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Coinbase and JPMorgan Feud Over Crypto Rules

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JP Morgan Chase puts contents through its CEO account, it goes viral. But the same content via JPMC account, no one cares (WSJ)

The growing clash between Coinbase and JPMorgan highlights a broader battle over the future of finance. As cryptocurrencies continue to gain mainstream adoption, traditional banking institutions and crypto-native companies are increasingly finding themselves on opposite sides of regulatory and operational debates.

The disagreement between Coinbase, one of the world’s largest cryptocurrency exchanges, and JPMorgan, the largest bank in the United States, reflects competing visions for how digital assets should be integrated into the global financial system. At the heart of the feud are questions surrounding access, compliance, and control.

Cryptocurrency firms argue that existing financial regulations were designed for a different era and often fail to accommodate the unique characteristics of blockchain technology. Coinbase has consistently advocated for clearer and more tailored crypto regulations, arguing that uncertainty stifles innovation and pushes companies to seek opportunities in more crypto-friendly jurisdictions.

JPMorgan, meanwhile, represents the traditional financial sector’s emphasis on risk management, regulatory oversight, and consumer protection.

While the bank has embraced certain aspects of blockchain technology and even developed its own digital asset initiatives, it has remained cautious regarding broader cryptocurrency adoption. Bank executives have frequently warned about risks related to money laundering, fraud, market manipulation, and investor protection within the crypto ecosystem. The latest disagreement centers on how financial institutions should interact with crypto platforms and what rules should govern those relationships.

Coinbase has accused large banks of attempting to preserve their dominance by supporting restrictive policies that make it harder for crypto companies to access banking services. According to crypto advocates, some traditional financial institutions view decentralized finance as a competitive threat that could reduce their control over payments, lending, and asset custody.

JPMorgan and other major banks reject such claims, arguing that strict standards are necessary to protect the integrity of the financial system.

They maintain that cryptocurrency firms should meet the same compliance requirements as traditional financial institutions. From their perspective, regulatory consistency is essential to preventing illicit activity and ensuring financial stability. The dispute comes at a time when digital assets are becoming increasingly intertwined with traditional finance. Bitcoin exchange-traded funds have attracted billions of dollars in investment, major asset managers have entered the crypto market, and governments around the world are developing frameworks for digital assets.

As these developments accelerate, disagreements over regulation have become more consequential. Investors are watching the conflict closely because its outcome could shape the next phase of crypto adoption. If regulators side more closely with crypto companies, the industry could gain easier access to banking services and experience faster growth. On the other hand, if regulators adopt a more conservative approach favored by large financial institutions, crypto firms may face higher compliance costs and slower expansion.

The debate also raises important questions about competition. Supporters of Coinbase argue that innovation thrives when new entrants are allowed to challenge established players. They believe blockchain technology has the potential to lower costs, increase financial inclusion, and create more efficient markets. Critics counter that innovation must be balanced with safeguards that protect consumers and preserve trust in financial institutions.

The Coinbase-JPMorgan feud is about more than two companies. It represents a larger struggle over who will help define the rules of the next financial era. As cryptocurrencies continue to mature and attract institutional interest, policymakers will face increasing pressure to strike a balance between fostering innovation and maintaining stability. The decisions made in the coming years could determine how deeply digital assets become embedded in the global economy and who benefits most from that transformation.

MicroStrategy Sells Bitcoin for the First Time in Years

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For years, MicroStrategy stood as the ultimate symbol of corporate conviction in Bitcoin. Under the leadership of executive chairman Michael Saylor, the company transformed itself from a traditional business intelligence software firm into the largest corporate holder of Bitcoin in the world.

Through market crashes, regulatory uncertainty, and extreme volatility, the company consistently accumulated more BTC, earning a reputation for never selling. That is why reports that MicroStrategy has sold Bitcoin for the first time in years have sent shockwaves through both the cryptocurrency market and the broader financial community. The significance of such a move extends far beyond the value of the Bitcoin sold.

MicroStrategy’s strategy has long been viewed as a vote of confidence in Bitcoin’s long-term future. The company’s relentless accumulation inspired numerous corporations, institutional investors, and even governments to consider Bitcoin as a treasury reserve asset. As a result, any indication that MicroStrategy may be reducing its holdings is closely scrutinized by investors seeking clues about the future direction of the market.

The sale comes at a particularly sensitive time for the cryptocurrency industry. Bitcoin has experienced heightened volatility throughout 2026, driven by shifting macroeconomic conditions, changing monetary policy expectations, and fluctuating demand from spot Bitcoin exchange-traded funds.

