Japan Maintains its Policy Rate, Inflation Forecasts Rise Slightly, and Crypto Market Walks Silently

TheNewsCryptoPublished on 2026-01-23Last updated on 2026-01-23

Abstract

The Bank of Japan (BOJ) has maintained its policy rate at 0.75%, a decision widely anticipated by markets. The central bank also slightly raised its inflation forecast for fiscal 2026 to 1.9%, citing balanced economic and price conditions. Despite these developments, the global crypto market remained largely stable, though its total capitalization dipped slightly to $3.03 trillion. Major cryptocurrencies like Bitcoin and Ethereum saw minor declines, failing to hold key support levels. Meanwhile, U.S. equity markets posted gains, potentially providing underlying support to crypto assets. Analysts note persistent volatility across financial markets amid uncertain macroeconomic conditions.

The Bank of Japan has decided to keep its policy rate unchanged at 0.75%. There is a slight increase in projected inflation, but optimism is sufficient for the growth of Japan. Meanwhile, the crypto market has remained largely unchanged, with possible support from US markets, which closed on a high note again.

Rate and Projected Inflation in Japan

The Bank of Japan (BOJ) last revised its rate from 0.50% to 0.75% in December 2025. It has now decided to keep it unchanged following the 2-day meeting, which ended on Friday. A report by Reuters has underlined that this was an expected decision, also mentioning that a proposal to hike the rate was supported by Board member Hajime Takata. The proposal didn’t find enough takers to process it further.

BOJ has also revised the consumer inflation forecast to 1.9% for fiscal year 2026. It was earlier 1.8%. The revision has been drawn after noting a balanced level between economic and price outlook. BOJ, in a report, has said that wages and prices rising moderately in tandem will be sustained, allowing inflation to rise moderately.

Reaction of Global Crypto Market

No matter the region, every financial decision taken becomes one of the key factors that affect the global crypto market. The recent decision by BOJ is no different, considering the crypto market has remained steady as it was yesterday. Fred Neumann, chief Asia economist at HSBC in Hong Kong, saying that the outlook of the central bank hints at growing hawkishness has possibly fueled the support for the crypto market.

The crypto market cap has declined, though. It is down by 0.26% to $3.03 trillion, with the FGI rating shifting to 34 points and the Altcoin Index tilting towards 29 points. BTC and ETH have lost their much-anticipated support levels of $90k and $3k, respectively. Bitcoin tokens are now trading at $89,454.23, and Ethereum tokens are exchanging hands at $2,963.79.

US Markets Recover, Again!

Two US indexes, Nasdaq and S&P 500, showed optimistic signs yesterday. They once again closed on a high of 0.91% and 0.55%, respectively. Dow also surged by 0.63% – most of it being credited to Trump’s U-turn on Greenland tariffs. Nevertheless, this optimism has possibly added as a supportive component for the crypto market to sustain its movement on the price chart.

Volatility remains persistent across the crypto market and every other industrial segment. Gregg Abella, CEO at Investment Partners Asset Management, has articulated the ongoing situation by saying that one does not know if it would be a Christmas morning or Friday the 13th.

Highlighted Crypto News Today:

South Korean Prosecutors Probe $49M Bitcoin Loss From State Custody

The Higher Bitcoin Goes, The Less Institutions Want It? Coinbase Executive Weighs In

Coinbase Head of Institutional Strategy John D'Agostino states that institutions which previously bought Bitcoin at higher prices are showing increased interest as its price drops to around $60,000. He notes no signs of panic selling or major liquidation risks among large investors; instead, many, including family offices and sovereign wealth funds, see the correction as a buying opportunity. D'Agostino emphasizes that institutional interest often grows when prices fall, reflecting a long-term holding strategy. Despite recent market volatility and geopolitical tensions, exposure via spot Bitcoin ETFs remains high, exceeding $750 billion. He attributes price swings to normal commodity-like behavior and believes current market infrastructure is stronger than in past downturns. Bitcoin was trading near $63,800 at the time of reporting.

