XRP Price Crash Could Deepen As Bearish Formations Gather

bitcoinistPublicado em 2025-08-04Última atualização em 2025-08-04

Resumo

Over the weekend, the XRP price crashed further and ultimately declined below the $3 support level. This has put it...

Trusted Editorial content, reviewed by leading industry experts and seasoned editors. Ad Disclosure

Over the weekend, the XRP price crashed further and ultimately declined below the $3 support level. This has put it on the path for possible losses as the current downtrend could continue to deepen. At the same time, there have also been a number of bearish formations that have emerged for the altcoin during this time. As the bearish formations pile up and sell-offs continue to be the order of the day, analysts have warned that the XRP price could be poised to crash further.

XRP Price Could Drop To The Bottom Of The Channel

According to crypto analyst CobraVanguard, there is the possibility that the XRP price could see a rapid decline to the bottom of the current channel. This comes as the altcoin is at risk of declining into the PRZ range, outlined by the chart shared by the crypto analyst on the TradingView website.

This PRZ range lies at the $2.8 level, meaning that the altcoin is dangerously close to actually falling below this point. At this level, there is the possibility that two things could happen. The first being that the bulls are able to maintain the momentum at this point and then trigger a bounce. In which case, the bearish thesis could be invalidated and the XRP price could begin the next wave of the uptrend.

However, there is a high probability that the XRP price will fall below this PRZ range, opening a path for bears to take control. This would mean a complete destruction of the support at $2.8, leading the cryptocurrency to fall to the bottom of the channel and putting it as low as $0.26 before the downtrend is over.

XRP Price
Source: TradingView.com

Descending Triangle Supports The Bears

Another crypto analyst who goes by KooksooTrade on the TradingView website has also lent their voice and warned that XRP could be facing a possible decline. The analyst points out the formation of a bearish descending triangle, whose possible break could trigger the next wave of losses.

As they explain, the XRP price has already broken down the neckline, and that is why the price has continued to decline. Following this trend, the crypto analyst explains that the bottom is not in and expects the altcoin to drawdown further to the $2.45-$2.5 range before the descent is over.

XRP Price 2
Source: TradingView.com

Analyst SwallowAcademy corroborates this formation in a response to the analysis, confirming that it is indeed a classic bearish pattern. Pointing to the neckline breakdown, they explain that this is indeed a strong signal suggesting that there could be more decline. However, unlike KooksooTrade, SwallowAcademy does expect the price to fall below the $2.45-$2.5 range before there is a bounce.

XRP price chart from TradingView.com
Price reverses as dumping slows | Source: XRPUSDT on TradingView.com
Featured image from Dall.E, chart from TradingView.com
Editorial Process for bitcoinist is centered on delivering thoroughly researched, accurate, and unbiased content. We uphold strict sourcing standards, and each page undergoes diligent review by our team of top technology experts and seasoned editors. This process ensures the integrity, relevance, and value of our content for our readers.

Scott Matherson is a leading crypto writer at Bitcoinist, who possesses a sharp analytical mind and a deep understanding of the digital currency landscape. Scott has earned a reputation for delivering thought-provoking and well-researched articles that resonate with both newcomers and seasoned crypto enthusiasts. Outside of his writing, Scott is passionate about promoting crypto literacy and often works to educate the public on the potential of blockchain.

Leituras Relacionadas

When US Giants Collectively "Defect" to Chinese AI Models

When Silicon Valley Giants Turn to Chinese AI Models to Cut Costs A surprising trend is emerging: major U.S. tech companies are significantly reducing AI costs by switching to Chinese models. Coinbase, the largest U.S. cryptocurrency exchange, reportedly halved its AI spending after migrating to China's GLM-5.2 and Kimi 2.7 models, despite increasing usage. They achieved this through a sophisticated three-part strategy: implementing an automatic routing system to select the most cost-effective model per task, boosting cache hit rates from 5% to 60% to reuse computations, and employing "context engineering" to provide AI with more precise, less cluttered information. They are not alone. AI startup Lindy switched from Claude to DeepSeek, saving millions, while Snowflake's tests found GLM-5.2 solved 66% of coding tasks compared to Claude Opus's 67%—but at a fraction of the cost (output pricing is 5-7 times lower). While the top Western models may offer slightly better stability, the massive price differential is leading many businesses to reconsider their value proposition. This shift signals a deeper change in the AI industry, moving beyond pure performance benchmarks to a fierce cost competition. As pressure mounts, even OpenAI and Anthropic have begun slashing prices. For users, this means more choices, lower costs, and a crucial lesson: using multiple models based on task complexity, optimizing with caching, and keeping contexts lean are now key to leveraging AI efficiently and affordably.

