BIT Research: ETF Purchases Have Slowed, Strategy (MicroStrategy) Has Slowed, What Else Can Drive Bitcoin's Rise?

marsbitPublished on 2026-06-05Last updated on 2026-06-05

Abstract

Market Refocus on Inflation and Rate Expectations Weighs on Bitcoin Currently, the market is in a phase of macro-repricing dominated by inflation and interest rate expectations. Bitcoin, which previously benefited from easy liquidity and low inflation, is seeing its core bullish drivers weaken. These drivers were market expectations for interest rate cuts and strong inflows from Bitcoin ETFs and institutions like MicroStrategy (referred to as "Strategy" in the text). The logic has shifted. Recent high inflation data (e.g., CPI hitting 3.8% in a May 2026 report) has caused the market to sharply reduce its rate cut expectations for 2025 and even price in potential hikes. This is a key constraint for Bitcoin, as it lacks cash flows and is highly sensitive to rate expectations. Concurrently, institutional capital flows have slowed significantly. Following the hot CPI data, Bitcoin ETFs saw accelerated outflows, with around $4.3 billion leaving over a period. MicroStrategy's ability to keep adding substantial Bitcoin to its balance sheet is also diminishing. Together, ETF and MicroStrategy holdings total roughly $110 billion, but their momentum as growth engines is cooling. In summary, Bitcoin's current pressure stems not from its own fundamentals but from a changing macro environment. As long as inflation stays elevated, Bitcoin is likely to remain in a consolidating phase. However, historically, inflation eventually peaks. Once it recedes and rate cut expectations rebuild, i...

The current market is in a macro repricing phase dominated by inflation and interest rate expectations. For over a decade, Bitcoin benefited from an environment of loose liquidity coexisting with low inflation, which continuously reinforced its narrative as a "hedge against monetary dilution." However, with institutional capital steadily entering, Bitcoin's pricing logic is shifting, becoming increasingly dependent on interest rate expectations and capital flows.

Judging from recent market performance, Bitcoin's recent weakness does not stem from a deterioration in its own fundamentals but rather from the waning of two core drivers behind this bull run. On one hand, market expectations for rate cuts are being persistently revised lower. On the other hand, incremental inflows from Bitcoin ETFs and corporate purchases (led by MicroStrategy, abbreviated as Strategy in some contexts) have begun to slow. Against this backdrop, pressure on Bitcoin is mounting, and its subsequent trajectory will still depend on changes in inflation and the Federal Reserve's policy path.

Resurgent Inflation: Interest Rate Expectations Become Bitcoin's Biggest Constraint

Post-pandemic fiscal stimulus altered monetary transmission mechanisms. Funds not only pushed up asset prices but also flowed into the real economy, leading to a significant rise in inflation approximately 18 months later. In June 2022, U.S. CPI hit a high of 9.1%. Subsequently, inflation continued to decline, falling to 2.4% in September 2024, which continuously bolstered market expectations for rate cuts and provided crucial support for Bitcoin's rise.

However, this logic began to change towards the end of 2024. As market concerns about resurgent inflation grew, expectations for rate cuts continued to recede. Market pricing for 2025 rate cuts decreased from approximately 6 cuts priced in September 2024 to nearly zero cuts by January 2025. Although it later recovered to around 2.6 cuts, when CPI hovered near 3% again, the market turned cautious once more. The CPI data released on May 12, 2026, came in at 3.8%, prompting the market to even start pricing in about 1.8 rate hikes again.

For stocks, higher inflation may still be partially absorbed through nominal revenue and earnings growth. But Bitcoin lacks cash flow and earnings support, making it more sensitive to changes in interest rate expectations. When the market reprices a higher interest rate path, Bitcoin often bears the brunt of the pressure.

Slowing ETF and Institutional Flows: Both Engines of the Bull Market Cool Simultaneously

In this cycle, Bitcoin ETFs have been one of the most significant sources of incremental capital. Since anticipation of ETF approval heated up in 2023, institutional capital became the core force driving the market higher. However, as the Federal Reserve's policy stance turned more hawkish, inflows have noticeably slowed. Entering 2026, Bitcoin ETFs have experienced sustained net outflows, with investor appetite for accumulation significantly declining.