bitcoinist22m ago

The Higher Bitcoin Goes, The Less Institutions Want It? Coinbase Executive Weighs In

bitcoinist22m ago

Bitmine Continues Aggressive Ethereum Accumulation as Others Scale Back

Bitmine, an Ethereum treasury, accumulated 126,971 ETH last week, reinforcing its aggressive accumulation strategy amid a broader market downturn. Its holdings now total $9.6 billion in assets, including 5.54 million ETH—representing 4.59% of the total supply—203 Bitcoin, stakes in Beast Industries and Eightco Holdings, and cash. The company has staked approximately 4.72 million ETH, generating significant yields and potential annual income of around $230 million. Chairman Thomas 'Tom' Lee views the market decline as the beginning of a "crypto spring," driven by anticipated rising demand for decentralized networks like Ethereum from advancing AI systems. Unlike many other treasury firms that have halted or reversed accumulation, Bitmine continues to acquire. It recently announced plans to raise capital via a public stock offering, with proceeds potentially used for further ETH purchases, ecosystem investments, and infrastructure expansion. Bitmine now holds the world's second-largest corporate crypto treasury and the largest dedicated Ethereum treasury.

TheNewsCrypto1h ago

Bitmine Continues Aggressive Ethereum Accumulation as Others Scale Back

TheNewsCrypto1h ago

Apple's Desired On-Device AI Sees a Dark Horse Emerge: The First Cognitive Model is Born, 4B Matches GPT-5.4

A Chinese company, Tomorrow's Journey (Nextie), has introduced what it is calling the industry's first "cognitive model" for edge devices. Named New Journey Alpha, this 4-billion-parameter model reportedly matches the performance of trillion-parameter giants like GPT-5.4 in group intelligence tasks such as debate and collective decision-making. The development follows Andrej Karpathy's vision of stripping vast factual knowledge from large language models to retain only a smaller "cognitive core" capable of reasoning, planning, and knowing its own limits. This approach directly addresses the soaring computational costs and token expenses hindering AI's widespread deployment, as highlighted by incidents like Amazon shutting down an internal AI tool due to prohibitive costs. Trained via reinforcement learning on a corpus of academic papers from 1800-2020 to enhance generalization, the model enables three key advancements: 1) Improved decision quality in multi-agent systems, 2) Drastically reduced compute costs, allowing for cost-effective cloud or on-device (e.g., MacBook) deployment, and 3) The feasibility of "proactive" AI agents that act autonomously without user prompts, unlocking new commercial possibilities beyond today's reactive models. Built by the former Microsoft Xiaoice team—known for creating a 3.6B model that outperformed a 65B Llama model—the company is now focusing on the multi-agent systems sector, a field gaining significant investor interest. The model's economic impact is profound; by achieving high-level performance with minimal parameters, it fundamentally alters the cost structure of AI services, challenging the prevailing model of ever-larger parameter counts.

marsbit2h ago

Apple's Desired On-Device AI Sees a Dark Horse Emerge: The First Cognitive Model is Born, 4B Matches GPT-5.4

marsbit2h ago

Hoskinson Claims Cardano Can Surpass Bitcoin By Solving Crypto’s Trust Problem

In a June 8 livestream, Cardano founder Charles Hoskinson presented an ambitious long-term vision for the network, framing its mission as solving the global "trust problem" rather than merely competing for crypto market share. He argued that the cryptocurrency industry's core purpose is to reduce the massive annual costs associated with trusted third parties in finance and commerce through "verifiable reflexivity"—where transactions carry their own proof of correctness. Hoskinson outlined four key requirements for this goal: a decentralized engine (via Ouroboros), the right accounting model (extended UTXO), modular expansion (exemplified by partner chains like Midnight), and robust decentralized governance. He emphasized that Cardano's design aims to avoid dependency on intermediaries for reconciliation and scale for specialized applications through technologies like Hydra. While governance structures are still developing, Hoskinson claimed that if Cardano succeeds in building this trust infrastructure, ADA could become the "currency of global trust" and has the potential to eventually surpass Bitcoin. He stressed that for Cardano to reach its next level, it must prove it is a self-healing system capable of surviving even a loss of confidence in its founder.

bitcoinist2h ago

Hoskinson Claims Cardano Can Surpass Bitcoin By Solving Crypto’s Trust Problem

bitcoinist2h ago

OpenAI's 'Blueprint for the Future': Making AI Beneficial for Every Person on the Planet

