Crypto World
Cisco (CSCO) Stock Q2 Earnings: What to Expect from Today’s Report
TLDR
- Cisco reports Q2 fiscal 2026 earnings Wednesday after market close with analysts expecting $1.02 EPS on $14.88 billion revenue
- Stock has surged 37% over the past year fueled by AI infrastructure demand from cloud and hyperscale customers
- UBS analyst forecasts Product orders to grow high single digits while AI orders may hold flat at $1.3 billion sequentially
- Options market implies 6.22% post-earnings move, more than double the stock’s typical 3.01% swing
- Company launched new AI networking chip Tuesday to compete directly with Broadcom and Nvidia
Cisco releases second quarter fiscal 2026 results after the bell Wednesday, February 11. The conference call follows at 4:30 pm ET.
Wall Street expects earnings per share of $1.02, up 8.5% year-over-year. Revenue estimates sit at $14.88 billion, representing 1.55% growth.
The consensus figures match Cisco’s guidance of $1.01 to $1.03 per share on $15.0 billion to $15.2 billion in revenue. With numbers aligned, investors will focus on forward guidance and AI order momentum.
CSCO stock has jumped 37% over the past year. Strong demand for AI networking infrastructure has powered the rally across cloud providers and enterprise customers.
The company announced a new AI networking chip Tuesday, positioning itself against Broadcom and Nvidia. The timing ahead of earnings suggests management wants to emphasize its AI credentials.
Analyst Expectations Point Higher
UBS analyst David Vogt maintains a Buy rating with a $90 price target. His industry checks indicate revenue could top his $15.05 billion estimate on strengthening enterprise markets.
Vogt projects Product orders rising high single digits, down from 13% growth last quarter. He conservatively expects AI orders flat sequentially at $1.3 billion, about 20% of his $6.2 billion full-year target.
Meta Platforms’ recent capex disclosure supports the AI thesis. Meta reported Q4 2025 capex of $22.1 billion, up 49% yearly, with 2026 guidance of $125 billion at the midpoint.
Cisco’s remaining performance obligations reached $42.9 billion in October, up 7.2% year-over-year. This backlog metric will signal whether AI deals continue converting to revenue.
Evercore analyst Amit Daryanani holds a Buy rating with a $100 price target. He highlighted Cisco’s Silicon One products including G200 and P200-based systems following the company’s AI Summit.
Options Activity Signals Volatility
Options traders expect a 6.22% move in either direction after earnings. That’s more than double the 3.01% average post-earnings move over the past four quarters.
The elevated implied volatility reflects investor uncertainty about AI order sustainability. Wall Street assigns a Strong Buy consensus with 10 Buy ratings and three Holds.
The average analyst price target of $91.30 implies roughly 6% upside. TipRanks’ AI Analyst rates the stock Outperform with a $96 target, citing solid fundamentals and positive technical indicators.
Cisco offers a 2.1% dividend yield. Management’s full-year fiscal 2026 guidance calls for $60.2 billion to $61.0 billion in revenue with EPS of $4.08 to $4.14.
The key questions for Wednesday’s call center on AI infrastructure momentum, enterprise spending trends, and whether management feels confident enough to raise full-year targets. Any hints of AI order delays or margin pressure could test the stock’s 37% run.
Investors will also watch for commentary on the competitive landscape after Tuesday’s chip announcement. Cisco disclosed over $2 billion in AI infrastructure orders during fiscal 2025 and has suggested the fiscal 2026 pipeline could exceed $3 billion.
The company ended Q1 with cumulative AI orders topping $2.1 billion. Converting that backlog into recognized revenue remains critical for sustaining growth and justifying the stock’s recent valuation expansion.
New forensic findings from the phone of crypto lobbyist Mauricio Novelli have revealed a draft document suggesting a possible $5 million agreement connected to Argentine President Javier Milei’s promotion of the Libra token, according to local media reports.