While institutional adoption remains strong compared to previous market cycles, concerns have emerged regarding ETF outflows, profit-taking by large holders, and a more cautious investment environment. For supporters of Bitcoin, the key question is whether the sale represents a strategic adjustment or a fundamental change in MicroStrategy’s outlook. Many analysts argue that a limited sale should not necessarily be interpreted as a loss of confidence.

Large corporations routinely manage assets for liquidity needs, debt obligations, tax considerations, or broader treasury optimization. In that context, selling a small portion of holdings may simply reflect prudent financial management rather than a bearish view on Bitcoin. Nevertheless, perception often matters as much as reality in financial markets. Because MicroStrategy built its identity around the idea of holding Bitcoin indefinitely, any sale risks being interpreted as a symbolic shift.

Traders and investors may wonder whether the company believes Bitcoin has reached a valuation level that justifies taking profits or whether it anticipates greater market turbulence ahead. The development also raises broader questions about corporate Bitcoin strategies. During the past several years, many firms embraced digital assets as part of their balance sheet management. MicroStrategy was the pioneer and remains the largest example of this trend.

If even the most committed corporate Bitcoin holder is willing to sell, other companies may feel more comfortable adopting flexible treasury policies rather than adhering to a strict buy-and-hold approach.

Bitcoin’s investment case has evolved significantly since MicroStrategy first began accumulating the asset in 2020. The emergence of spot Bitcoin ETFs, growing institutional participation, expanding derivatives markets, and increasing regulatory clarity have transformed the ecosystem. Bitcoin is no longer viewed solely as a speculative asset; it is increasingly treated as a mainstream financial instrument.

In such an environment, active portfolio management may become more common, even among long-term believers. The market’s reaction will depend on the scale and purpose of the sale. If the transaction proves to be relatively small and linked to routine corporate needs, investor concerns may fade quickly. However, if it marks the beginning of a broader shift in strategy, it could signal a new chapter not only for MicroStrategy but also for the relationship between corporations and Bitcoin.

SoftBank’s AI-Fueled Surge Lifts Nikkei Above 67,000, Overtakes Toyota as Japan’s Most Valuable Company

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Japan’s stock market entered a new phase of the artificial intelligence boom on Monday as the benchmark Nikkei 225 breached the 67,000 mark for the first time in history, driven overwhelmingly by AI-linked companies and a dramatic surge in shares of SoftBank Group, which overtook Toyota Motor as the country’s most valuable listed company.

The milestone underscores how investor enthusiasm is increasingly shifting away from Japan’s traditional industrial champions toward companies positioned at the center of the global AI infrastructure race.

The Nikkei climbed as much as 1.4% to a record 67,231.28 before ending the session at 66,934.33, up 0.9%. Yet the headline gain masked a highly concentrated rally. SoftBank alone accounted for more than the entire net increase in the index, highlighting how a handful of AI beneficiaries are now exerting outsized influence over Japanese equities.

Shares of the technology investment giant jumped 14%, adding roughly 845 points to the Nikkei. By contrast, the index itself rose 605 points, meaning the broader market was considerably weaker than the benchmark’s headline performance suggested.

The rally propelled SoftBank’s market capitalization to approximately ¥48.8 trillion ($306 billion), surpassing Toyota’s ¥45.9 trillion after the automaker’s shares fell 4.5%.

The changing rankings carry symbolic importance. For decades, Toyota represented the pinnacle of Japan’s corporate sector, embodying the country’s manufacturing strength and export prowess. SoftBank’s ascent signals that investors believe the next era of value creation will come from AI infrastructure, computing power, and digital platforms rather than automobiles and traditional industrial production.

At the center of investor enthusiasm is SoftBank founder Masayoshi Son’s aggressive push into artificial intelligence. Over the weekend, the company unveiled plans to invest about €75 billion ($87 billion) over five years to help build AI infrastructure in France, one of the largest technology investment commitments ever announced in Europe.

The French initiative forms part of a broader strategy that is transforming SoftBank into one of the world’s largest AI infrastructure investors. The company has already committed tens of billions of dollars to OpenAI, benefits from its controlling stake in Arm Holdings, and continues to expand investments spanning data centers, chips, cloud infrastructure, and next-generation computing.

For investors, SoftBank represents a leveraged bet on global AI adoption.

The company’s valuation has been boosted not only by the soaring worth of Arm and OpenAI but also by expectations that demand for AI computing capacity will remain robust for years as governments and corporations race to build data centers capable of training and deploying advanced AI models.