A new transformative technology emerges every few generations. OpenAI draws a parallel with the advent of electricity in the 1920s, which initially brought convenience but ultimately enabled unprecedented progress in medicine, engineering, and living standards by empowering people to create new possibilities. AI is poised to recreate this phenomenon. Its true significance lies not in the technology itself, but in what people can achieve with it—from understanding a medical bill or starting a business to aiding scientific discovery. OpenAI believes AI should be universally accessible, allowing everyone to use it according to their own needs. This future, however, is not guaranteed. While transformative tech can centralize power, OpenAI's philosophy is that AI must serve humanity, augmenting human capabilities and broadly distributing its benefits. The company's first commitment is to build AI for human service, aiming to empower the many rather than concentrate power in a few. Safety, alignment with human intent, and oversight are paramount. OpenAI is optimistic about AI's potential to expand human welfare but remains clear-eyed about risks. The goal is to help people achieve more, not to replace them. Full automation is not the desired future; human judgment, values, and direction will become even more critical. OpenAI outlines three core goals: 1. Build automated AI researchers to accelerate and increasingly automate the research process itself, maintaining close human collaboration. The internal projection is that by March 2028, a significant portion of their research will be conducted by AI systems working alongside human researchers. 2. Accelerate economic development by advancing science, boosting productivity, and fostering growth, while ensuring the fruits are widely shared. 3. Provide a personal AGI for everyone on Earth, allowing individuals to benefit from this transformative technology in their own way. The company is entering its third phase, moving from foundational AGI research (Phase 1) to product deployment and learning from real-world use (Phase 2). The current challenge is making advanced AI abundant, affordable, safe, practical, and usable for all individuals and organizations. OpenAI concludes that a widely distributed power structure leads to a more resilient, adaptable, and free society. A positive AI future should not be controlled by a handful of entities but built, benefited from, and owned by many. If realized correctly, AI can become a cornerstone for enhancing global productivity, creativity, scientific advancement, and economic opportunity, fulfilling the mission to ensure AGI benefits all of humanity.

marsbit3h ago

OpenAI's 'Blueprint for the Future': Making AI Beneficial for Every Person on the Planet

