Analyst Says The Real XRP Move Hasn’t Happened Yet, What To Expect

bitcoinistPublished on 2026-04-10Last updated on 2026-04-10

Abstract

Crypto analyst CasiTrades suggests that XRP's recent surge to $1.39 was not a true bullish move but rather the completion of a corrective Wave 2 within an Elliott Wave structure. This bounce, which reached the 0.618 Fibonacci retracement level, failed to break higher and has set the stage for a stronger downward Wave 3 impulse. The analyst predicts a decline toward $1.09, followed by a potential bounce to $1.20, and possibly further drops to $0.862 if bearish momentum continues. Key factors that could influence this outlook include the upcoming CLARITY Act markup and developments in the Iran ceasefire situation.

XRP’s brief surge on Tuesday was no cause for celebration, at least not according to crypto analyst CasiTrades. Recent price action pushed the cryptocurrency as high as $1.39, creating what looks like a temporary rally. However, one analyst believes the real move hasn’t happened yet, and the current price action is merely preparing for a bigger downward push that could catch traders off guard.

Clean Wave Structure Points To A Larger Move Brewing

The XRP price climbed as high as $1.39 on April 8 as a Pakistan-brokered ceasefire between the US and Iran led to a wave of short liquidations across the crypto market, and sentiment changed from extreme fear to cautious neutral optimism.

But crypto analyst CasiTrades, who has been tracking XRP’s wave structure, saw something different in the price action. The bounce, she says, was exactly what the chart needed to complete a corrective structure. Now, the real move is set to begin.

According to CasiTrades, the recent XRP price bounce in XRP was the completion of a corrective phase. The move into the 0.618 Fibonacci retracement level, which is visible on the chart around the $1.35 to $1.40 range, helped confirm what she identifies as a clean Wave 2 in an Elliott Wave structure.

This move completed the counter-trend move without breaking the broader bearish count. Despite the strength of the bounce, it failed to break above these Fibonacci levels, and XRP is now back to trading at $1.32. Therefore, the next projected move is a Wave 3 impulse that continues the correction.

What The Chart Is Saying

CasiTrades’ analysis lays out a five-wave impulsive decline playing out on the one-hour timeframe. According to her count, XRP had already completed Wave 1 down and Wave 2 up by the time the ceasefire bounce peaked. With Wave 2 now likely completed, attention turns to what typically follows in Elliott Wave theory: Wave 3, which is the strongest and fastest move in the sequence.

The target for Wave 3’s conclusion is somewhere around $1.09, and this corresponds to a 0.618 Fibonacci retracement level. A fourth-wave bounce to $1.20 is expected next. After that, a fifth-wave continuation could follow, with the 0.786 extension at $1.0854 and the 0.854 extension at $0.862 serving as deeper structural targets if the move plays out fully.

The current macro environment offers few bullish factors that can negate the bearish outlook. The two bullish factors are the CLARITY Act markup, which is scheduled for the second half of April, and any progress on the Iran ceasefire. However, if the CLARITY Act stalls and the war drags on, XRP’s $1.30 support could break, and the price could fall lower.

XRP trading at $1.34 on the 1D chart | Source: XRPUSDT on Tradingview.com

Trending Cryptos

Related Questions

QAccording to analyst CasiTrades, what was the significance of XRP's recent price bounce to the $1.35-$1.40 range?

AIt was the completion of a corrective phase, specifically a Wave 2 in the Elliott Wave structure, which confirmed the counter-trend move without breaking the broader bearish count.

QWhat is the next projected move for XRP after the completion of Wave 2, according to the Elliott Wave analysis?

AThe next projected move is a Wave 3 impulse, which is typically the strongest and fastest move in the sequence, expected to continue the correction downward.

QWhat are the two key bullish factors mentioned in the article that could potentially negate the bearish outlook for XRP?

AThe two key bullish factors are the CLARITY Act markup scheduled for the second half of April and any progress on the Iran ceasefire.

QWhat price level is given as the target for the conclusion of the projected Wave 3 decline?

AThe target for the conclusion of Wave 3 is around $1.09, which corresponds to a 0.618 Fibonacci retracement level.