The strength of that narrative was evident across Japanese technology stocks. Electronic components manufacturer Murata Manufacturing surged 9%, benefiting from expectations that AI server demand will create new opportunities across semiconductor supply chains and advanced electronics manufacturing.

Analysts say the market is broadening beyond obvious AI winners such as chipmakers and cloud providers, with investors increasingly identifying secondary beneficiaries throughout the technology ecosystem.

“Despite concentration risks and rising volatility, the AI theme continues to be underpinned by strong earnings,” strategists at Jefferies wrote in a research note.

“This rally is fundamentally driven, and the message is clear: follow the earnings momentum.”

That earnings story has become important as investors attempt to distinguish the current AI boom from previous technology bubbles. Unlike the dot-com era, many of today’s leading AI companies are generating substantial revenue growth and attracting significant capital commitments from enterprise customers.

Still, Monday’s market action also revealed growing divisions beneath the surface. The broader Topix index fell 0.4%, illustrating that much of the market remains disconnected from the AI rally. Among the Tokyo Stock Exchange’s 33 industry groups, only seven advanced, while most sectors declined.

The divergence was especially apparent in the automotive sector. Auto shares dropped 3.8%, making them among the weakest performers of the day. The decline reflects concerns that rising geopolitical uncertainty, trade tensions, and slowing global growth could weigh on traditional manufacturing businesses even as technology firms benefit from AI-related spending.

Market breadth was similarly narrow. Only 70 of the Nikkei’s 225 constituent companies gained ground, while 155 declined.

That imbalance indicates that investors are becoming increasingly selective, concentrating capital into a relatively small group of AI-linked companies while reducing exposure to sectors viewed as vulnerable to economic headwinds.

Geopolitical uncertainty remains one of those headwinds.

Both the Nikkei and Topix reached record highs last week amid optimism that the United States and Iran could move closer to a peace agreement. However, negotiations remain fragile, with Washington and Tehran continuing to disagree on several major issues.

“Uncertainty regarding the situation in the Middle East seems to be intensifying,” said Maki Sawada, a strategist at Nomura Securities.

The region remains critical to global energy markets, and any prolonged disruption could reignite inflation concerns, pressure corporate margins, and complicate monetary policy decisions worldwide. Those concerns help explain why investors continue to show caution toward large segments of the market even as AI-related shares surge.

Interestingly, not all semiconductor-related stocks participated in Monday’s rally. Chip-testing equipment maker Advantest fell 1.9%, while cable and electronics supplier Fujikura declined 2%.

Their weakness highlights another emerging feature of the AI trade: investors are differentiating between companies directly benefiting from spending growth and those whose exposure is viewed as more indirect.

The broader significance of Monday’s trading extends beyond Japan. Global equity markets are undergoing a historic reallocation of capital toward AI infrastructure, semiconductors, data centers, and cloud computing. Similar trends are visible in the United States, where companies tied to AI have accounted for a disproportionate share of stock market gains over the past two years.

Japan’s market is now following the same pattern, with SoftBank becoming the country’s clearest proxy for the AI investment cycle.

The company’s rise above Toyota marks more than a shift in market capitalization rankings. It is seen as a reflection of a changing view among investors about where future economic value will be created. For much of the past half-century, Japan’s stock market was defined by manufacturers, exporters, and industrial giants. Increasingly, it is being shaped now by companies building the infrastructure required to power artificial intelligence.

Uber and Autobrains Plan to Test Self-Driving Taxis in Munich

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The race to commercialize autonomous transportation continues to accelerate as ride-hailing giant Uber Technologies and autonomous driving technology developer Autobrains announce plans to begin testing self-driving taxis in the German city of Munich.

The initiative represents another significant step toward the broader adoption of autonomous mobility services in Europe and highlights the growing collaboration between transportation platforms and artificial intelligence-driven vehicle technology firms. The planned pilot program is expected to evaluate how autonomous vehicles can safely operate in complex urban environments while providing passengers with a convenient and reliable transportation option.

Munich, known for its advanced infrastructure, strong automotive industry presence, and supportive technology ecosystem, offers an ideal testing ground for next-generation mobility solutions.

The city is also home to several major automotive manufacturers and research institutions, making it a natural location for innovation in transportation technology. For Uber, the partnership reflects a long-term strategy to integrate autonomous vehicles into its ride-hailing network. The company has invested heavily in self-driving initiatives over the years, recognizing that automation could significantly reduce operating costs while increasing transportation accessibility.

