2026-08-03 Segunda

Notícias de cripto - Página 155

Mantenha-se a par do mercado de cripto. Notícias em tempo real, análises, preços, histórias em alta e análise de especialistas — tudo num só lugar.

Is the MicroStrategy Model Failing? Imitator Holding 30,000 Bitcoins Sees Pre-IPO Investors Backing Out

"The 'Bitcoin Treasury' model is facing a critical test. BSTR Holdings, a company founded by Adam Back and holding 30,021 Bitcoin, has called off its planned merger with SPAC Cantor Equity Partners I. The deal, which would have taken it public, fell apart as the attached private investment (PIPE) financing collapsed. This failure highlights a core vulnerability of the 'Bitcoin accumulation company' strategy popularized by MicroStrategy. The model relies on a key metric: mNAV, or the premium of a company's stock market value over the value of its Bitcoin holdings. This premium fuels a cycle where companies issue shares at a premium, use the cash to buy more Bitcoin, and theoretically increase the Bitcoin per share for investors. However, with Bitcoin's price down roughly 49% from its late-2024 peak, this premium has evaporated across the sector. Companies like American Bitcoin and Metaplanet are also under severe pressure. For BSTR, the lack of premium meant investors were unwilling to fund the original deal structure at the proposed terms. The companies are now renegotiating. The next SEC filing detailing any new agreement will be a crucial indicator. It will show if the model can be repriced for a low-premium environment by preserving Bitcoin holdings and investor commitments, or if it requires significantly diluting shareholders and scaling back ambitions. The outcome is a public stress test for the entire 'Bitcoin treasury' investment thesis."

marsbit07/13 06:09

Is the MicroStrategy Model Failing? Imitator Holding 30,000 Bitcoins Sees Pre-IPO Investors Backing Out

marsbit07/13 06:09

Want Another Bull Market? Bitcoin Needs Trillions in Fresh Capital Inflow

Title: Want Another Bull Run? Bitcoin Needs Trillions in New Capital Bitcoin has fallen 50% from its October 2025 high of $126k, now trading near $63,000. Recent on-chain reports reveal structural differences in this downturn compared to past cycles, extending beyond simple price charts. A key issue is declining capital efficiency. CryptoQuant analysis shows the capital required for price appreciation has surged dramatically. In 2011, $27 billion in net inflows drove a 55,436% gain. From 2018-2021, $36.5 billion fueled a ~2000% rise. This cycle, $69.7 billion in realized cap growth has yielded only a 689% increase. Today, an estimated $101 billion is needed to double the price, versus just $5 million in 2011. The report concludes that triggering a major bull run now likely requires over $1 trillion in new institutional capital, positioning Bitcoin as a core global asset class rather than relying on retail ETF flows. Meanwhile, supply is tightening. K33 Research notes long-term holder supply has hit a record 79% of circulating coins. Dormant bitcoin moving after 2+ years is at its lowest since 2012. Alphractal data confirms this trend, with ~830k BTC recently moving to long-term storage. This scarcity of tradable supply can amplify price moves from any new buying pressure but doesn't guarantee capital inflow. Profitability metrics signal a potential bottom. CryptoQuant's Net Realized Profit/Loss ratio has dropped to -0.35, a 43-month low matching levels seen during the 2022 FTX crash. Historically, such extremes preceded major bull markets in 2015 and 2019. The current price is only 16% above the network's realized price; historically, this has led to average gains of 41% in six months and 81% in one year. Bitcoin is testing key support near $60,000, with analysts noting a potential W-bottom pattern forming. Macro headwinds persist. U.S. spot Bitcoin ETFs saw record monthly outflows of over $4.5 billion in June. Uncertainty around Federal Reserve policy under a potential new chair and mixed economic data add pressure. While European institutional infrastructure is slowly developing (e.g., German banks offering BTC services), this is a demand factor, not an immediate liquidity catalyst. In summary, the market shows signs of bottoming: sell-side pressure is largely exhausted, supply is scarce, and metrics are at historical extremes. However, for a significant bull run akin to past cycles, unprecedented institutional capital—likely exceeding $1 trillion—is required to overcome the new reality of drastically lower capital efficiency. The decisive variable of massive new institutional inflows remains absent.

Foresight News07/13 06:06

Want Another Bull Market? Bitcoin Needs Trillions in Fresh Capital Inflow

Foresight News07/13 06:06

USDT usage at 35% in 2026 – What’s the key factor driving investors to stablecoins?