The document, recovered from Novelli’s iPhone during a judicial investigation into the Libra crypto scandal, outlines a three-part payment structure totaling $5 million. Screenshots of the note surfaced after expert materials held by prosecutor Eduardo Taiano since November were made public, Argentine outlet El Destape reported.
The draft note was reportedly written in English on Feb. 11, 2025, just three days before Milei posted about the Libra token on X. “Hello friends, this is the final agreement discussed with H,” the text begins, which is believed to refer to crypto entrepreneur Hayden Davis.
The document then details the payment structure. “$1.5M of liquid tokens or cash as an advance. $1.5M in liquid tokens or cash = Milei announces on Twitter that his advisor is Hayden Davis/Kelsier/the Davis family. $2M in tokens or cash = contract signed in person with Milei for blockchain/AI consulting for the Argentine government and/or Javier Milei and review with Javier and Karina,” the text reads.
Notably, the draft note does not specify who would receive the funds.
Related: Argentina turns up the heat in Libra scandal with sweeping asset freeze
Another note outlines crisis message after scandal
Investigators also recovered a separate note drafted on Feb. 16, 2025, two days after the Libra controversy erupted online. The message appears to outline a public statement intended to calm the situation.
“This is what I want for the tweet. This is the only thing that saves him, me, and us,” the note’s translation from Spanish reads. The draft message then states support for the Libra project while denying any financial involvement and attributing accusations of wrongdoing to political opponents.
Authorities believe the message may have been prepared for Milei to post on social media or reference in an interview, according to local media reports.
Novelli was in Dallas during the token’s launch. Call records show he communicated with Milei and his sister Karina shortly before and after the president’s social media post about the token. As the controversy spread online, Novelli also held multiple calls with presidential adviser Santiago Caputo while the government managed the crisis.
Related: Argentine exchange Ripio bets on peso stablecoins amid cautious 2026 outlook
Libra hit $4 billion after Milei post before crashing
In February last year, Milei posted on X about the Libra (LIBRA) memecoin, which briefly reached a $4 billion market capitalization before plunging 94% within hours.
The crash wiped out hundreds of millions in investor funds and prompted opposition lawmakers to call for Milei’s impeachment. Milei later said he had merely “spread the word” about the token rather than promoted it.
Magazine: 2026 is the year of pragmatic privacy in crypto — Canton, Zcash and more
Crypto World
5 Undervalued AI Stocks for 2026: Oracle (ORCL), AMD, Micron (MU), TSMC and Dell Lead the Pack
While the artificial intelligence revolution has minted numerous success stories, many headline-grabbing companies now carry valuations that price in years of perfect execution. The real opportunities may lie with the less glamorous players—those providing the essential building blocks of AI infrastructure, from semiconductors and memory to cloud platforms and enterprise servers. Here are five stocks trading at attractive valuations despite their critical roles in the AI ecosystem.
Oracle’s Transformation Into an AI-Driven Cloud Giant
Once dismissed as a dinosaur in the database industry, Oracle is rewriting its narrative with impressive momentum.
The company’s most recent quarterly results showed total revenue climbing 22%, while cloud revenue surged 44% and Oracle Cloud Infrastructure accelerated an impressive 84% year-over-year. Perhaps most striking was the 325% jump in remaining performance obligations to $553 billion—representing committed future revenue already in the pipeline. Management has confidently raised its fiscal 2027 revenue guidance to $90 billion.
Wall Street may still be valuing Oracle through the lens of its legacy software business, but the reality is dramatically different. As the company’s revenue composition shifts increasingly toward high-margin AI cloud services, the valuation gap becomes more apparent. Should Oracle successfully monetize its massive backlog, significant upside potential remains.
AMD Emerges as a Legitimate Nvidia Competitor
While AMD is not Nvidia, the narrative that it’s perpetually behind is outdated.
Advanced Micro Devices, Inc., AMD
AMD delivered record quarterly revenue of $10.3 billion in Q4 2025, maintaining a healthy 54% gross margin. The data center division generated $5.4 billion in revenue—a 39% increase from the prior year—fueled by robust adoption of both EPYC server processors and Instinct AI accelerators.
