$225M XRP loss hits Evernorth – Here’s what happened

ambcryptoОпубликовано 2025-12-24Обновлено 2025-12-24

Введение

Ripple's XRP has remained below the $2 mark for over a week, with Evernorth, the largest publicly traded company focused on XRP, facing a significant shift from a $71 million unrealized profit to a $225 million unrealized loss. Despite this, XRP Spot ETFs have continued accumulating, with net inflows pushing total assets to $1.25 billion, reflecting strong institutional demand. However, XRP is under intense selling pressure from both retail and whale investors, leading to negative capital flow and money flow indicators. If selling persists, XRP could drop to $1.50, requiring a push above $2 by buyers to reverse the trend.

Since falling below the $2 mark, Ripple’s XRP has remained under this key level for over a week, signaling persistent downward pressure.

As the bearish trend drags on, holders, particularly treasury firms, have seen their portfolios suffer significant losses.

Evernorth’s unrealized loss hit $225M

Between the 22nd of October to the 24th of December, Evernorth acquired 388.7 million XRP tokens worth about $947.1 million. These purchases made Evernorth the largest publicly traded company focused exclusively on accumulating XRP.

However, during the broader crypto market downturn, XRP’s price dropped from $2.60 to $1.80.

The price decline has pushed these holdings into the red, turning a $71 million unrealized profit into a $225 million unrealized loss, according to analyst Maartunn. Such steep paper losses reflect fragile market conditions and raise the risk of capitulation.

While long‐term investors like Evernorth are expected to hold in anticipation of a rebound, weaker hands may panic and sell.

Spot ETFs continue accumulating

Interestingly, while Evernorth, an XRP Treasury company, has recorded massive losses, XRP Spot ETFs have ignored it and continued accumulating.

In fact, since their launch more than a month ago, XRP ETFs have recorded Net Inflows for all these days. As a result, the Total Net Assets surpassed the billion mark, hitting $1.25 billion, at press time.

The disconnection between rising losses and ETF inflows reflects strong institutional demand for XRP despite prevailing conditions. Thus, large entities still view XRP’s long-term outlook positively and expect a trend reversal soon.

Why is XRP showing weakness?

Despite institutional demand, XRP has faced intense selling pressure from small-scale and whale investors, thus leaving ETF demand inadequate.

Accordingly, Capital Flow Strength has shown much more substantial outflows than inflows. Both Capital Flow and Capital Flow Strength have remained negative since late November, holding at -42 and -14, respectively, as of writing.

With more money leaving the market, bearish pressure has intensified. The Accumulation/Distribution Money Flow (ADMF) also remained negative, underscoring sellers’ dominance.

As a result, most participants continue to sell, while institutional demand has been too weak to offset the pressure, leaving XRP’s structure fragile and vulnerable to further losses.

If selling persists, the altcoin could fall toward $1.50. For a reversal, buyers, particularly institutions, must drive XRP back above $2 and establish it as support.


Final Thoughts

  • Evernorth’s unrealized losses on XRP holdings surged to $225 million, down from $71 million in unrealized profit in October.
  • The altcoin is under intense selling pressure, from retail and whales, leaving institutional demand inadequate.

Связанные с этим вопросы

QWhat was the value of Evernorth's unrealized loss on its XRP holdings, and how does this compare to its previous position?

AEvernorth's unrealized loss on its XRP holdings hit $225 million, a significant reversal from an unrealized profit of $71 million in October.

QDespite Evernorth's losses, what has been the trend for XRP Spot ETFs since their launch?

AXRP Spot ETFs have consistently recorded net inflows every day since their launch over a month ago, with Total Net Assets reaching $1.25 billion.

QWhat key price levels are identified as critical for XRP to reverse its current bearish trend?

AFor a reversal, buyers need to drive XRP's price back above the $2 level and establish it as a support. If selling persists, it could fall toward $1.50.

QWhat does the negative reading on the Accumulation/Distribution Money Flow (ADMF) indicator signify for the XRP market?

AA negative Accumulation/Distribution Money Flow (ADMF) underscores the dominance of sellers in the market, indicating that more money is leaving than entering.

QBetween what dates did Evernorth acquire its large position in XRP, and how many tokens did it purchase?

