TRUMP slips to key levels – The memecoin eyes $9.70 support next

ambcryptoPublished on 2025-07-23Last updated on 2025-07-25

Key Takeaways

Traders and investors have shown mixed sentiment on TRUMP, with some appearing to take short positions, while others are actively accumulating.


Amid this market correction, the Official Trump [TRUMP] memecoin dropped to a key level of $9.70. This may have occurred due to the overall market structure, which has now shifted into a correction phase.

Along with this, another major reason behind the decline is the rising Bitcoin [BTC] dominance, which has continued to increase over the past three days.

In the crypto landscape, when Bitcoin dominance rises, it indicates that interest in altcoins is potentially fading, which may lead to a price dip across altcoins.

Justin Sun’s bullish update

At press time, the TRUMP memecoin traded near $9.75, having dropped by over 10.85% in the past 24 hours.

During this period, traders and investors have shown strong interest in the token, resulting in a 30% increase in trading volume compared to the previous day.

This surge in trading volume, along with the sinking price, indicates strong bearish momentum. However, crypto billionaire and Tron [TRX] founder Justin Sun attempted to offset the negativity with a bullish update.

On the 24th of July, Sun shared a post on X (formerly Twitter) announcing that the TRUMP memecoin has officially landed on Tron.

He stated,

“All roads lead to TRON.”

This isn’t just a statement, it’s a clear sign of Tron’s intent to globalize TRUMP.

However, the sentiment remains unchanged, with the price of TRUMP is still hovering around a key level.

Technical analysis and key levels 

AMBCrypto’s technical analysis suggests caution, as the memecoin’s price approaching an area of convergence at the time of writing.

Horizontal support at $9.70 and an ascending trendline support met on the four-hour chart.

TRUMP technical analysisTRUMP technical analysis

Source: TradingView

If the bearish market structure remains intact and TRUMP falls below the $9.65 level, a further price drop of 12.50% could be likely, potentially taking the memecoin down to the $8.50 level.

However, the price is currently showing signs of a reversal. If it holds above the $9.70 level, an upside rally could follow.

Also, Relative Strength Index (RSI) appears to be supporting the reversal, as it stands at 35, near the oversold territory, a level that often signals a potential trend reversal.

Amid this uncertainty, investors seem to be taking advantage of the price dip and appear to be accumulating, as revealed by CoinGlass data.

TRUMP Spot Inflow/OutflowTRUMP Spot Inflow/Outflow

Source: CoinGlass

However, traders remain bearish in this environment, as the TRUMP Long/Short Ratio remained at 0.91.

Share

Related Reads

Li Fei-Fei's Latest Long-Form Article: When Video Generation, Robotics, and NVIDIA All Call Themselves World Models, We Need a Taxonomy

In a new article, Dr. Fei-Fei Li addresses the widespread and often inconsistent use of the term "world model" in AI. She proposes a clear, functional taxonomy rooted in the classic Partially Observable Markov Decision Process (POMDP) loop (agent → action → state → observation → agent). According to this framework, current systems called "world models" are different projections of this loop, categorized by their primary output: 1. **Renderers**: Output observations (pixels). Their goal is visual fidelity for human consumption (e.g., video generation models like Sora). They are the most commercially mature but are limited by a focus on appearance over physical accuracy. 2. **Simulators**: Output states (geometric, physical, dynamic representations). They provide a structurally accurate world for both human professionals (e.g., architects) and computational agents (e.g., robots for training). Li argues simulators are the crucial, underappreciated bridge, as they can underpin both rendering and planning. 3. **Planners**: Output actions. Given an observation and a goal, they decide what an agent should do next (e.g., robotic action models). This area is highly promising but remains the least mature for real-world deployment. Li highlights a key trend: the boundaries between these three categories are beginning to blur, as they all rely on a shared underlying understanding of geometry, physics, and dynamics. The logical endpoint is a unified world foundation model capable of switching between rendering, simulation, and planning based on downstream needs. This convergence, she concludes, is central to advancing spatial intelligence—enabling machines not just to talk about the world, but to truly understand, imagine, and interact with it.

marsbit45m ago

Li Fei-Fei's Latest Long-Form Article: When Video Generation, Robotics, and NVIDIA All Call Themselves World Models, We Need a Taxonomy

marsbit45m ago

Forbes Feature: Stablecoin Cross-Border Payments Are Faster, But Not Yet Cheaper

A Forbes feature delves into the state of stablecoin-based cross-border payments, noting rapid growth but a key shortfall: while faster and more accessible, they are not yet cheaper. At a recent industry conference in Mexico City, optimism about technology, regulation, and volume was tempered by discussions with practitioners. The core issue is liquidity. Traditional FX brokers charge 60-70 basis points, and stablecoins promise to slash this to 2-5 basis points. However, this theoretical cost advantage cannot be realized until deep liquidity pools are established at scale, requiring significant institutional capital inflow. A major adoption barrier is trust. Businesses often rely on long-standing relationships with traditional brokers, valuing reliability over marginal cost savings. This shift will be gradual. Furthermore, successful companies in the space are not positioning themselves as replacements for legacy systems like SWIFT, but as complements. They leverage stablecoins for speed while using traditional rails for their standardization and reliability in ensuring accurate payment details—a critical factor for supplier payments to avoid customs issues. Companies like Caliza, experiencing high monthly growth, exemplify this hybrid approach. The industry anticipates consolidation, as long-term viability will depend on securing the essential trifecta: proper licensing, robust fiat on/off-ramps, and deep liquidity. Without these, firms risk being mere intermediaries rather than building sustainable businesses.

marsbit46m ago

Forbes Feature: Stablecoin Cross-Border Payments Are Faster, But Not Yet Cheaper

marsbit46m ago

Li Feifei's Latest Article: When Video Generation, Robotics, and NVIDIA All Claim to Have 'World Models,' We Need a Taxonomy

"World Model" has become a widely used yet ambiguous term in AI. Drawing from the classic POMDP framework (agent → action → state → observation), this article proposes a functional taxonomy to clarify the concept. It identifies three distinct types, categorized by their output in the perception-action loop: 1. **Renderers**: Output visual observations (pixels). These models, like advanced video generators, prioritize visual fidelity but often lack underlying physical accuracy. 2. **Simulators**: Output the state of the world (geometry, physics, dynamics). They provide a structurally accurate representation for professionals (e.g., architects) and serve as training environments for robots and AI agents. 3. **Planners**: Output actions. Given an observation and a goal, they determine what an agent should do next, closing the perception-action loop (e.g., vision-language-action models). While renderers are currently the most commercially mature and planners are the most aspirational, the article argues that **simulators are the crucial, underappreciated hub**. By working at the level of geometry and physics, a simulator can project upwards to create visuals for humans and downwards to predict action consequences for agents. The future lies in the convergence of these three functions. Emerging research and products, like World Labs' Marble model which outputs both visual splats and physical collision meshes, are beginning to blur these boundaries. The logical endpoint is a unified world foundation model capable of rendering, simulating, and planning based on a shared understanding of spatial and temporal structures—ultimately enabling machines to understand, imagine, and interact with the physical world.

链捕手57m ago

Li Feifei's Latest Article: When Video Generation, Robotics, and NVIDIA All Claim to Have 'World Models,' We Need a Taxonomy

链捕手57m ago

Trading

Spot
活动图片