China’s PBOC Injects $22 Billion As M2 Surges — A Tailwind For Crypto Markets?

bitcoinistPublished on 2025-06-22Last updated on 2025-06-22

Abstract

In an interesting development, China has now injected RMB 161.2 billion ($22.4 billion) into its economy in a move that...

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

In an interesting development, China has now injected RMB 161.2 billion ($22.4 billion) into its economy in a move that could have global financial ripple effects. This event comes amidst an ongoing extensive correction in the crypto market that has sparked speculations on the viability of the current bull market run.

Crypto Market Set For Rebound As China Restarts Money Supply Growth 

In an Open Market Operations announcement on June 20, the People’s Bank of China (PBOC) stated intentions to inject RMB 161.2 billion into the economy through a seven-day reverse repo operations at a 1.40% interest rate. For context, reverse repos are short-term liquidity tools in which the central bank purchases securities from commercial banks with an agreement to sell them back at a later date, thereby temporarily boosting liquidity in the banking system.

Interestingly, this latest injection is part of a broader monetary easing trend observed in China’s recent policy stance. Notably, on May 7, the PBOC implemented a 0.5 percentage point reduction in the reserve requirement ratio (RRR), a move that freed up approximately RMB 1 trillion ($138 billion) in long-term liquidity, effectively coinciding with a Bitcoin price surge above $97,000 on that day and new all-time high a few weeks after.

Crypto
Source: @TedPillows on X

However, unlike the RRR cut which had more enduring liquidity implications, the latest RMB 161.2 billion injection via reverse repo is designed for short-term liquidity management. Nevertheless, popular crypto analyst and key opinion leader Ted Pillows explains it is a strong indicator that China’s M2 money supply is now trending upward again after peaking in Q1 2025.

Generally, an increase in M2 signals expanding liquidity, often viewed as a long-term bullish indicator for both traditional and digital asset markets. Considering the ongoing crypto market correction, China’s latest monetary intervention is a positive signal reinforcing the potential of bullish resurgence in the coming weeks.

US Fed To Follow Suit?

Following the recent announcement by the PBOC, speculation is mounting over whether the US Federal Reserve might adopt similar liquidity-boosting measures. However, according to a report by Scotsman Guide, analysts at Wells Fargo predict that the Fed is likely to maintain its quantitative tightening stance throughout 2025.

At press time, the total crypto market cap is worth $3.14 trillion following a 1.48% decrease in the past day. Daily trading volume has also dropped to $94.96 billion. Meanwhile, Bitcoin, the market leader, is currently valued at $102,784 reflecting losses of 0.74% and 3.39% on the daily and weekly chart respectively. 

China
BTC trading at $102,649 on the daily chart | Source: BTCUSDT chart on Tradingview.com
Featured image from Adobe Stock, chart from Tradingview
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.

Semilore Faleti works as a crypto-journalist at Bitconist, providing the latest updates on blockchain developments, crypto regulations, and the DeFi ecosystem. He is a strong crypto enthusiast passionate about covering the growing footprint of blockchain technology in the financial world.

Trending Cryptos

Related Reads

Claude Accused of Becoming Dumber by the Entire Internet, Anthropic Steps In to Reveal: It’s Not the Model That’s Tricking You

When users complained that Claude was "getting dumber," the root cause wasn't the AI model itself. In an official blog post, Anthropic clarified the critical difference between two key settings in Claude Code: Model and Effort. Model refers to the core "brain"—the fixed, trained weights of a specific AI (like Sonnet, Opus, or Fable). Changing the Model addresses *capability* ("can it do this?"), but its knowledge is static post-training. Effort, however, controls the AI's *approach and thoroughness* for a specific task. A higher Effort level instructs Claude to read more files, run tests, perform verification, and complete multi-step reasoning before responding, significantly increasing its "work output" for that job. Conversely, low Effort leads to quicker, less thorough replies. This distinction explains the March 2024 uproar where users experienced a sudden drop in Claude's performance. The cause was not a model change but Anthropic quietly lowering the *default* Effort setting from "high" to "medium" to reduce latency, which was later reverted. The key insight is that a smaller, capable model (like Sonnet) on high Effort can often outperform a larger, more powerful model (like Opus) on low Effort for many tasks. The article provides a practical troubleshooting framework: if Claude makes an error, first check the context and instructions. If it seems to skip necessary steps or validations, increase Effort. If it diligently attempts the task but fails conceptually or makes consistent factual errors despite good context, then consider switching to a more capable Model. The takeaway is a shift in focus: effective AI programming is less about always choosing the "strongest" model and more about intelligently *orchestrating* models and effort levels—acting like a project manager to assign the right "brain" with the right level of diligence for each job, optimizing both results and cost.