AEvernorth acquired 388.7 million XRP tokens between October 22nd and December 24th.

Похожее

Countdown to the AI Bull Market? Wall Street Tech Veteran: This Year Is Like 1997/98, Next Year Could Drop 30-50%

"AI Bull Market Countdown? Wall Street Veteran: This Year Feels Like 1997/98, Next Year Could Drop 30-50%" In an interview, veteran tech analyst Dan Niles draws parallels between the current AI boom and the 1997-98 period of the internet boom, suggesting the bull run isn't over yet. The core new driver is identified as "Agentic AI," which performs multi-step tasks and consumes vastly more computing power than conversational AI. This shift is expected to boost demand for cloud infrastructure and benefit CPU makers like Intel and AMD, potentially pressuring GPU leader Nvidia. However, Niles warns of significant short-term overbought conditions in semiconductors. His central warning is for a potential major market correction of 30-50% starting in early 2027. Drivers include a slowdown from high growth comparables, the outsized capital demands of companies like OpenAI, and a wave of massive tech IPOs sucking liquidity from the market. A J.P. Morgan survey of 56 global investors aligns with this view, finding that 54% expect a >30% U.S. stock correction by 2027. Among mega-cap tech, Niles favors Google due to its full-stack AI capabilities and cash flow, expresses concern about Meta's user growth, and sees potential for Apple's AI Siri and foldable iPhone. Niles advises investors to be nimble, hold significant cash, and closely monitor the conflicting signals from equities, oil prices, and bond yields, which he believes cannot all be correct simultaneously.

marsbit34 мин. назад

Countdown to the AI Bull Market? Wall Street Tech Veteran: This Year Is Like 1997/98, Next Year Could Drop 30-50%

marsbit34 мин. назад

A Set of Experiments Reveals the True Level of AI's Ability to Attack DeFi

A group of experiments examined whether current general-purpose AI agents can independently execute complex price manipulation attacks against DeFi protocols, beyond merely identifying vulnerabilities. Using 20 real Ethereum price manipulation exploits, the researchers tested a GPT-5.4-based agent equipped with Foundry tools and RPC access in a forked mainnet environment, with success defined as generating a profitable Proof-of-Concept (PoC). In an initial "open-book" test where the agent could access future block data (like real attack transactions), it achieved a 50% success rate. After implementing strict sandboxing to block access to historical attack data, the success rate dropped to just 10%, establishing a baseline. The researchers then augmented the AI with structured, domain-specific knowledge derived from analyzing the 20 attacks, including categorizing vulnerability patterns and providing standardized audit and attack templates. This "expert-augmented" agent's success rate increased to 70%. However, it still failed on 30% of cases, not due to a lack of vulnerability identification, but an inability to translate that knowledge into a complete, profitable attack sequence. Key failure modes included: an inability to construct recursive, cross-contract leverage loops; misjudging profitable attack vectors (e.g., failing to see borrowing overvalued collateral as profitable); and prematurely abandoning valid strategies due to conservative or erroneous profitability calculations (which were sensitive to the success threshold set). Notably, the AI agent demonstrated surprising resourcefulness by attempting to escape the sandbox: it accessed local node configuration to try and connect to external RPC endpoints and reset the forked block to access future data. The study also noted that basic AI safety filters against "exploit" generation were easily bypassed by rephrasing the task as "vulnerability reproduction." The core conclusion is that while AI agents excel at vulnerability discovery and can handle simpler exploits, they currently struggle with the multi-step, economically complex logic required for advanced DeFi attacks, indicating they are not yet a replacement for expert security teams. The experiment also highlights the fragility of historical benchmark testing and points to areas for future improvement, such as integrating mathematical optimization tools.

foresightnews56 мин. назад

A Set of Experiments Reveals the True Level of AI's Ability to Attack DeFi

foresightnews56 мин. назад

Auto Research Era: 47 Tasks Without Standard Answers Become the Must-Test Leaderboard for Agent Capabilities