Human drivers currently represent one of the largest costs associated with ride-hailing services. By introducing autonomous vehicles, Uber aims to improve efficiency, expand service availability, and potentially lower fares for customers over time. Autobrains brings specialized expertise in autonomous driving software powered by artificial intelligence.

Unlike some competitors that rely heavily on high-definition maps and expensive sensor arrays, the company has focused on creating systems capable of understanding and responding to real-world driving conditions in a more adaptive manner. This approach seeks to improve scalability and reduce deployment costs, two critical challenges facing the autonomous vehicle industry.

The Munich tests will likely focus on collecting real-world operational data and validating the performance of autonomous systems under various traffic, weather, and road conditions. Urban environments present numerous challenges for self-driving technology, including pedestrians, cyclists, construction zones, and unpredictable driver behavior. Successfully navigating these situations is essential before autonomous taxi services can be deployed at a larger scale.

The announcement also underscores Europe’s increasing importance in the autonomous mobility sector.

While much of the early development and testing of self-driving vehicles occurred in the United States and China, European cities are becoming attractive locations for pilot programs due to their advanced regulatory frameworks and emphasis on sustainable transportation. Governments across the continent are exploring ways to integrate autonomous technologies into broader smart-city initiatives aimed at reducing congestion, improving safety, and lowering emissions.

Despite the promise of self-driving taxis, challenges remain. Regulators must ensure that autonomous systems meet rigorous safety standards, while companies must address public concerns regarding reliability, liability, and cybersecurity. Building public trust will be just as important as achieving technological milestones. Any large-scale deployment will depend on demonstrating that autonomous vehicles can operate at least as safely as human drivers.

If the Munich pilot proves successful, it could pave the way for wider deployment across Germany and other European markets. The collaboration between Uber and Autobrains reflects a broader transformation underway in the transportation industry, where artificial intelligence, automation, and digital platforms are converging to reshape how people move through cities.

As autonomous technology continues to mature, partnerships like this one may help bring the vision of self-driving taxi networks closer to everyday reality. The Munich tests represent more than a local experiment; they are another milestone in the global effort to redefine urban mobility for the future.

The Fastest Way to Copy Top Traders on Base  

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Copying a top trader on Base now takes about two minutes of setup, no browser extension, no seed phrase to manage. Banana Gun Pro handles the wallet for you, surfaces the 50 best-performing wallets for any token in a single widget, and supports block 0 copy trading on Base via Flashblocks, so your buy can land in the same block as the target trader. If you have watched a wallet flip a 10x while you were still approving a MetaMask transaction, this closes that gap.

How Copy Trading on Base Actually Works

Copy trading mirrors another wallet’s buys automatically, without you touching anything. Base changes the latency side meaningfully: it runs on roughly 2-second blocks, subdivided into ten Flashblock sub-blocks, each about 200ms. Banana Gun Pro supports block 0 copy trading by tapping into these Flashblocks, which means your buy can land in the same block as the original trade rather than a block behind. That 200ms figure describes Base’s sub-block granularity, not a guaranteed execution time for your specific trade. What it means in practice: your order goes in at the earliest preconfirmation point available, before a full block is finalized. On tokens where price moves in the first few seconds after a whale entry, that head start is the whole point. The difference between block 0 and block 1 entry can be the difference between getting in at launch price and chasing a token already up 30%.

For a deeper look at how wallet mirroring works across chains, see what is copy trading and how wallet mirroring works across multiple blockchains.

Getting In Without MetaMask

The usual onboarding friction for DeFi tools is the wallet setup: install MetaMask, write down 12 words, fund a new address, add Base network manually. Banana Gun Pro skips all of it.

You log in at pro.bananagun.io/app using Privy, which lets you authenticate with Google, Twitter, or Telegram. Your private keys are generated locally in your browser, shown to you once, and never transmitted off your device. This is a non-custodial setup, meaning the platform does not hold your funds, but you also do not need to install anything or manage a browser extension. The initial funding step is also simpler than traditional DeFi: once logged in, you deposit ETH on Base directly to your Privy wallet address, no bridging wizard, no chain-switching required.

One rule: always use the same login method. Switch from Google to Twitter and you create a second account with a separate wallet. Once you are in, fund your Base wallet with ETH on Base for gas.

Finding Wallets Worth Copying: The Top Traders Widget

Banana Gun Pro includes a Top Traders widget that surfaces the 50 highest-PNL wallets for any token you search. Hover over any wallet address in that list and a PNL card appears showing the trader’s realized gains, open positions, and recent activity. From that same card, you can start copying that wallet with one click.