Investor preference for stability over risk is driving increased usage of stablecoins, with Tether [USDT] projected to reach 35.1% usage by July 2026, up from 29.0% in 2021. This growth is fueled by their expanding real-world utility, particularly in cross-border payments and corporate treasury operations. Major payment firms like Visa, Mastercard, PayPal, and Stripe are integrating stablecoins into their infrastructure, supporting a surge in daily active addresses and a total market value nearing $312 billion. While institutional investors continue to favor stablecoins for efficient transactions over speculative assets like Bitcoin or Ethereum, the growing corporate adoption for practical settlement and payment use cases is strengthening blockchain's long-term foundation beyond mere cost savings.

ambcrypto07/13 05:02

USDT usage at 35% in 2026 – What’s the key factor driving investors to stablecoins?

ambcrypto07/13 05:02

The Signal That Has Appeared Before Every BTC Bottom Since 2014, It Was Close This Time

A valuation model tracking Bitcoin for 12 years has been updated. The new model shows a current score of 24.3, placing BTC in the historical bottom 20% range. However, analysis reveals that since 2014, every Bitcoin bear market bottom has seen this score drop *below 20* for a sustained period before turning around. The current cycle's low so far was 21.5 on July 1st. The author explains the model was rebuilt to address a flaw in its historical baseline, making it a more accurate "map" of current value. Two interpretations are offered: either the historically definitive washout has not yet occurred, or this cycle's bottom will be shallower, as each cycle has been less volatile than the last. The author's action plan involves automated buying triggered at specific score levels. A purchase was made at the cycle's cheapest reading (21.5), with more capital allocated for a potential drop below 20. The strategy emphasizes following a pre-written plan over emotion. Additional market context is provided: Bitcoin reclaimed its 200-week moving average, the BTC/Gold ratio is at a 3-year low showing capital preference for gold, and Bitcoin dominance remains high at 59%, indicating no "altcoin season." The summary concludes by noting the model's inconvenient implication—the market looks less like a bottom now—and poses a question to readers: at what score would they deploy their final capital?

marsbit07/13 04:38

The Signal That Has Appeared Before Every BTC Bottom Since 2014, It Was Close This Time

marsbit07/13 04:38

Qingyan Jingzhun Raises Hundreds of Millions in Funding, with Investment from National Equipment Manufacturing Giants

Qingyan Precision, a provider of physical AI infrastructure, has secured billions of RMB in Series B financing. The investment round, led by prominent automotive industry funds and notably featuring the state-owned China National Machinery Industry Corp. (Sinomach) fund, underscores a strategic shift in the capital market towards companies with proven industrial application capabilities. The company positions itself as the "engineering foundation for physical AI," specializing in enabling embodied intelligence (like humanoid robots) to operate in complex, real-world industrial environments. Its core offering is the "TsingLoop" multi-modal data engineering pipeline, which captures and standardizes data from physical workspaces (like visual, force, and process parameters) to create reusable data assets. This system supports a "Robot-in-the-Loop" testing framework that validates robotic performance in digital twin simulations and real-world conditions before deployment. Qingyan Precision leverages over eight years of experience and a network of 2000+ industrial sensor nodes across sectors like automotive and mining. This provides a crucial "training ground" for embodied AI models. The founding team combines academic pedigree from Tsinghua University and Stanford with deep industry experience from leading robotics firms. The company's vision is to build "one foundation, one brain, and hundreds of vertical applications," using its data platform and industrial world model to deploy scalable physical intelligence across various industrial tasks.

marsbit07/13 04:30

Qingyan Jingzhun Raises Hundreds of Millions in Funding, with Investment from National Equipment Manufacturing Giants

marsbit07/13 04:30

Making a Fortune of $10.32 Million: The World Cup Money-Printing Tactic of a Polymarket Whale

**Earning $10.32 Million: A Polymarket Whale's World Cup Profit Strategy** While teams battle for the World Cup trophy, a hidden whale nicknamed "swisstony" has been quietly making a fortune on the prediction market Polymarket. This account, created around July 2025, boasts total profits of $18.62 million, with $10.33 million earned in the past month alone. With a 52.9% win rate, it has placed over 139,600 predictions, averaging about 380 trades per day—indicating it is likely a high-frequency quantitative bot. The account's signature "trash panda" aptly describes its strategy: sifting through vast market data and tiny price discrepancies to build wealth. Its current holdings are heavily concentrated on the France vs. Spain semi-final, including a roughly $160,000 bet against France. Analysis shows two core tactics driving its success: 1. **High-Volume "Anti-Favorite" Bets:** Placing large wagers (often $400k-$1M) against overvalued favorites like Germany or England, buying "No" shares at favorable prices when market-implied win probability is 46%-64%. It has recorded over 17 individual profits exceeding $1 million using this method. 2. **"Lottery-Ticket" Bets on Extreme Long Shots:** Allocating small amounts (thousands of dollars) to buy shares priced as low as 0.2¢-1.2¢ on outcomes deemed nearly impossible. While most of these bets lose, the occasional win—like those with payouts over 100x—generates significant profits (over $100,000 per hit) that boost overall returns without risking much capital. This dual approach combines consistent, large-scale profit from correcting major market mispricings with opportunistic, high-reward bets on extreme underdogs. The account exemplifies how systematic, high-frequency execution can amplify a small statistical edge into millions in profits on prediction markets.

