpassing all prior 2024 levels and hitting new highs.

According to Token Terminal data, monthly active addresses climbed beyond 1.6 million – A clear sign of intensified network engagement. Daily figures pushed even higher on 10 February, hitting record peaks above 1.6–1.7 million on the C-Chain.

This surge occurred despite the price action punishing holders, reflecting fractured confidence and widespread bearish sentiment. And yet, participants have continued to transact robustly, expanding usage despite deteriorating market mood.

Put simply, real adoption and on-chain conviction deepened even as surface-level narratives turned pessimistic. This is the kind of classic decoupling that often precedes reversals on the price charts.

Will the structural support hold on?

AVAX’s price action on the daily time frame told a brutal, unforgiving story. At press time, the altcoin had retraced over 84% from its October peak before stabilizing around the $8.85–$11.86 support zone.

Meanwhile, sellers showed clear exhaustion near the $8-level after sustained downside pressure. Therefore, downside momentum weakened as selling intensity gradually faded.

Notably, the MACD flashed a bullish cross directly at the support level during this phase. At the same time, the RSI remained deeply oversold at 29.87 too. As a result, the RSI holding at such depressed levels suggested AVAX was at or around a local bottom.

Worth noting, however, that technical signals alone might not be enough to shift market structure.

For a meaningful expansion to begin, volume must be expected to rise clearly. Without confirmation, the setup will risk becoming another failure, rather than a true reversal.

Upside liquidity concentrated at $10–$12

Downside liquidity had largely been cleared before 10 February 2026. As a result, the 2-week liquidation data showed growing upside liquidity clustered between $10 and $12 at press time.

This imbalance shifted attention upwards. Not because of optimism, but mechanics. Market makers often target such zones with ruthless efficiency.

Therefore, volatility might just be inevitable, rather than optional. As it stands, the liquidity is above the price, daring the market to react. Only time will tell if this liquidity can ignite the most awaited expansion for AVAX.


Final Thoughts

  • On-chain data reflected tension, not recovery, as capital and activity contradicted the damage seen on the price charts
  • AVAX may be primed for volatility, driven by liquidity.

Perguntas relacionadas

QWhat was the amount of Avalanche's monthly net inflows and how did it rank among other blockchains?

AAvalanche recorded $135 million in monthly net inflows, leading the way among the market's blockchains.

QBy what percentage did Avalanche's active addresses surge since early January, and what milestone did they reach?

AAvalanche's active addresses surged by over 242% since early January, surpassing all prior 2024 levels and hitting new highs beyond 1.6 million.

QWhat two key technical indicators suggested that AVAX might be at a local price bottom?

AThe MACD flashed a bullish cross at the support level, and the RSI remained deeply oversold at 29.87, suggesting a local bottom.

QAccording to the liquidation data, where was the upside liquidity for AVAX concentrated?

AThe upside liquidity was concentrated in the $10 to $12 price range.

QWhat does the article suggest is the primary driver for potential upcoming volatility in AVAX's price?

AThe article suggests that the primary driver for potential volatility is liquidity mechanics, with market makers likely to target the concentrated liquidity zones above the current price.

Leituras Relacionadas

OpenAI Post-Training Engineer Weng Jiayi Proposes a New Paradigm Hypothesis for Agentic AI

OpenAI engineer Weng Jiayi's "Heuristic Learning" experiments propose a new paradigm for Agentic AI, suggesting that intelligent agents can improve not just by training neural networks, but also by autonomously writing and refining code based on environmental feedback. In the experiment, a coding agent (powered by Codex) was tasked with developing and maintaining a programmatic strategy for the Atari game Breakout. Starting from a basic prompt, the agent iteratively wrote code, ran the game, analyzed logs and video replays to identify failures, and then modified the code. Through this engineering loop of "code-run-debug-update," it evolved a pure Python heuristic strategy that achieved a perfect score of 864 in Breakout and performed competitively with deep reinforcement learning (RL) algorithms in MuJoCo control tasks like Ant and HalfCheetah. This approach, termed Heuristic Learning (HL), contrasts with Deep RL. In HL, experience is captured in readable, modifiable code, tests, logs, and configurations—a software system—rather than being encoded solely into opaque neural network weights. This offers potential advantages in explainability, auditability for safety-critical applications, easier integration of regression tests to combat catastrophic forgetting, and more efficient sample use in early learning stages, as demonstrated in broader tests on 57 Atari games. However, the blog acknowledges clear limitations. Programmatic strategies struggle with tasks requiring long-horizon planning or complex perception (e.g., Montezuma's Revenge), areas where neural networks excel. The future vision is a hybrid architecture: specialized neural networks for fast perception (System 1), HL systems for rules, safety, and local recovery (also System 1), and LLM agents providing high-level feedback and learning from the HL system's data (System 2). The core proposition is that in the era of capable coding agents, a significant portion of an AI's learned experience could be maintained as an auditable, evolving software system.