Especially after the CPI data release on May 12, 2026, ETF outflows intensified markedly, with cumulative outflows reaching approximately $4.3 billion. In the following 15 trading days, net selling was recorded on 14 days, indicating institutional capital's caution in a high-inflation environment. Concurrently, while MicroStrategy (referred to as Strategy in some contexts) and Bitcoin ETFs have collectively accumulated roughly $110 billion worth of Bitcoin, the room for further accumulation by MicroStrategy is gradually narrowing, and its role as the second-largest capital engine is also weakening.

With ETF inflows stalling, institutional allocation appetite declining, and MicroStrategy's accumulation momentum slowing, the two core drivers that supported this bull run are showing signs of cooling, creating greater resistance for a Bitcoin rebound.

Overall, the primary challenges facing Bitcoin currently do not stem from within the industry but from changes in the macro environment. The loose liquidity and rate cut expectations that supported the market's rise in the past are fading, while institutional capital remains cautious about high inflation and potentially higher rates. In the short term, as long as inflation remains elevated, Bitcoin is likely to continue consolidating. However, looking at historical cycles, inflation eventually peaks. Once inflation recedes and rate cut expectations are restored, institutional capital may flow back in, potentially ushering in a new and more forceful recovery phase for Bitcoin.

Silicon Valley 'Startup Guru' Steve Hoffman: Web3 + AI Could Be a Trap

Silicon Valley investor and "Godfather of Startups" Steve Hoffman warns that combining Web3 with AI is likely a trap, not a promising venture. In an interview, Hoffman argues that while AI is a foundational technology touching all industries, Web3 adds complexity, friction, and regulatory risk without solving mainstream consumer or business needs. He advises founders to focus on deep, specialized applications where startups can out-iterate giants, rather than on generic features easily replicated by large tech companies. Hoffman observes that Silicon Valley will lead foundational AI research, while China excels at rapid, large-scale application and commercialization, particularly in robotics. He stresses that AI-driven autonomous agents capable of collaborative, multi-step tasks are 2-4 years away, which will cause significant job displacement. The solution is not to slow AI but to redesign business models around human-AI collaboration and reform social systems like education and retraining. For startups, Hoffman recommends focusing on vertical, expertise-heavy domains to build defensibility. He sees major opportunities in AI fraud detection and cybersecurity. Key founder mindsets include systemic thinking over feature-focus, relentless customer centricity, building adaptive teams, and deeply understanding AI's capabilities and limits. Hoffman is also leading a non-profit initiative to establish university centers aimed at training future leaders in responsible, human-value-aligned AI innovation.

marsbit48m ago

Silicon Valley 'Startup Guru' Steve Hoffman: Web3 + AI Could Be a Trap

marsbit48m ago

Token Inefficient, Economy Tokenless

The article "Tokens Aren't Economical, Economics Aren't Tokenized" analyzes a pivotal shift in the AI industry from a technology-driven narrative to one dominated by capital efficiency. It highlights two concurrent trends: a severe capital shortage due to the exorbitant and recurring costs of compute (e.g., OpenAI's high burn rate) and a wave of corporate spin-offs where major tech companies are separating their AI units (like Kuaishou's Kling and Baidu's Kunlunxin). The core argument is that AI's "anti-internet" business model, where user growth increases costs rather than profits, has created a disconnect between high valuations and actual cash flow. Spin-offs address this by allowing AI assets to be valued independently. Within a parent company, they are seen as cost centers, but as standalone entities, they are priced based on their growth potential and scarcity in the primary market, leading to massive valuation premiums (e.g., Kling's estimated value tripling post-spin-off). The industry is at an inflection point, moving from "model worship" to "value realization." The competition is evolving from a pure compute (GPU) race to a broader focus on systemic efficiency and full-stack engineering (involving CPUs and orchestration) to achieve viable commercialization. The year 2026 is framed as a critical moment where the industry must definitively answer how to economically translate AI capability into tangible business value, reshaping the sector's future power structure.

