Zcash (ZEC) Jumps 12%: Can the Momentum Fuel a Bigger Weekly Run?

TheNewsCryptoPublicado a 2026-03-17Actualizado a 2026-03-17

Resumen

Zcash (ZEC) surged 12.51% amid a $25 million funding boost, signaling strong investor confidence and development support. Trading at $266.43, its market cap reached $4.42 billion, while daily trading volume spiked 72.59% to $721.17 million. Technical indicators show bullish momentum, with the MACD line above the signal line and a CMF of 0.13 indicating buying pressure. However, the RSI of 73.15 suggests overbought conditions, hinting at a potential pullback. If momentum holds, ZEC could target $282.56; a reversal may see it test support at $258.31 or lower.

The trigger behind the Zcash (ZEC) rally might be the $25M funding that happened a few days back, which boosts confidence in development. It also signals strong investor confidence in the growing worldwide adoption. After certain corrections from its previous highs, the asset is currently trading on the upside, with a 12.51% jump.

At the time of writing, Zcash is trading within the $266.43 range, and the market cap is resting at around $4.42 billion. Besides, the daily trading volume of ZEC has increased by over 72.59%, reaching the $721.17 million mark, as reported by CoinMarketCap.

Zooming in on the 4-hour chart of the ZEC/USDT trading pair, the bulls are in control, taking the price to hit a resistance at around $274.38. Further pressure on the upside may trigger the golden cross to unfold, and the potent bulls would send the asset’s price up above $282.56.

Conversely, if the Zcash momentum reverses, the price might immediately retrace and find the nearest support level at $258.31. An extended downside correction could initiate the emergence of the death cross, and likely, the mighty bears will drive the price even lower, below $250.

Zcash Indicators Turn Bullish: Can the Momentum Hold?

The technical analysis reports that the MACD line is above the signal line, a sign that bullish momentum is building. Notably, Zcash’s price movement is getting stronger, and if the gap between the lines keeps widening, the uptrend gains more strength.

Moreover, the CMF indicator of ZEC is at 0.13, showing moderate buying pressure. Notably, the money is flowing into the asset rather than out, with the buyers actively supporting the price action. It reflects steady accumulation and positive sentiment.

Zcash’s daily RSI of 73.15 indicates its overbought condition. The price has risen strongly, with buyers firmly in control. Also, the momentum might continue to move higher if the trend stays strong, but there is a higher chance of a small pullback.

Furthermore, the BBP reading of 45.07 suggests very strong bullish dominance in the ZEC market. Significantly, it hints at an upward momentum and strong demand. Such a high value supports a strong uptrend, though the move can get stretched.

At press time, the market sentiment of the altcoin points toward the bullish side. If the surge is sustained and gains more strength, it may hit all the crucial recent highs. With the bears entering the Zcash market, the price would slip back. For a clearer future trajectory, explore our comprehensive outlook, providing a detailed price forecast for Zcash (ZEC) 2026, 2027, and going through 2030.

Top Updated Crypto News

Crypto Market Shows Gains as US Diesel and Gasoline Prices Rise

Preguntas relacionadas

QWhat was the main trigger behind the recent Zcash (ZEC) price rally according to the article?

AThe main trigger behind the Zcash (ZEC) rally was the $25 million funding that happened a few days back, which boosted confidence in development and signaled strong investor confidence.

QWhat are the current key price levels for ZEC, including its resistance and nearest support?

AAt the time of writing, ZEC was trading around $266.43. The nearest resistance level is at $274.38, and the immediate support level is at $258.31.

QWhat does the MACD indicator being above the signal line signify for Zcash's momentum?

AThe MACD line being above the signal line is a sign that bullish momentum is building for Zcash.

QWhat does the daily RSI value of 73.15 indicate about ZEC's market condition?

AA daily RSI of 73.15 indicates that ZEC is in an overbought condition, suggesting the price has risen strongly with buyers in control, but also implying a higher chance of a small pullback.