marsbitHá 19m

OpenAI Post-Training Engineer Weng Jiayi Proposes a New Paradigm Hypothesis for Agentic AI

marsbitHá 19m

Your Claude Will Dream Tonight, Don't Disturb It

This article explores the recent phenomenon of AI companies increasingly using anthropomorphic language—like "thinking," "memory," "hallucination," and now "dreaming"—to describe machine learning processes. Focusing on Anthropic's newly announced "Dreaming" feature for its Claude Agent platform, the piece explains that this function is essentially an automated, offline batch processing of an agent's operational logs. It analyzes past task sessions to identify patterns, optimize future actions, and consolidate learnings into a persistent memory system, akin to a form of reinforcement learning and self-correction. The article draws parallels to similar features in other AI agent systems like Hermes Agent and OpenClaw, which also implement mechanisms for reviewing historical data, extracting reusable "skills," and strengthening long-term memory. It notes a key difference from human dreaming: these AI "dreams" still consume computational resources and user tokens. Further context is provided by discussing the technical challenges of managing AI "memory" or context, highlighting the computational expense of large context windows and innovations like Subquadratic's new model claiming drastically longer contexts. The core critique argues that this strategic use of human-centric vocabulary does more than market products; it subtly reshapes user perception. By framing algorithms with terms associated with consciousness, companies blur the line between tool and autonomous entity. This linguistic shift can influence user expectations, tolerance for errors, and even perceptions of responsibility when systems fail, potentially diverting scrutiny from the companies and engineers behind the technology. The article concludes by speculating that terms like "daydreaming" for predictive task simulation might be next, continuing this trend of embedding the idea of an "inner life" into computational processes.

marsbitHá 21m

Your Claude Will Dream Tonight, Don't Disturb It

marsbitHá 21m

Trading

Spot
Futuros

Artigos em Destaque

Como comprar AVAX

Bem-vindo à HTX.com!Tornámos a compra de Avalanche (AVAX) simples e conveniente.Segue o nosso guia passo a passo para iniciar a tua jornada no mundo das criptos.Passo 1: cria a tua conta HTXUtiliza o teu e-mail ou número de telefone para te inscreveres numa conta gratuita na HTX.Desfruta de um processo de inscrição sem complicações e desbloqueia todas as funcionalidades.Obter a minha contaPasso 2: vai para Comprar Cripto e escolhe o teu método de pagamentoCartão de crédito/débito: usa o teu visa ou mastercard para comprar Avalanche (AVAX) instantaneamente.Saldo: usa os fundos da tua conta HTX para transacionar sem problemas.Terceiros: adicionamos métodos de pagamento populares, como Google Pay e Apple Pay, para aumentar a conveniência.P2P: transaciona diretamente com outros utilizadores na HTX.Mercado de balcão (OTC): oferecemos serviços personalizados e taxas de câmbio competitivas para os traders.Passo 3: armazena teu Avalanche (AVAX)Depois de comprar o teu Avalanche (AVAX), armazena-o na tua conta HTX.Alternativamente, podes enviá-lo para outro lugar através de transferência blockchain ou usá-lo para transacionar outras criptomoedas.Passo 4: transaciona Avalanche (AVAX)Transaciona facilmente Avalanche (AVAX) no mercado à vista da HTX.Acede simplesmente à tua conta, seleciona o teu par de trading, executa as tuas transações e monitoriza em tempo real.Oferecemos uma experiência de fácil utilização tanto para principiantes como para traders experientes.

623 Visualizações TotaisPublicado em {updateTime}Atualizado em 2025.03.21

Como comprar AVAX

Discussões

Bem-vindo à Comunidade HTX. Aqui, pode manter-se informado sobre os mais recentes desenvolvimentos da plataforma e obter acesso a análises profissionais de mercado. As opiniões dos utilizadores sobre o preço de AVAX (AVAX) são apresentadas abaixo.

活动图片