Stacks [STX] finds its floor, but $0.40 is the real test

ambcryptoPublicado em 2026-02-04Última atualização em 2026-02-04

Resumo

Stacks (STX) surged 20.8% in 24 hours, rebounding from a deep retracement after a failed attempt to break a multi-month downtrend earlier in January. The rally was halted at the $0.412 resistance level amid a broader market sell-off. Currently, STX is trading within a range of $0.238 to $0.40, with the $0.32 midpoint and the $0.327–$0.335 supply zone posing significant resistance. While short-term momentum is strong, technical indicators like the DMI and CMF suggest bears remain in control. Traders are advised to wait for a breakout above $0.34 before considering long positions.

Stacks [STX] has rallied an incredible 20.8% in the past 24 hours. It was only up 5.8% in the past week, and its price charts revealed that the recent bounce came after a deep retracement.

STX, like Bitcoin [BTC] and major altcoins, also experienced a rally at the start of 2026.

AMBCrypto reported that this move almost broke a multi-month downtrend, falling just short of the former support level, now turned resistance, at $0.412.

The rejection at this resistance came alongside a wider market sell-off as Bitcoin descended below $84.5k and went as low as $74,600 recently.

The $566 million market cap altcoin has strong short-term momentum, but Stacks buyers have an uphill battle ahead.

Is Stacks trading within a consolidation phase?

The technical indicators showed that STX bears were firmly in control. The DMI showed a strong downtrend in progress on the 1-day timeframe.

The CMF was negative, but not below -0.05, the threshold that analysts use to understand if the capital outflows are significant.

The price action also showed a notable tussle between bears and bulls. The sellers had been dominant since August, but the early January rally shifted this briefly.

Though STX was trading below $0.325 once more, the sustained downtrend has stalled. This idea gained more credibility when you consider the reaction from the $0.237 support level.

What’s next for STX?

The past month’s price action revealed a range formation in play. It extended from $0.238 to $0.40, with the midpoint at $0.32. At the time of writing, STX was headed toward this resistance.

Beyond $0.32, the $0.327-$0.335 supply zone was also a formidable threat to the bulls.

Traders’ call to action – Wait to buy

The liquidation map agreed with the supply zones identified earlier. The $0.34 and $0.40 were also magnetic zones to the price. STX may see a bearish reaction from either level, especially at the month-long range’s high.

Therefore, traders can wait for an STX acceptance beyond $0.34 to buy. Until then, patience is needed.

Final Thoughts

  • Stacks bulls tried and failed to break the multi-month downtrend early in January.
  • The month-long range formation that the current price bounce could continue.

Disclaimer: The information presented does not constitute financial, investment, trading, or other types of advice and is solely the writer’s opinion.

Perguntas relacionadas

QWhat was the percentage increase in Stacks (STX) price in the past 24 hours according to the article?

AStacks (STX) rallied an incredible 20.8% in the past 24 hours.

QWhat is the significant resistance level that STX failed to break in early January?

AThe significant resistance level that STX failed to break was at $0.412, which was a former support level turned resistance.

QBetween which two price levels is STX forming a range formation, as per the article?

ASTX is forming a range formation from $0.238 to $0.40, with the midpoint at $0.32.

QWhat does the article suggest traders should wait for before buying STX?

AThe article suggests traders wait for an STX acceptance beyond the $0.34 level before buying.

QWhat major event in the wider market contributed to the rejection at the $0.412 resistance for STX?

AThe rejection at the $0.412 resistance came alongside a wider market sell-off as Bitcoin descended below $84.5k and went as low as $74,600.

Leituras Relacionadas

CLARITY Act: Banking Trade Groups Push For Yield Agreement Revision – Details

US banking trade groups are urging revisions to the stablecoin yield compromise in the upcoming CLARITY Act ahead of a key committee markup. The Act currently aims to ban all passive, deposit-like interest on stablecoins to prevent competition with traditional bank savings, while allowing rewards tied to active uses like staking or transactions. In a letter, groups including the American Banking Association and Bank Policy Institute proposed stricter language to eliminate perceived loopholes for passive yield and prevent deposit flight from banks. However, these efforts are reportedly viewed as minor by some lawmakers. The Senate Banking Committee is scheduled to mark up the bill on May 14, a critical step before it can advance through Congress.

bitcoinistHá 11h

CLARITY Act: Banking Trade Groups Push For Yield Agreement Revision – Details

bitcoinistHá 11h

This Finance CEO Picks Solana Instead Of Bitcoin — Here’s Why

Finance CEO Raoul Pal prefers Solana over Bitcoin, citing its high throughput and low transaction costs as better suited for the future crypto-AI era. He believes Solana is ideal for machine-to-machine microtransactions and AI-driven DeFi activity, predicting AI agents will soon dominate DeFi users. While Bitcoin serves as a store of value, Pal sees higher growth in networks built for mass, automated transactions. This view was highlighted at Consensus 2026, where AI integration and crypto infrastructure were key themes.