Foresight News07/13 04:03

Making a Fortune of $10.32 Million: The World Cup Money-Printing Tactic of a Polymarket Whale

Foresight News07/13 04:03

AI Token Factory Explosion: Tsinghua University Team Raises 10 Billion in Half a Year

Qijing Tech, a company founded by a Tsinghua University team of faculty and students, has rapidly become a significant player in China's AI infrastructure sector, focusing on high-quality AI token production. Over the past six months, the startup has secured over 1 billion RMB in funding. The company specializes in AI inference—the efficient use of AI models—positioning itself as a "high-quality AI token factory." Unlike many competitors initially focused on model training, Qijing Tech believes inference is where real economic value is generated. Its core technology optimizes the entire AI token production chain through innovations like "full-system heterogeneous collaboration," aiming for stable, efficient, and low-cost output suitable for enterprise use. This strategy has attracted significant investor interest. Major funding rounds have been led by institutions such as Henan Investment Group Huirong Fund, with continued backing from existing investors. The company's "less models, deeper optimization" approach, concentrating resources on key models and high-value scenarios, is resonating in a market where a few top models dominate token usage. The results are promising. Since early 2026, Qijing Tech reports a threefold increase in token production efficiency per unit of computing power and a thirtyfold increase in total high-quality token output. Monthly revenue for June 2026 alone surpassed its entire 2025 revenue. Operating on a "Token as a Service" (TaaS) model, Qijing Tech engages in both direct token sales and collaborative operations, helping partners like state-owned enterprises transition from traditional computing power leasing to high-value token production. As AI token usage in China surges, Qijing Tech aims to be a key enabler in the emerging AI token economy, building the essential infrastructure for the AI era.

marsbit07/13 03:42

AI Token Factory Explosion: Tsinghua University Team Raises 10 Billion in Half a Year

marsbit07/13 03:42

Financing Weekly Report | SBI Makes Consecutive Moves, Bets $125 Million on Gauntlet; Crypto Capital Continues to Flow to Trading and Infrastructure

Weekly crypto financing highlights show capital continues to flow into trading, compliance, and digital asset infrastructure, with traditional financial institutions like Japan's SBI Holdings playing a larger role. SBI made two major investments: a $125M exclusive investment in DeFi risk management and asset allocation platform Gauntlet, and leading a $76M Series C round for crypto exchange EDX Markets. Other notable crypto deals included: QIZ Security ($17M seed) for post-quantum cryptography management; TrueDAO ($10M strategic) for AI-powered DeFi infrastructure; KOR Protocol ($7.5M Series A) for an on-chain creative asset clearing platform; Tether's $20M strategic investment in Brazil's Mercado Bitcoin; and M1X Global ($5.5M seed) for sovereign financial infrastructure. The AI sector saw larger individual rounds. Prime Intellect raised $130M Series A for its decentralized AI protocol stack. AI legal services firm Norm raised $120M, reaching a $1.2B valuation. Voice AI company Gradium's total funding surpassed $100M. The report also notes a shift towards business models focused on specific enterprise-level AI infrastructure and application scenarios. Overall, the crypto primary market remains subdued, with nine deals totaling over $261M last week, centered on centralized finance, DeFi, and infrastructure.

marsbit07/13 03:41

Financing Weekly Report | SBI Makes Consecutive Moves, Bets $125 Million on Gauntlet; Crypto Capital Continues to Flow to Trading and Infrastructure

marsbit07/13 03:41

Why Bitcoin miners are holding 1.19M BTC despite 10% mining stock losses

Bitcoin miners are continuing to accumulate and hold their BTC reserves, which have reached approximately 1.1938 million, despite a challenging market environment. Bitcoin has struggled to reclaim the $64,000 price level, and mining stocks have seen significant losses, with an aggregate 10% decline over the past month. Key metrics, however, indicate miner confidence. The Bitcoin Miners’ Position Index (MPI) reads -1.1, signaling miners are holding rather than selling, and the Miner Supply Ratio has been rising since early July. While miners control over 5% of Bitcoin's total supply—meaning any large-scale selling could pressure prices—their current accumulation is providing a supportive dynamic for the asset's price.

ambcrypto07/13 03:03

Why Bitcoin miners are holding 1.19M BTC despite 10% mining stock losses

ambcrypto07/13 03:03

Vitalik and Aya Hong Kong Conversation: The Ethereum Ecosystem Is Entering a Multi-Node Future

"Vitalik Buterin and Aya Miyaguchi's dialogues in Hong Kong, along with subsequent events, signal Ethereum's shift into a multi-node future. Over two months, key developments included the Ethereum Foundation's restructuring to focus on longevity and core protocol values (CROPS), the establishment of independent non-profit organizations like Ethlabs for R&D and Ethereum Institutional as an institutional gateway, and continued efforts by Etherealize to connect Ethereum with traditional finance. These moves reflect a broader transition where the EF is deliberately doing less, embracing a 'subtraction' philosophy and a 'walk-away test' to ensure the ecosystem's resilience isn't dependent on a single central body. Instead, specialized nodes are emerging to handle different functions like protocol development, institutional adoption, and regional community coordination. The opening of the ETH HK Hub in Asia exemplifies this trend, positioning Hong Kong as a key node for builder coordination and institutional outreach. The core takeaway is that Ethereum's strength and future evolution increasingly depend on a decentralized network of independent, collaborative organizations rather than a single central coordinator."

marsbit07/13 02:55

Vitalik and Aya Hong Kong Conversation: The Ethereum Ecosystem Is Entering a Multi-Node Future

marsbit07/13 02:55

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