The compelling case for AMD lies in its valuation relative to peers and its diversified revenue streams. Unlike pure-play AI chip companies, AMD benefits from multiple growth vectors including AI GPUs, traditional server CPUs, embedded solutions, and general cloud infrastructure expansion. Investors who believe AMD will continue capturing market share in high-performance computing may find today’s valuation attractive.
Micron: The Essential Memory Provider Wall Street Overlooks
Artificial intelligence infrastructure demands massive quantities of high-bandwidth memory, and Micron stands among the select few manufacturers capable of delivering at volume.
First-quarter fiscal 2026 results showcased revenue of $13.6 billion—a 57% year-over-year increase. Micron also achieved record free cash flow and announced increased capital expenditures to expand production capacity for next-generation HBM (high-bandwidth memory).
Memory chip manufacturers historically face cyclical demand patterns, making investors hesitant to assign premium valuations. However, AI workloads may be establishing a structural shift in memory demand that defies traditional cycles. If HBM remains in tight supply as expected, Micron could command a higher valuation multiple than legacy memory producers typically receive.
TSMC: The Indispensable Manufacturer Behind AI’s Biggest Names
TSMC fabricates the cutting-edge processors that enable virtually every significant AI innovation. Companies from Nvidia and AMD to Apple depend entirely on TSMC’s manufacturing capabilities.
Fourth-quarter 2025 results demonstrated revenue growth of 25.5% in U.S. dollar terms, accompanied by a 62.3% gross margin and 54% operating margin. The momentum continued into 2026, with January and February revenue climbing 29.9% compared to the same period in the previous year.
TSMC shares have traditionally traded at a discount to American semiconductor peers due to geopolitical risks associated with Taiwan. Yet from a pure operational and financial perspective, TSMC rivals or exceeds nearly any large-cap chip company. As AI hardware demand keeps advanced node capacity fully utilized, the company’s earnings trajectory appears increasingly robust.
Dell’s Explosive AI Server Growth Flies Under the Radar
Dell has transformed into a critical supplier of AI infrastructure, though many investors haven’t yet recognized this evolution.
Fiscal fourth-quarter 2026 results revealed overall revenue growth of 39%, but the real story was in AI-optimized servers, where revenue exploded 342% to reach $9 billion. Dell entered the current year with an extraordinary $43 billion backlog of AI server orders—providing revenue visibility that few hardware manufacturers can match.
The market continues pricing Dell largely as a personal computer company, creating a disconnect between perception and reality. With AI servers representing an expanding portion of total revenue, the valuation gap between Dell’s legacy image and its actual business composition is becoming harder to ignore. Value-oriented investors seeking AI exposure are increasingly recognizing this opportunity.
Final Thoughts
Oracle, AMD, Micron, TSMC, and Dell may not generate the same headlines as the most prominent AI stocks, but they’re providing the essential infrastructure—processors, memory chips, manufacturing capacity, cloud platforms, and complete systems—that enables the entire AI revolution. For investors concerned that the obvious AI beneficiaries already reflect lofty expectations, these five companies offer an alternative pathway to capitalize on the same secular growth trend.
Bitcoin (CRYPTO: BTC) has hovered near the $71,000 level as large holders ramp up exposure, according to Santiment’s latest weekly assessment. The analysis highlights a renewed shift by wallets that hold 10 to 10,000 BTC, which Santiment described as a bullish signal if it endures. The share of the total supply controlled by this cohort rose to 68.17% from 68.07% a week earlier, signaling a persistent tilt toward big holders even as prices stabilize. Retail demand, meanwhile, remains fragile; the Crypto Fear & Greed Index was in Extreme Fear at 16 on Sunday, underscoring ongoing caution among everyday investors. Bitcoin was around $71,350 at the time of publication, marking a roughly 6% rise over the past week. On the liquidity side, US spot BTC ETFs logged their first five-day inflow streak of 2026, bringing in roughly $767.32 million this week, a reminder that regulated products continue to channel capital into the market.