marsbit53m ago

marsbit53m ago

Crossing the 'Memory Wall': The Wafer-Level Revolution and Computing Power Routes in the AI Inference Era

In 2026, a historic shift occurred in AI as major cloud providers' inference spending surpassed training spending for the first time, signaling a move from "building large models" to "using large models." This shifts the core challenge from computing power to the "memory wall"—the bottleneck of data movement (model weights, activations, KV Cache) between external DRAM and processors, where energy and latency from data transfer far exceed computation itself. Companies like Nvidia face GPU idle time due to bandwidth limits. In contrast, Cerebras Systems adopts a radical "wafer-scale" approach with its Wafer-Scale Engine (WSE). Instead of cutting a silicon wafer into many chips, Cerebras uses almost the entire wafer as one massive chip (WSE-3). This design provides 44GB of on-chip SRAM, delivering memory bandwidth thousands of times higher than traditional HBM (e.g., 21 PB/s vs. Nvidia B200). For LLM inference, weights are streamed layer-by-layer from external MemoryX storage to the chip, avoiding HBM bottlenecks. This results in token generation speeds 1.5–5 times faster than Nvidia's B200 in some models and significant advantages in first-token latency and long-context tasks. Additionally, Cerebras's architecture offers much lower interconnect power consumption (0.15 pJ/bit vs. GPU's ~10 pJ/bit). However, Cerebras faces challenges: SRAM scaling has slowed with advanced nodes, limiting future capacity gains; the chip requires specialized liquid cooling and custom software stacks; and its external I/O bandwidth (150 GB/s) is low compared to NVLink, hindering multi-system scaling for very large models. Competition is intensifying. Major players are pursuing three paths: 1) Developing proprietary inference ASICs (e.g., Google TPU, Microsoft Maia), 2) Leveraging advanced packaging (e.g., TSMC's SoW) to democratize wafer-scale-like integration, potentially eroding Cerebras's process advantage within a few years, and 3) Exploring optical interconnects for ultimate bandwidth. Commercially, Cerebras is transitioning from a hardware vendor to a service provider, facing the immense challenge of building high-power, specialized data centers to meet large contracts (e.g., 250MW/year from 2026–2028). In conclusion, the AI inference era presents a fundamental architectural trade-off. Cerebras opts for extreme physical optimization for low-latency, single-task performance, while Nvidia prioritizes versatility and massive cluster throughput. The path forward remains uncertain, with technology and business models still evolving in the race toward advanced AI.

marsbit58m ago

Crossing the 'Memory Wall': The Wafer-Level Revolution and Computing Power Routes in the AI Inference Era

marsbit58m ago

Has Bitcoin's 'Rebound Ended', Officially Entering the Late Bear Market Phase?

**Title: Has Bitcoin's Rebound Ended, Entering the Late Bear Market Phase?** **Summary:** Bitcoin's price has declined by 13% this week, signaling a potential return to late-stage bear market conditions. The price fell to around $67k, positioned between the Realized Price and Realized Cap Weighted Average. For the first time since early 2022, the Short-Term Holder cost basis has dropped below this key average, confirming a hallmark of late-cycle bear markets. Profitability metrics have collapsed sharply. The 7-day average of the Realized Profit/Loss ratio plummeted from a local high of 3.16 to 0.29, mirroring the February panic sell-off. Critically, the 90-day average never breached the threshold of 2, indicating the recent rally to $82k was a bear market bounce, not a structural shift. Realized losses surged to $1.35 billion daily, with $770 million coming from Long-Term Holders selling at a loss. This accelerating redistribution of supply from weak to strong hands is a necessary but ongoing process for a market bottom. The rally stalled almost precisely at the aggregate cost basis (~$83k) of US spot Bitcoin ETF investors, turning that level into strong resistance and leaving the average ETF holder underwater again. Spot market flows have turned decisively negative, showing sellers are dominating order books despite the price drop. While a significant futures long liquidation event cleared over $400 million in leverage, providing a potential reset, sustained spot demand is yet to materialize. Options markets continue to price in higher future volatility (Implied Volatility) than recent price action (Realized Volatility) has shown, with a persistent skew towards put options, indicating ongoing demand for downside protection. In conclusion, multiple metrics point to a fragile market structure. Resistance at the ETF cost basis, accelerating realized losses, dominant spot selling, and cautious options pricing all suggest the bear market trend persists. A sustainable recovery likely requires a resurgence of spot demand, ETF holders returning to profit, and a clear reduction in selling pressure.