QWhat is the significance of the Bull Bear Power (BBP) reading of 45.07 for ZEC?

AA BBP reading of 45.07 suggests very strong bullish dominance in the ZEC market, hinting at upward momentum and strong demand, which supports a strong uptrend.

Lecturas Relacionadas

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.

marsbitHace 1 min(s)

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

marsbitHace 1 min(s)

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Hace 25 min(s)

Claude Opus 4.8 Finds a $4.5 Billion Bug: The AI Era is Mass-Producing Hackers

A researcher discovered a critical "infinite mint" vulnerability in the Zcash cryptocurrency's Orchard protocol using Claude Opus 4.8, leading to a swift fix but also a 50% market drop, erasing billions in value. This incident highlights a new era where powerful, accessible AI models are dramatically lowering the barrier to finding software vulnerabilities. Previously, the security community feared specialized models like Claude Mythos Preview, capable of finding decades-old zero-day exploits. The Zcash case, however, involved a publicly available, general-purpose model. This shift makes advanced security auditing—and attack capabilities—accessible to far more people, not just experts. The mass democratization of vulnerability discovery brings a dual challenge: a flood of low-quality, AI-generated false reports that overwhelm maintainers, and the real, rapid uncovering of deep, dangerous bugs. Open-source projects, often understaffed and unfunded, are particularly vulnerable to this "attention DDoS." The article cites examples like curl shutting down its bug bounty program due to the unsustainable workload. Our perceived digital safety has often been luck, relying on the high cost and effort required to find deeply hidden flaws in complex systems, as seen with historical vulnerabilities like Heartbleed or Baron Samedit. AI changes this cost structure, effectively "mass-producing flashlights" to illuminate every corner of our codebase. While large companies operate extensive security chains involving external white-hat hackers and massive defensive operations, the global cybersecurity workforce faces a severe shortage, especially of experienced personnel capable of analyzing complex threats and coordinating fixes. The core dilemma emerges: AI makes *finding* bugs cheap and scalable, but *fixing* them remains a slow, expensive, and human-intensive process. The article concludes that AI won't destroy the internet but acts as a bright light, revealing that our digital existence is not inherently secure but is precariously maintained by ongoing human effort. The true cost in the AI era may not be discovery, but whether there will be enough people left willing and able to do the hard work of repair.

marsbitHace 58 min(s)

Claude Opus 4.8 Finds a $4.5 Billion Bug: The AI Era is Mass-Producing Hackers

marsbitHace 58 min(s)

Ethereum Price Prediction: ETH Could Double While Cardano (ADA) and This Newcomer Token Near 500% Rally

As the cryptocurrency market anticipates a potential bull cycle, investor focus is shifting toward projects with high return potential. Ethereum (ETH), currently at approximately $2,014, is highlighted for its long-term value, with predictions suggesting a possible 2x increase to over $4,000. Cardano (ADA), trading around $0.2329, remains a choice for its research-driven development and scalability focus, though some seek higher upside elsewhere. Significant attention is drawn to Little Pepe (LILPEPE), a new Layer 2 Ethereum-compatible token priced at $0.0022 in its presale stage, which has raised over $28.19 million. The project aims to build a dedicated blockchain for meme communities, offering lower costs and faster transactions. Backers speculate a potential 500% gain, driven by strong presale demand, planned ecosystem features like staking and a launchpad, and active community engagement through giveaways. While Ethereum and Cardano are viewed as foundational investments, LILPEPE represents a newer, high-growth opportunity for investors targeting the meme coin sector.