For context, Santiment’s notes on on-chain behavior were complemented by a broader view of market sentiment. The firm’s observations on wholesale accumulation come as traders weigh the implications of a shift in ownership toward larger addresses. The wholesale activity is particularly relevant when juxtaposed with the persistence of cautious sentiment among retail participants, a dynamic that has characterized much of Bitcoin’s range-bound work over recent months. The interplay between accumulation by whales and the slower pace of retail adoption has created a tug-of-war that market participants are watching closely, especially in areas where technicals align with on-chain signals to form a potential base for price stability.
In a separate frame of reference, the market has been responding to regulatory and product-structure developments that shape how new participants access Bitcoin. ETF inflows, now aided by a broader appetite for regulated exposure, can lend a degree of liquidity that supports price discovery. At the same time, analysts caution that this is not a simple, linear uptrend; episodes of volatility can arise if large holders react to evolving risk cues or if retail conviction fluctuates sharply. The balance between on-chain momentum and macro-driven appetite for regulated products continues to define Bitcoin’s core narrative as the year progresses.
Past on-chain patterns also color expectations. A week earlier, Santiment noted a marked reversal among whales after a sprint of buying earlier in the month. In a Mar. 6 report, the firm highlighted that whales had sold roughly 66% of the Bitcoin they had purchased between Feb. 23 and Mar. 3, just as Bitcoin breached the $70,000 level and briefly touched $74,000. The takeaway is not that whales cannot sustain accumulation, but that their activity can pivot rapidly in response to price moves, implying that a potential bottom may require a clearer alignment of broader market participants around a stable price range. The market’s tendency to reward the consensus with a lag remains a recurring theme that analysts stress when evaluating the durability of any bottom signal. Willy Woo, a prominent on-chain commentator, recently framed Bitcoin’s price action as “solidly in the middle of its bear market through a lens of long-range liquidity,” a reminder that structural factors can influence how the market transitions from caution to confidence over time.
The current environment also reflects a broader appetite for regulated crypto exposure. The five-day inflow streak into US spot Bitcoin ETFs is a notable marker of renewed institutional interest, a trend that has historically added a layer of liquidity and can help moderate sharp downside moves. The inflows come as traders observe how on-chain activity interacts with price levels and how new participants engage with the asset through regulated vehicles. While this liquidity backdrop can support a steadier price path, it does not by itself guarantee a sustained rally, particularly in a market where sentiment remains guarded and retail participation shows mixed signals. In the mix of factors shaping near-term moves, the balance between whales’ accumulation and retail behavior, alongside evolving ETF dynamics, will likely influence Bitcoin’s trajectory over the coming weeks.
Key takeaways
- Whale accumulation around $71k offers a potential floor if the trend persists, signaling renewed on-chain demand from large holders.
- The rising share of supply held by wallets with 10–10,000 BTC suggests ownership concentration is increasing, which could impact price dynamics if these addresses sustain net buying.
- Retail demand remains a wildcard, with Extreme Fear readings implying a cautious market that could slow any rapid upside despite bullish on-chain signals.
- Regulated exposure via US spot BTC ETFs contributed to a five-day inflow streak of roughly $767.32 million, adding liquidity that can influence near-term price action.
- Historical whale behavior—selling into strength—serves as a reminder that large holders can shift momentum quickly, creating risk for a sustained rally without broader participation.
Tickers mentioned: $BTC
Sentiment: Neutral
Price impact: Positive. Bitcoin’s price has moved higher in the week, reflecting on-chain accumulation and improving liquidity conditions from ETF inflows.
Trading idea (Not Financial Advice): Hold. The current mix of whale accumulation and cautious retail sentiment suggests waiting for clearer directional cues before committing to a new position.
Market context: A liquidity backdrop is evolving as US spot BTC ETFs post renewed inflows, complementing on-chain signals and shaping potential price moves as investors reassess risk and regulatory considerations.