marsbit59m ago

Has Bitcoin's 'Rebound Ended', Officially Entering the Late Bear Market Phase?

marsbit59m ago

TechFlow Intelligence Agency: Anthropic Calls for Global Pause in AI Development While Preparing for Trillion-Dollar IPO; SpaceX IPO Roadshow Heats Up, But S&P 500 Rejects Fast-Track Inclusion

In today's TechFlow Intelligence Briefing, several major tech stories highlight a growing theme of trust and credibility gaps across AI, crypto, and finance. AI company Anthropic has publicly called for a global pause in AI development, citing risks from Claude's "recursive self-improvement." Ironically, this coincides with reports the company is preparing for a massive IPO targeting a near $1 trillion valuation. This perceived hypocrisy, coupled with widespread user complaints about Claude's declining performance, is sparking debate over whether the safety warning is genuine or a competitive tactic. Meanwhile, in a substantive security move, Anthropic open-sourced a framework for AI-powered vulnerability discovery. In the crypto market, Bitcoin's price drop below $61,000 triggered over $1.16 billion in liquidations, flipping the market into a state where more BTC is held at a loss than at a profit, a historical bearish signal. On the corporate front, SpaceX's highly anticipated IPO is generating immense Wall Street excitement, with Goldman Sachs projecting 100x revenue growth by 2030. However, the S&P 500 has refused to fast-track the company's inclusion post-IPO, potentially limiting immediate institutional demand. Separately, ByteDance's AI app Doubao lost over 6 million monthly active users after introducing a subscription model, highlighting the challenges of AI monetization. Other notable developments include Nvidia certifying HBM4 memory from Samsung, SK Hynix, and Micron; Cloudflare's acquisition of front-end tooling company VoidZero; and its CEO warning that bot traffic now exceeds human traffic online. The underlying narrative connects these events: a trust crisis. From AI firms' contradictory actions and crypto volatility to the clash between SpaceX's hyped narrative and institutional rules, a pattern is emerging where stated intentions and actual practices are increasingly misaligned.

marsbit1h ago

TechFlow Intelligence Agency: Anthropic Calls for Global Pause in AI Development While Preparing for Trillion-Dollar IPO; SpaceX IPO Roadshow Heats Up, But S&P 500 Rejects Fast-Track Inclusion

marsbit1h ago

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1.6k Total ViewsPublished 2024.04.04Updated 2024.12.03

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54 Total ViewsPublished 2024.12.17Updated 2024.12.17

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While the concept of Agent S is fundamentally innovative, specific information about its creator remains elusive. The creator is currently unknown, which highlights either the nascent stage of the project or the strategic choice to keep founding members under wraps. Regardless of anonymity, the focus remains on the framework's capabilities and potential. Who are the Investors of Agent S? As Agent S is relatively new in the cryptographic ecosystem, detailed information regarding its investors and financial backers is not explicitly documented. The lack of publicly available insights into the investment foundations or organisations supporting the project raises questions about its funding structure and development roadmap. Understanding the backing is crucial for gauging the project's sustainability and potential market impact. How Does Agent S Work? At the core of Agent S lies cutting-edge technology that enables it to function effectively in diverse settings. 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713 Total ViewsPublished 2025.01.14Updated 2025.01.14

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