bitcoinistHá 11h

This Finance CEO Picks Solana Instead Of Bitcoin — Here’s Why

bitcoinistHá 11h

Gensyn AI: Don't Let AI Repeat the Mistakes of the Internet

In recent months, the rapid growth of the AI industry has attracted significant talent from the crypto sector. A persistent question among researchers intersecting both fields is whether blockchain can become a foundational part of AI infrastructure. While many previous AI and Crypto projects focused on application layers (like AI Agents, on-chain reasoning, data markets, and compute rentals), few achieved viable commercial models. Gensyn differentiates itself by targeting the most critical and expensive layer of AI: model training. Gensyn aims to organize globally distributed GPU resources into an open AI training network. Developers can submit training tasks, nodes provide computational power, and the network verifies results while distributing incentives. The core issue addressed is not decentralization for its own sake, but the increasing centralization of compute power among tech giants. In the era of large models, access to GPUs (like the H100) has become a decisive bottleneck, dictating the pace of AI development. Major AI companies are heavily dependent on large cloud providers for compute resources. Gensyn's approach is significant for several reasons: 1) It operates at the core infrastructure layer (model training), the most resource-intensive and technically demanding part of the AI value chain. 2) It proposes a more open, collaborative model for compute, potentially increasing resource utilization by dynamically pooling idle GPUs, similar to early cloud computing logic. 3) Its technical moat lies in solving complex challenges like verifying training results, ensuring node honesty, and maintaining reliability in a distributed environment—making it more of a deep-tech infrastructure company. 4) It targets a validated, high-growth market with genuine demand, rather than pursuing blockchain integration without purpose. Ultimately, the boundaries between Crypto and AI are blurring. AI requires global resource coordination, incentive mechanisms, and collaborative systems—areas where crypto-native solutions excel. Gensyn represents a step toward making advanced training capabilities more accessible and collaborative, moving beyond a niche controlled by a few giants. If successful, it could evolve into a fundamental piece of AI infrastructure, where the most enduring value in the AI era is often created.

marsbitHá 12h

Gensyn AI: Don't Let AI Repeat the Mistakes of the Internet

marsbitHá 12h

Why is China's AI Developing So Fast? The Answer Lies Inside the Labs

A US researcher's visit to China's top AI labs reveals distinct cultural and organizational factors driving China's rapid AI development. While talent, data, and compute are similar to the West, Chinese labs excel through a pragmatic, execution-focused culture: less emphasis on individual stardom and conceptual debate, and more on teamwork, engineering optimization, and mastering the full tech stack. A key advantage is the integration of young students and researchers who approach model-building with fresh perspectives and low ego, prioritizing collective progress over personal credit. This contrasts with the US culture of self-promotion and "star scientist" narratives. Chinese labs also exhibit a strong "build, don't buy" mentality, preferring to develop core capabilities—like data pipelines and environments—in-house rather than relying on external services. The ecosystem feels more collaborative than tribal, with mutual respect among labs. While government support exists, its scale is unclear, and technical decisions appear driven by labs, not state mandates. Chinese companies across sectors, from platforms to consumer tech, are building their own foundational models to control their tech destiny, reflecting a broader cultural drive for technological sovereignty. Demand for AI is emerging, with spending patterns potentially mirroring cloud infrastructure more than traditional SaaS. Despite challenges like a less mature data industry and GPU shortages, Chinese labs are propelled by vast talent, rapid iteration, and deep integration with the open-source community. The competition is evolving beyond a pure model race into a contest of organizational execution, developer ecosystems, and industrial pragmatism.

marsbitHá 13h

Why is China's AI Developing So Fast? The Answer Lies Inside the Labs

marsbitHá 13h

3 Years, 5 Times: The Rebirth of a Century-Old Glass Factory

Corning, a 175-year-old glass company, is experiencing a dramatic revival as a key player in AI infrastructure, driven by surging demand for high-performance optical fiber in data centers. AI data centers require vastly more fiber than traditional ones—5 to 10 times as much per rack—to handle high-speed data transmission between GPUs. This structural demand shift, coupled with supply constraints from the lengthy expansion cycle for fiber preforms, has created a significant supply-demand gap. Nvidia has invested in Corning, along with Lumentum and Coherent, in a $4.5 billion total commitment to secure the optical supply chain for AI. Corning's competitive edge lies in its expertise in producing ultra-low-loss, high-density, and bend-resistant specialty fiber, which is critical for 800G+ and future 1.6T data rates. Its deep involvement in co-packaged optics (CPO) with partners like Nvidia further solidifies its position. While not the largest fiber manufacturer globally, Corning's revenue from enterprise/data center clients now exceeds 40% of its optical communications sales, and it has secured multi-year supply agreements with major hyperscalers including Meta and Nvidia. Financially, Corning's optical communications revenue has surged, doubling from $1.3 billion in 2023 to over $3 billion in 2025. Its stock price has risen nearly 6-fold since late 2023. Key future catalysts include the rollout of Nvidia's CPO products and the scale of undisclosed customer agreements. However, risks include high current valuations and potential disruption from next-generation technologies like hollow-core fiber. The company's long-term bet on light over electricity, maintained even through the telecom bubble crash, is now being validated by the AI boom.

marsbitHá 14h

3 Years, 5 Times: The Rebirth of a Century-Old Glass Factory

marsbitHá 14h

Trading

Spot
Futuros
活动图片

Categorias popularesright-arrow

Etiquetas Popularesright-arrow