TheNewsCryptoHace 1 hora(s)

Ethereum Price Prediction: ETH Could Double While Cardano (ADA) and This Newcomer Token Near 500% Rally

TheNewsCryptoHace 1 hora(s)

Codex Goal Mode Usage Guide: How to Make AI Continuously Pursue a Specific Objective

"Codex Goal Mode: How to Make AI Work Continuously Toward a Specific Goal" OpenAI's Codex "goal mode" (/goal) transforms the AI from a reactive code assistant into a proactive execution agent capable of working autonomously for hours or even days to achieve a defined objective. To maximize its effectiveness, follow these key principles: 1. **Define Clear, Verifiable Exit Criteria:** The goal prompt should be a concise, measurable success condition, not a lengthy specification. Use quantifiable metrics like "reduce build time by 30%" or "achieve 100% test parity." 2. **Provide Initial Guidance and Tools:** Direct Codex toward likely problem areas and specify available tools (e.g., browsers, testing environments) to prevent it from exploring unproductive paths. 3. **Enable Progress Measurement:** Equip Codex with ways to track advancement, such as creating comparison tools for visual tasks or evaluation sets, ensuring it can gauge its own progress. 4. **Use a Realistic Execution Environment:** For tasks like performance optimization, provide access to environments that closely mimic production (e.g., similar configs, databases) to yield valid results. 5. **Be Cautious with Visual Goals:** Avoid vague "pixel-perfect" instructions. Instead, supplement visual references with functional checklists or design system specifications to prevent Codex from obsessing over minor details. 6. **Implement Progress Tracking:** For long-running tasks, have Codex commit code to draft PRs, update progress documents, or send Slack updates to maintain visibility into its work. 7. **Review and Consolidate Results:** Once the goal is met, instruct Codex to review its work, clean up ineffective experimental code, and reflect on what strategies succeeded or failed. Ultimately, using goal mode shifts the developer's role from writing prompts to managing a persistent engineering agent—defining objectives, establishing metrics, configuring environments, and conducting final reviews.

marsbitHace 2 hora(s)

Codex Goal Mode Usage Guide: How to Make AI Continuously Pursue a Specific Objective

marsbitHace 2 hora(s)

Trading

Spot

Futuros

Artículos destacados

Cómo comprar ZEC

¡Bienvenido a HTX.com! Hemos hecho que comprar Zcash (ZEC) sea simple y conveniente. Sigue nuestra guía paso a paso para iniciar tu viaje de criptos.Paso 1: crea tu cuenta HTXUtiliza tu correo electrónico o número de teléfono para registrarte y obtener una cuenta gratuita en HTX. Experimenta un proceso de registro sin complicaciones y desbloquea todas las funciones.Obtener mi cuentaPaso 2: ve a Comprar cripto y elige tu método de pagoTarjeta de crédito/débito: usa tu Visa o Mastercard para comprar Zcash (ZEC) al instante.Saldo: utiliza fondos del saldo de tu cuenta HTX para tradear sin problemas.Terceros: hemos agregado métodos de pago populares como Google Pay y Apple Pay para mejorar la comodidad.P2P: tradear directamente con otros usuarios en HTX.Over-the-Counter (OTC): ofrecemos servicios personalizados y tipos de cambio competitivos para los traders.Paso 3: guarda tu Zcash (ZEC)Después de comprar tu Zcash (ZEC), guárdalo en tu cuenta HTX. Alternativamente, puedes enviarlo a otro lugar mediante transferencia blockchain o utilizarlo para tradear otras criptomonedas.Paso 4: tradear Zcash (ZEC)Tradear fácilmente con Zcash (ZEC) en HTX's mercado spot. Simplemente accede a tu cuenta, selecciona tu par de trading, ejecuta tus trades y monitorea en tiempo real. Ofrecemos una experiencia fácil de usar tanto para principiantes como para traders experimentados.

346 Vistas totalesPublicado en 2024.12.12Actualizado en 2026.06.02

Discusiones

Bienvenido a la comunidad de HTX. Aquí puedes mantenerte informado sobre los últimos desarrollos de la plataforma y acceder a análisis profesionales del mercado. A continuación se presentan las opiniones de los usuarios sobre el precio de ZEC (ZEC).