Уверенный рост SOPR свидетельствует о старте нового бычьего цикл биткоина

cryptonews.ruPublished on 2025-11-19Last updated on 2025-11-19

Показатель SOPR Ratio, сравнивающий прибыльность долгосрочных и краткосрочных держателей, вновь смещается в сторону первых. Это может стать важным сигналом для рынка биткоина (BTC). Исторически, когда прибыльность концентрировалась у долгосрочных инвесторов, цена актива демонстрировала продолжительные периоды роста.

В ранние годы существования первой криптовалюты, с 2010 по 2013, коэффициент отличался высокой волатильностью. Тогда рынок находился в стадии открытия, и именно долгосрочные держатели чаще всего получали значительные прибыли во время резких ценовых скачков. Этот фактор создавал фундамент для первых масштабных ралли.

В период с 2014 по 2018 годы ситуация изменилась. Во время затяжного медвежьего рынка 2014 года краткосрочные инвесторы усилили давление на продажи, что резко снизило показатель. Однако уже в 2017 году, в разгар нового роста, коэффициент снова ушел в пользу долгосрочных держателей.

Следующий крупный цикл, охватывающий 2019–2021 годы, продемонстрировал более умеренное значение. Прибыльность распределялась и между краткосрочными игроками, что сделало вершину рынка более хрупкой. В результате коррекция наступила быстрее, чем в прошлых циклах.

Во время медвежьего тренда 2022–2024 годов показатель оставался низким. Это отражало ослабленную позицию долгосрочных инвесторов. Однако уже с 2023 года начался постепенный разворот: прибыльность таких держателей вновь стала расти, указывая на возможное формирование нового этапа.

Сегодня коэффициент находится в балансирующем, но восходящем положении. Это означает, что долгосрочные держатели снова начинают доминировать. Если тенденция сохранится, исторические параллели говорят о высокой вероятности продолжительного ралли, которое может вывести биткоин выше отметки $120 000.

Related Reads

The War Without a Unified Name: The Domestic Tech Giants' World Model Landscape

The article outlines the diverse and fragmented landscape of "World Models" in China's tech industry, where major players are pursuing similar goals under different names like world foundational models, physical AI, or integrated within autonomous driving and embodied intelligence systems. The core aim is to enable AI to create an internal, dynamic environment for simulation, reasoning, and learning, reducing reliance on infinite real-world data. This "data engine" allows for unlimited generation, experimentation, and iteration. The report categorizes the approaches of different companies: * **Internet Giants:** Alibaba is developing models for linguistic, virtual, and physical worlds (Qwen-AgentWorld, HappyOyster, Qwen-RobotWorld). Tencent's HY-World focuses on 3D, game, and social scenarios. ByteDance leverages its vast video data for a potential "digital twin" model. Huawei integrates its model into industrial applications like smart cars and robotics without separately branding it. Baidu embeds world model capabilities within its Apollo autonomous driving and Ernie systems. * **Automakers:** Companies like NIO, Li Auto, XPeng, and Geely are using world models as virtual "driving schools" and "testing grounds." They generate complex scenarios (e.g., rain, snow) to train and validate autonomous driving systems in simulation, aiming for more capable and safer AI drivers. * **Autonomous Driving Suppliers:** Firms such as Momenta, Horizon Robotics, Haomo.ai, and DeepRoute.ai are building the underlying "world engines." They focus on large-scale video generation for simulation, reinforcement learning, and enhancing end-to-end autonomous driving models, often integrating these capabilities into commercial products. While startups bring focus and innovation, they face challenges like limited data, compute resources, and deployment channels. Large companies possess these advantages and are rapidly transitioning world models from research projects into core business infrastructure powering products in vehicles, games, and industry. The conclusion is that world models represent an evolution and convergence of existing AI fields into crucial industrial infrastructure, moving the competition from simply building a model to effectively deploying it to understand and interact with the physical world.

marsbit9m ago

The War Without a Unified Name: The Domestic Tech Giants' World Model Landscape

marsbit9m ago

The Crypto Industry Enters the 'Show Me' Era: Vision Alone Is No Longer Enough

The crypto industry has entered a "Show Me" era, where grand visions and white papers are no longer sufficient to gain traction. This shift is driven by increased skepticism, high-profile bad actors, and notably, the serious entry of traditional finance (TradFi) institutions like BlackRock, Fidelity, and JPMorgan Chase, which are launching real, scaled products such as tokenized funds and blockchain-based settlement. This raises the bar for what constitutes a credible project. The communication dynamic has fundamentally changed. The focus is no longer on "what you are building" but on "what you have built and who is using it." Startups must now provide a "proof stack": verifiable data like mainnet transaction volume and active wallets, genuine partnerships with signed contracts, and evidence of organic product-market fit from real users, not just investors. Announcements must be backed by concrete, chain-verifiable evidence. For communication strategies, this means leading with proven facts and hard data—even if modest—rather than speculative narratives. A compelling story must be grounded in demonstrated results. While vision remains important, the balance has inverted from 80% vision/20% substance to the opposite. This higher threshold ultimately benefits builders with genuine traction, filtering out noise and allowing their real signals to stand out clearly. The "Show Me" era is a permanent maturation, demanding that communication strategies prove value, not just promise it.

链捕手40m ago

The Crypto Industry Enters the 'Show Me' Era: Vision Alone Is No Longer Enough

链捕手40m ago

Meta Follows the Trend into Prediction Markets: Can It Avoid Repeating the Failure of the Metaverse?

Meta, the tech giant behind Facebook, has reportedly formed a team to develop "Arena," a new application focused on prediction markets. Users would use platform points to place bets on outcomes in politics, sports, and global events. This move follows Meta's massive, nearly $900 billion, losses from its heavily-invested metaverse division, Reality Labs. The prediction market industry is already showing strong demand, with leading platforms like Kalshi and Polymarket facilitating hundreds of billions in annual volume. Meta, with its 3.56 billion daily active users across its apps, possesses the unprecedented scale to bring this niche activity to a mainstream audience, similar to its past success in cloning features like Stories and Reels. However, Arena faces significant hurdles. Meta plans to start with a points-based system to avoid strict financial regulations, but this may dilute the core incentive of accurate prediction that real-money markets provide. More critically, Meta enters the space with a major trust deficit stemming from its past regulatory battles, notably the failed Libra/Diem stablecoin project, and its controversial history with political content and misinformation. The prediction market sector itself is under increasing regulatory scrutiny, with recent CFTC actions including fines and the first-ever insider trading case. While Meta's vast user base offers a unique opportunity to expand the market, its success hinges on navigating complex regulations and rebuilding the credibility necessary for a platform dealing with sensitive topics like elections. The outcome could range from Meta dramatically growing the industry to Arena becoming a high-profile regulatory target before it can scale.

Foresight News57m ago

Meta Follows the Trend into Prediction Markets: Can It Avoid Repeating the Failure of the Metaverse?

Foresight News57m ago

Trading

Spot
Futures
活动图片