marsbit1h ago

Claude Accused of Becoming Dumber by the Entire Internet, Anthropic Steps In to Reveal: It’s Not the Model That’s Tricking You

marsbit1h ago

Will the Ethereum Foundation Evolve into a 'Mascot'? Diversified Organizations Are Fragmenting Its Functions

The Ethereum Foundation (EF) is undergoing significant internal turmoil and functional erosion. Following its largest-ever layoff of 54 staff (20% of its workforce) and a major organizational restructuring announced in June, its Protocol Support Team has been officially dissolved. This comes alongside the high-profile resignation of key figures like co-executive director Xiaowei Wang, bringing senior departures this year to at least eight. Criticism of EF's rigid structure, opaque decision-making, and perceived lack of a clear value narrative for ETH has intensified within the community. The layoffs have catalyzed the emergence of independent, non-profit organizations like Ethlabs and Ethereum Institutional, founded by former EF researchers and members. These entities are now taking on core functions such as protocol research/development and institutional adoption, effectively fragmenting the EF's traditional leadership role. Concurrently, EF's security team is adapting to technological change, deploying specialized AI agents to audit Ethereum's codebase, which successfully discovered a critical vulnerability (CVE-2026-34219). While EF states AI complements rather than replaces researchers, it signals a potential future shift in its operational model. Faced with these challenges—internal restructuring, talent drain, the rise of competing organizations, and AI integration—the Ethereum Foundation appears to be stepping back from a central commanding role. Analysts and community observers speculate it may increasingly transition towards a symbolic "ecosystem mascot" function, while decentralized initiatives drive Ethereum's future growth and institutional adoption.

marsbit1h ago

Will the Ethereum Foundation Evolve into a 'Mascot'? Diversified Organizations Are Fragmenting Its Functions

marsbit1h ago

Nearly a Hundred Players Rush into Embodied Data: With 4.47 Billion Yuan in Financing in One Year, Who Can Really Make Money by 'Selling Data'?

The domestic embodied AI data industry has attracted nearly 100 players, with 70 focused on data collection and 27 on data infrastructure. In the past year, 15 independent embodied data service providers raised approximately 4.47 billion yuan. Despite this growth, the sector remains early-stage, fragmented, and faces significant challenges. Data collection methods are diverse, categorized into four main routes: teleoperation of real robots, human demonstration without a robot (using motion capture, exoskeletons, etc.), simulation synthesis, and distillation from internet videos. Most companies (43%) adopt hybrid approaches, combining multiple routes, as no single method can meet all training needs. Teleoperation alone is pursued by 31% of players, often by state-owned platforms and robot companies, while newer firms favor asset-light, no-hardware human demonstration. Independent data service providers now form the largest player group (40%), indicating the emergence of a distinct industry segment rather than just a subsidiary function for robot makers. Two-thirds of all players are "embodied-native" startups, while one-third are companies that pivoted from fields like AI data annotation, which are more prevalent in the data infrastructure layer. Current annual industry capacity is estimated at 1.6-1.8 million hours plus 70-80 million data points, with a short-term goal to increase this 15-20 fold within 1-3 years. Data collection factories are spread across 20 provinces in China, concentrated in the Yangtze River Delta, Beijing-Tianjin-Hebei, and Pearl River Delta regions. Financially, the 4.47 billion yuan raised in the past year pales compared to the 43.8 billion yuan raised by the broader embodied intelligence sector in just the first half of 2026, highlighting that data remains a less "sexy" bet for investors. The 15 funded independent providers show clear stratification: a top tier led by a unicorn (Lightwheel Intelligence, 3.1 billion yuan), a middle tier of 11 firms raising tens to hundreds of millions, and an early-stage tier of 3 companies. Sixty-nine investment institutions have participated, but none have made concentrated bets, reflecting uncertainty about viable business models. Over half of these funded companies are less than a year old, most are at pre-A or A rounds, and profitability remains largely unproven. In summary, the embodied data industry has become an independent track creating jobs and local economic activity. However, it is still nascent, with unformed consensus, unsolved problems, and unproven business models. The coming 1-2 years will be a critical validation window to see if companies can build sustainable, profitable businesses purely by "selling data."

marsbit4h ago

Nearly a Hundred Players Rush into Embodied Data: With 4.47 Billion Yuan in Financing in One Year, Who Can Really Make Money by 'Selling Data'?

marsbit4h ago

Trading

Spot

Hot Articles

Discussions

Welcome to the HTX Community. Here, you can stay informed about the latest platform developments and gain access to professional market insights. Users' opinions on the price of S (S) are presented below.

活动图片