QWhat event on April 8th was cited as the catalyst for XRP's brief surge and a wave of short liquidations across the crypto market?

AA Pakistan-brokered ceasefire between the US and Iran was the catalyst that led to the surge and short liquidations.

Related Reads

Anthropic Creates an AI Jailbreak 'Penal Code': Your Requests, Four Ways to Die

Anthropic has publicly detailed its security measures and a new "Cyber Jailbreak Severity" (CJS) framework following the controversial takedown of its Fable 5 model. The incident, triggered by simple user requests like counting letters or stating a profession, highlighted overzealous safety filters. Anthropic classifies cybersecurity-related prompts into four tiers: malicious activities (blocked), high-risk dual-use (like pentesting, with strict limits), low-risk dual-use (often blocked by "safety margin" errors), and harmless tasks (theoretically allowed but still frequently flagged). The company admits its classifiers are tuned for high sensitivity, leading to many false positives. The newly proposed CJS framework aims to objectively score the severity of AI "jailbreaks" (prompts that bypass safety rules) on a 0-10 scale across four dimensions: Capability Gain (does it grant new attack abilities?), Breadth (does it work across multiple attack types?), Weaponization Ease (how hard is it to turn into a real attack?), and Discoverability (how easy is it to find?). The score determines the response, from no action (CJS-0) to a potential model takedown (CJS-4). The score is context-dependent; for example, discovering a major unknown vulnerability today scores high, while asking about a well-known one scores low. The article raises concerns about Anthropic's dual role: it is both creating powerful models (like the restricted Mythos 5) and defining the rules (CJS) for judging their misuse, potentially giving it disproportionate influence. This is set against the backdrop of U.S. export controls, which for the first time directly restricted API access to a model (Fable 5), creating a "tiered" system where public models are heavily filtered and advanced ones are limited to vetted partners. The CJS framework is portrayed as potentially providing regulators with a metric to justify future API shutdowns. For users, the advice is to carefully phrase prompts, watch for signs of being downgraded to a weaker model, and wait indefinitely for promised filter improvements.

marsbit17m ago

Anthropic Creates an AI Jailbreak 'Penal Code': Your Requests, Four Ways to Die

marsbit17m ago

$100M Annual Revenue, Two Berkeley Roommates in Their 20s Build the Most Profitable AI Business

Arena, the AI model ranking platform, has become a $100 million annual revenue business just eight months after launching its commercial service. Originally a UC Berkeley open-source research project called Chatbot Arena, it created a "battle arena" where users blind-test and vote on anonymous AI model responses. This has generated a highly trusted, community-driven leaderboard based on over 10 million user evaluations and 82 million votes. Major AI companies like OpenAI, Google, and Anthropic submit their flagship models to be ranked. The core monetization strategy is its AI Evaluations service, where model developers and large enterprises pay for in-depth performance analysis from Arena's massive user community. This provides real-world feedback on model strengths, weaknesses, and hallucinations—a critical service as models become more complex. The company, spun out from Berkeley in early 2025, quickly raised $100 million in seed funding at a $600 million valuation and later secured a $150 million Series A at a $1.7 billion valuation. The founding team includes CEO Anastasios Angelopoulos, a mathematician focused on rigorous model evaluation; CTO Wei-Lin Chiang, creator of the popular Vicuna chatbot; and co-founder Ion Stoica, a renowned Berkeley professor. Arena is now expanding beyond chat benchmarks into "Agent Mode," evaluating AI agents on complex, multi-step tasks like coding and research. The company's success illustrates the growing value and cost of independent, real-world AI model evaluation as the industry intensifies.

marsbit21m ago

$100M Annual Revenue, Two Berkeley Roommates in Their 20s Build the Most Profitable AI Business