marsbit3h ago

Trading

Spot

Futures

Hot Articles

What is $BANK

Bank AI: A Revolutionary Step in the Future of Banking Introduction In an era marked by rapid advancements in technology, Bank AI stands at the intersection of artificial intelligence (AI) and banking services. This innovative project seeks to redefine the financial landscape, enhancing operational efficiency, security measures, and customer experiences through the power of AI. As we embark on this exploration of Bank AI, we will delve into what the project entails, its operational dynamics, its historical context, and significant milestones. What is Bank AI? At its core, Bank AI represents a transformative initiative aimed at integrating artificial intelligence into various banking operations. This project harnesses the capabilities of AI to automate processes, improve risk management protocols, and enhance customer interaction through personalized services. The primary objectives of Bank AI include: Automation of Banking Functions: By leveraging AI technologies, Bank AI aims to automate routine tasks, reducing the burden on human resources and enhancing efficiency. Enhanced Risk Management: The project utilises AI algorithms to predict and identify risks, thereby fortifying security measures against fraud and other threats. Personalization of Banking Services: Bank AI focuses on offering tailored financial products and services by analysing customer data and behaviours. Improving Customer Experience: The implementation of AI-driven solutions, such as chatbots and virtual assistants, aims to provide users with more human-like interactions, revolutionising the way customers engage with banks. With these goals, Bank AI positions itself as a crucial player in rendering banking more efficient, secure, and user-centric. Who is the Creator of Bank AI? Details regarding the creator of Bank AI remain unknown. As such, no specific individual or organisation has been identified in the available information. The anonymity surrounding the project's inception raises questions but does not detract from its ambitious vision and objectives. Who are the Investors of Bank AI? Similar to the project's creator, specific information regarding the investors or supporting organisations of Bank AI has not been disclosed. Without this information, it is challenging to outline the financial backing and institutional support that might be propelling the project forward. Nevertheless, the importance of having a robust investment foundation is pivotal for sustaining development in such an innovative field. How Does Bank AI Work? Bank AI operates on several innovative fronts, focusing on unique factors that differentiate it from traditional banking frameworks. Below are key operational features: Automation: By applying machine learning algorithms, Bank AI automates various manual processes within banks. This results in reduced operational costs and allows human workers to redirect their efforts towards more strategic activities. Advanced Risk Management: The integration of AI into risk management practices equips banks with tools to accurately predict potential threats such as fraud, ensuring that customer information and assets remain secure. Tailored Financial Recommendations: Through continuous learning from customer interactions, the AI systems develop a nuanced understanding of user needs, enabling them to offer tailored advice on financial decisions. Enhanced Customer Interactions: Utilizing chatbots and virtual assistants powered by AI, Bank AI enables a more engaging customer experience, allowing users to have their queries resolved quickly, thus reducing wait times and improving satisfaction levels. Together, these operational features position Bank AI as a pioneer in the banking sector, establishing new benchmarks for service delivery and operational excellence. Timeline of Bank AI Understanding the trajectory of Bank AI requires a look at its historical context. Below is a timeline highlighting important milestones and developments: Early 2010s: The conceptualization of AI integration into banking services began to gain attention as banking institutions recognised the potential benefits. 2018: A marked increase in the implementation of AI technologies occurred when banks started using AI tools like chatbots for basic customer service and risk management systems for improved security handling. 2023: The sophistication of AI continued to advance, with generative AI being introduced for more complex tasks such as document processing and real-time investment analysis. This year marked a significant leap in the capabilities afforded to banks by AI technology. 2024-Current Status: As of this year, Bank AI is on an upward trajectory, with ongoing research and developments poised to further enhance capabilities in banking operations. Continued exploration of AI applications hints at exciting developments yet to come. Key Points About Bank AI Integration of AI in Banking: Bank AI focuses on adopting artificial intelligence to streamline banking processes and improve user experiences. Automation and Risk Management Focus: The project strongly emphasizes these areas, aiming to shift the burden of routine tasks while enhancing security frameworks through predictive analytics. Personalized Banking Solutions: By harnessing customer data, Bank AI enables tailored banking services that cater to individual user needs. Commitment to Development: Bank AI remains committed to ongoing research and development efforts, ensuring its adaptability and ongoing relevance as technology continues to evolve. Conclusion In summary, Bank AI exemplifies a crucial step forward in the banking industry, leveraging artificial intelligence to reshape operational paradigms, enhance security, and promote customer satisfaction. Despite gaps in information surrounding the creator and investors, the clear objectives and functional mechanisms of Bank AI provide a strong foundation for its ongoing evolution. As AI technology continues to advance and merge with the banking sector, Bank AI is well-positioned to significantly impact the future of financial services, enhancing the way we understand and interact with banking.

953 Total ViewsPublished 2024.04.05Updated 2024.12.03

How to Buy BANK

Welcome to HTX.com! We've made purchasing Lorenzo Protocol (BANK) simple and convenient. Follow our step-by-step guide to embark on your crypto journey.Step 1: Create Your HTX AccountUse your email or phone number to sign up for a free account on HTX. Experience a hassle-free registration journey and unlock all features.Get My AccountStep 2: Go to Buy Crypto and Choose Your Payment MethodCredit/Debit Card: Use your Visa or Mastercard to buy Lorenzo Protocol (BANK) instantly.Balance: Use funds from your HTX account balance to trade seamlessly.Third Parties: We've added popular payment methods such as Google Pay and Apple Pay to enhance convenience.P2P: Trade directly with other users on HTX.Over-the-Counter (OTC): We offer tailor-made services and competitive exchange rates for traders.Step 3: Store Your Lorenzo Protocol (BANK)After purchasing your Lorenzo Protocol (BANK), store it in your HTX account. Alternatively, you can send it elsewhere via blockchain transfer or use it to trade other cryptocurrencies.Step 4: Trade Lorenzo Protocol (BANK)Easily trade Lorenzo Protocol (BANK) on HTX's spot market. Simply access your account, select your trading pair, execute your trades, and monitor in real-time. We offer a user-friendly experience for both beginners and seasoned traders.

4.7k Total ViewsPublished 2025.05.09Updated 2026.06.02

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 BANK (BANK) are presented below.