marsbitHá 3m

When US Giants Collectively "Defect" to Chinese AI Models

marsbitHá 3m

BIS Report Compliance Watch: The Real Risks of Stablecoins Are Not Just 'De-pegging'

BIS Report Compliance Observations: The real risks of stablecoins go beyond "depegging" The BIS report "Anchoring trust in money: innovation beyond stablecoins" argues that while stablecoins and tokenization offer efficiency gains, their primary risk lies in fitting into an identifiable, monitorable, accountable, and regulatable financial system. Money's trust stems not just from technology but from institutional arrangements: a common unit of account, guaranteed redemption at par, liquidity support, regulatory frameworks, and financial integrity requirements. Stablecoins, operating on permissionless blockchains with pseudo-anonymity and non-custodial wallets, create systemic compliance gaps: unclear customer identity, incomplete fund origins, unexplained transaction purposes, fragmented cross-chain paths, and ambiguous liability. On-chain transparency does not equal compliance transparency. Public addresses don't reveal identity or intent. While blockchain analytics aid law enforcement, they cannot replace routine, large-scale AML/CFT controls. Effective compliance requires a closed-loop process encompassing customer onboarding, transaction monitoring, investigation, reporting, and audit. Stablecoin risks are not confined to the blockchain; they re-enter the traditional financial system via on/off-ramps, exchanges, and payment institutions. This forces banks to monitor client accounts for activity linked to virtual assets. The future direction is not to prohibit innovation but to embed rules into the technology. Tokenized finance should integrate with the existing two-tier monetary system, embedding compliance—like customer identification, pre-transaction screening, and auditable data trails—directly into the transaction flow. For compliance professionals, the key takeaway is that any new financial instrument must answer core questions: Who identifies the customer? Who monitors transactions? Who handles exceptions? Who is liable? Compliance is not the antithesis of innovation but the essential infrastructure for its sustainable growth.

链捕手Há 4m

BIS Report Compliance Watch: The Real Risks of Stablecoins Are Not Just 'De-pegging'

链捕手Há 4m

When American Giants 'Defect' to Chinese AI Models

Summary: The trend of major U.S. technology firms adopting more cost-effective Chinese AI models is gaining momentum. A prime example is Coinbase, the largest U.S. cryptocurrency exchange, which reportedly halved its AI expenditure by switching to Chinese models GLM-5.2 and Kimi 2.7, while its usage volume increased. This was achieved through a sophisticated cost-saving system featuring intelligent model routing (selecting the most suitable model per task), dramatically improving cache hit rates from 5% to 60%, and implementing "Context Engineering" to streamline prompts. This shift is not isolated. Other companies like the AI startup Lindy and data cloud firm Snowflake are making similar moves, drawn by the significant price disparity. For instance, GLM-5.2 costs $1.40/$4.40 per million tokens (input/output), compared to $5/$25 for Claude Opus 4.7. While top Western models may offer slightly higher stability or speed in complex tasks, the performance gap is narrowing, making the price difference harder to justify for many enterprise use cases. The implications are significant for both businesses and individual users. It highlights the importance of a multi-model strategy based on task requirements, the value of caching and reusing outputs, and the effectiveness of providing concise context. Ultimately, this migration signals a potential reshaping of the AI industry's pricing model, moving competition from pure performance benchmarks to practical cost-effectiveness, with increased choice and downward price pressure benefiting end-users.

链捕手Há 11m

When American Giants 'Defect' to Chinese AI Models

链捕手Há 11m

Trading

Spot
活动图片