The widget also flags wallet labels: developer, bundler, sniper, pump.fun buyer, dev connected, cluster, top holders. These labels matter more than the raw PNL number. A developer wallet or a bundler may show spectacular gains precisely because they created the token or held pre-launch allocation. Copying one of those wallets does not replicate their edge; it just puts you in the same trades late. Focus on wallets without those flags, with a clean recent trade history across multiple tokens, not just one outsized win. A wallet that has profited consistently on six different tokens over 30 days carries far more signal than one that hit a single 50x and nothing else.

Setting Up a Copy Trade: Simple vs Advanced Mode

Simple mode asks for the target wallet address, a MAX BUY per transaction, a SPEND LIMIT (the total your bot will spend across all copies of that target), slippage tolerance, and an MEV tip. That last setting tells the network how much extra you are willing to pay to get your transaction included quickly. Set it too low and your trade may land a block late; set it too high and you eat into your edge on smaller trades.

Advanced mode adds Buy Only Once (copies the target into a token once, then stops), Buy Percentage, Buy Fixed, Copy Sell, and market cap filters to block tokens already beyond a size where meaningful upside is unlikely.

Presets save an advanced config for reuse. Once a copy is live, the Copy Trade Overview shows Active, History, and Blocked tabs. Blocked Tokens prevents re-entry: when Buy Only Once fires, that token is blocked automatically so the bot does not enter the same coin twice.

The Risk You Cannot Skip

Copy trading distributes your trades across every move a target wallet makes, including the bad ones. A wallet that has run 15 profitable trades in a row can still rug you on the 16th if the trader decides to exit into your buy. That is called being used as exit liquidity, and it is more common than most guides admit. Exit liquidity events tend to cluster in the first 48 hours after a token launches, when early holders are most motivated to distribute into retail volume.

Before copying anyone, run the wallet through a scanner and check their last 20 to 30 trades. Look for a consistent pattern across multiple tokens, not a single spike. Use the SPEND LIMIT field on every copy: a limit of 0.05 ETH on a new wallet caps your downside at 0.05 ETH regardless of how many trades fire.

The platform gives you the tools; the judgment on which wallets to trust is still yours.

Base DEXes You Are Trading On

On Base, Banana Gun Pro routes across Uniswap v2/v3, Sushiswap v2/v3, Baseswap v2/v3, Aerodrome, and Pancakeswap v2/v3 automatically. You do not pick the DEX manually; the bot selects the best available route for the token you are copying into. Aerodrome handles a significant share of Base native token volume, so having it in the routing stack matters for newer launches that have not yet migrated to Uniswap v3. Base is an EVM chain, which means there are no sniping-DEX restrictions of the kind you find on Solana, so any token listed on those DEXes is available for copy trading without extra configuration. Multi-hop routing also means the bot can fill your order across two pools in the same transaction when single-pool liquidity is thin. The same copy trade setup is also accessible from the unified Telegram bot at bananagun.io, which covers Base, ETH, SOL, BNB Chain, and more in one session.

Frequently Asked Questions

How do you copy top traders on Base?

Log in to Banana Gun Pro at pro.bananagun.io using Google, Twitter, or Telegram via Privy. Fund your Base wallet with ETH on Base. Use the Top Traders widget to find a high-PNL wallet, hover the address for a full PNL card, then click to open the Copy Trade widget. Set your target wallet, max buy, and spend limit. The bot then mirrors every qualifying buy that wallet makes on Base.

Do you need MetaMask to copy trade on Base?

No. Banana Gun Pro uses Privy for login, accepting Google, Twitter, or Telegram accounts. Privy generates your private keys locally in your browser, so no browser extension and no seed phrase management is required. The setup is fully non-custodial: your keys never leave your device, and the platform does not hold your funds.

How do you avoid copying scam wallets?

Use the Labels filter in the Top Traders widget to exclude developers, bundlers, snipers, and pump.fun buyers, all of which may show high PNL from insider positioning rather than skill. Then check the wallet’s recent trades independently in a wallet scanner before setting up any copy. Set a SPEND LIMIT on every copy trade so a single bad call cannot drain your full balance.

How fast is copy trading on Base?

Banana Gun Pro supports block 0 copy trading on Base via Base Flashblocks. Base divides its ~2-second blocks into ten ~200ms sub-blocks, and Banana Gun uses this to submit your copy trade at the earliest preconfirmation point, so your buy can land in the same block as the target trader’s entry. This is not a guaranteed 200ms execution time; it describes the sub-block granularity that makes block 0 entry possible.