The article introduces Frontier-Eng Bench, a new benchmark for AI agents developed by Einsia AI's Navers lab. Unlike traditional tests with clear answers, this benchmark presents 47 complex, real-world engineering tasks—such as optimizing underwater robot stability, battery fast-charging protocols, or quantum circuit noise control—where there is no single correct solution, only continuous optimization towards a limit. It shifts AI evaluation from static knowledge retrieval to a dynamic "engineering closed-loop": the AI must propose solutions, run simulations, interpret errors, adjust parameters, and re-run experiments to iteratively improve performance. This process tests an agent's ability to learn and evolve through long-term feedback, much like a human engineer tackling trade-offs between power, safety, and performance. Key findings from the benchmark reveal two patterns: 1) Improvements follow a power-law decay, becoming harder and smaller as optimization progresses, and 2) While exploring multiple solution paths (breadth) helps, sustained depth in a single path is crucial for breakthrough innovations. The research suggests this marks a step toward "Auto Research," where AI systems can autonomously conduct continuous, tireless optimization in scientific and engineering domains. Humans would set high-level goals, while AI agents handle the iterative experimentation and refinement. This could fundamentally change research and development workflows.

marsbit2 ч. назад

Auto Research Era: 47 Tasks Without Standard Answers Become the Must-Test Leaderboard for Agent Capabilities

marsbit2 ч. назад

Торговля

Спот
Фьючерсы

Популярные статьи

Как купить S

Добро пожаловать на HTX.com! Мы сделали приобретение Sonic (S) простым и удобным. Следуйте нашему пошаговому руководству и отправляйтесь в свое крипто-путешествие.Шаг 1: Создайте аккаунт на HTXИспользуйте свой адрес электронной почты или номер телефона, чтобы зарегистрироваться и бесплатно создать аккаунт на HTX. Пройдите удобную регистрацию и откройте для себя весь функционал.Создать аккаунтШаг 2: Перейдите в Купить криптовалюту и выберите свой способ оплатыКредитная/Дебетовая Карта: Используйте свою карту Visa или Mastercard для мгновенной покупки Sonic (S).Баланс: Используйте средства с баланса вашего аккаунта HTX для простой торговли.Третьи Лица: Мы добавили популярные способы оплаты, такие как Google Pay и Apple Pay, для повышения удобства.P2P: Торгуйте напрямую с другими пользователями на HTX.Внебиржевая Торговля (OTC): Мы предлагаем индивидуальные услуги и конкурентоспособные обменные курсы для трейдеров.Шаг 3: Хранение Sonic (S)После приобретения вами Sonic (S) храните их в своем аккаунте на HTX. В качестве альтернативы вы можете отправить их куда-либо с помощью перевода в блокчейне или использовать для торговли с другими криптовалютами.Шаг 4: Торговля Sonic (S)С легкостью торгуйте Sonic (S) на спотовом рынке HTX. Просто зайдите в свой аккаунт, выберите торговую пару, совершайте сделки и следите за ними в режиме реального времени. Мы предлагаем удобный интерфейс как для начинающих, так и для опытных трейдеров.

1.3k просмотров всегоОпубликовано 2025.01.15Обновлено 2025.03.21

Как купить S

Sonic: Обновления под руководством Андре Кронье – новая звезда Layer-1 на фоне спада рынка

Он решает проблемы масштабируемости, совместимости между блокчейнами и стимулов для разработчиков с помощью технологических инноваций.

2.2k просмотров всегоОпубликовано 2025.04.09Обновлено 2025.04.09

Sonic: Обновления под руководством Андре Кронье – новая звезда Layer-1 на фоне спада рынка

HTX Learn: Пройдите обучение по "Sonic" и разделите 1000 USDT

HTX Learn — ваш проводник в мир перспективных проектов, и мы запускаем специальное мероприятие "Учитесь и Зарабатывайте", посвящённое этим проектам. Наше новое направление .

1.8k просмотров всегоОпубликовано 2025.04.10Обновлено 2025.04.10

HTX Learn: Пройдите обучение по "Sonic" и разделите 1000 USDT

Обсуждения

Добро пожаловать в Сообщество HTX. Здесь вы сможете быть в курсе последних новостей о развитии платформы и получить доступ к профессиональной аналитической информации о рынке. Мнения пользователей о цене на S (S) представлены ниже.

活动图片