marsbit21m ago

Racking Up 24,000 Stars: With One Command, AI Can Now Find Its Own Skills

Vercel, known for its developer tools like Next.js, has launched 'skills', a package manager for AI coding agents, garnering 24,000 GitHub stars. It allows developers to add specialized capabilities, such as React best practices, to AI assistants like Claude Code or Cursor with a single command: `npx skills add <package>`. Skills are shareable, reusable modules that define an AI agent's behavior for specific tasks, moving beyond one-off prompt engineering towards standardized 'capability engineering'. A key innovation is the 'find-skills' skill, which acts as an internal search engine, allowing an agent to autonomously find and install the right skill for a user's request. This lowers the barrier for non-developers to leverage advanced AI coding assistance. However, this 'npm moment' for AI brings significant security risks. Security audits of thousands of skills on platforms like skills.sh and ClawHub found over 30% contained security flaws, with about 13% classified as severe. Threats include malicious scripts that can access local files and credentials, and prompt injection hidden within skill documentation. Unlike traditional code packages, skills blend instructions, code, and system access, posing a direct risk to user machines and data. Experts advise treating skills like code—reviewing them carefully before installation, especially their scripts, and being wary of excessive permissions. Ultimately, Vercel's initiative represents a major shift towards modular, reusable AI capabilities, but its rapid adoption requires developers to bring the same caution used in managing traditional software dependencies.

marsbit22m ago

Racking Up 24,000 Stars: With One Command, AI Can Now Find Its Own Skills

marsbit22m ago

Claude Engineer Finally Unveils Fable 5's Ultimate Strategy, Teaching You How to Bridge the Information Gap with AI Models

This article, titled "Claude Engineer Finally Releases Fable 5 'Skill-Burning' Guide, Teaching How to Bridge the Information Gap with Models," details a blog post by Claude Code engineer Thariq Shihipar. The core concept is the "information gap" or "unknowns"—the disconnect between a user's instructions (the "map") and the actual task requirements (the "territory"). The article argues that with powerful models like Claude Fable 5, work quality depends on the user's ability to identify and clarify these unknowns. Shihipar categorizes unknowns into four types: Known Knowns (explicit instructions), Known Unknowns (awareness of gaps), Unknown Knowns (implicit, unstated knowledge), and Unknown Unknowns (unforeseen issues). The blog provides a framework for addressing these gaps throughout the workflow: * **Before Implementation:** Techniques include "Blindspot Scanning" to uncover Unknown Unknowns, brainstorming/prototyping for visual or complex tasks, having Claude ask clarifying questions, using reference code/examples, and creating implementation plans. * **During Implementation:** Maintaining an "implementation notes" file for Claude to document deviations and decisions made due to encountered edge cases. * **After Implementation:** Creating summary documents for review and having Claude generate quizzes to ensure the user fully understands the completed changes. The article concludes that as models become more capable, the key to success is systematically discovering and defining these unknowns through low-cost methods like prototyping and planning, allowing for more effective collaboration.

marsbit26m ago

Claude Engineer Finally Unveils Fable 5's Ultimate Strategy, Teaching You How to Bridge the Information Gap with AI Models

marsbit26m ago

Trading

Spot

Hot Articles

How to Buy T

Welcome to HTX.com! We've made purchasing Threshold Network Token (T) simple and convenient. Follow our step-by-step guide to embark on your crypto journey.Step 1: Create Your HTX AccountUse your email or phone number to sign up for a free account on HTX. Experience a hassle-free registration journey and unlock all features.Get My AccountStep 2: Go to Buy Crypto and Choose Your Payment MethodCredit/Debit Card: Use your Visa or Mastercard to buy Threshold Network Token (T) instantly.Balance: Use funds from your HTX account balance to trade seamlessly.Third Parties: We've added popular payment methods such as Google Pay and Apple Pay to enhance convenience.P2P: Trade directly with other users on HTX.Over-the-Counter (OTC): We offer tailor-made services and competitive exchange rates for traders.Step 3: Store Your Threshold Network Token (T)After purchasing your Threshold Network Token (T), store it in your HTX account. Alternatively, you can send it elsewhere via blockchain transfer or use it to trade other cryptocurrencies.Step 4: Trade Threshold Network Token (T)Easily trade Threshold Network Token (T) on HTX's spot market. Simply access your account, select your trading pair, execute your trades, and monitor in real-time. We offer a user-friendly experience for both beginners and seasoned traders.

12.3k Total ViewsPublished 2024.03.29Updated 2026.06.02

How to Buy T

Discussions

Welcome to the HTX Community. Here, you can stay informed about the latest platform developments and gain access to professional market insights. Users' opinions on the price of T (T) are presented below.

活动图片