Why it matters
On-chain behavior remains a critical lens through which investors assess Bitcoin’s near-term health. The consolidation of ownership among larger addresses can indicate a readiness to anchor prices at higher levels, especially if these participants sustain their accumulation into key support zones. If whales continue to accumulate while smaller holders trim their activity, the market could be positioning for a more durable base rather than a transient spike. This dynamic matters because it can reduce the likelihood of rapid, sharp declines and increase the odds of a steadier ascent should risk sentiment improve modestly.
Retail sentiment, captured by the Fear & Greed Index, matters because it often acts as a contrarian indicator. When everyday investors grow increasingly optimistic, the market may face a pullback if the enthusiasm outpaces underlying fundamentals. Conversely, persistent caution can delay upside while prices remain tethered to macro and on-chain cues. The emergence of ETF inflows adds another layer to the equation: while inflows are not a guarantee of a sustained rally, they can augment liquidity and provide a stepping-stone for broader participation, including institutional players who seek regulated exposure. Together, these factors sketch a market that could wobble near a confluence of on-chain signals, regulatory dynamics, and liquidity shifts rather than follow a simple, predictable trajectory.
In practical terms, traders and investors should watch how whale and retail balances evolve in tandem. A sustained rise in the share of BTC held by the 10–10,000 BTC cohort could reinforce a floor, especially if accompanied by continued ETF inflows. However, a resurgence in retail buying could introduce additional volatility, particularly if it coincides with macro developments or shifting risk appetite. The market’s path forward will likely hinge on the resilience of on-chain signals and the depth of liquidity provided by regulated products as the year progresses.
What to watch next
- Monitor the balance between whale and retail wallet activity; a persistent tilt toward large holders could support a higher floor.
- Track the Crypto Fear & Greed Index for shifts in sentiment that could precede a change in buying patterns.
- Observe ETF inflows beyond this week’s levels to gauge whether regulated exposure remains a tailwind for liquidity and price discovery.
- Watch price action around $71k and nearby psychological levels to assess how momentum players respond to resistance zones.
- Stay alert to macro developments and regulatory signals that could alter risk appetite for the crypto sector.
Sources & verification
- Santiment weekly summary on wallet balances and the share of supply held by 10–10,000 BTC addresses.
- On-chain discussion of whale dynamics and potential bottom formation from Santiment.
- Crypto Fear & Greed Index reading (Extreme Fear) for the period referenced.
- Bitcoin price context around $71,350 with seven-day performance data (CoinMarketCap).
- U.S. spot Bitcoin ETF inflows totaling approximately $767.32 million in the week reviewed.
TLDR
- Federal Reserve convenes Wednesday with expectations of maintaining rates between 3.5%–3.75%, focus shifts to Powell’s commentary
- Crude oil surged past $100 per barrel following Iran conflict that has disrupted Strait of Hormuz shipping routes
- Micron Technology delivers quarterly results Wednesday following remarkable stock surge of over 300% in past year
- Major earnings releases include FedEx, Dollar Tree, Alibaba, and multiple retail companies
- Goldman Sachs forecasts Q4 oil averaging $93/barrel if Strait of Hormuz blockade continues for two months
Equity markets extended their losing streak to three consecutive weeks as escalating tensions in Iran drove crude oil to heights last witnessed during the 2022 energy emergency. The S&P 500 declined 1.6% for the week. The Dow Jones Industrial Average shed 2%. The Nasdaq Composite retreated 1.3%.
Investors now face a calendar-packed week featuring a Federal Reserve policy announcement, numerous corporate earnings reports, and Nvidia’s signature developer conference.
The Federal Open Market Committee convenes Wednesday for its latest monetary policy deliberation. The benchmark federal funds rate currently stands at 3.5% to 3.75%. Market participants are nearly unanimous in expecting no change to current policy.
Chairman Jerome Powell will conduct a press briefing following the announcement. Analysts suggest this commentary could prove more significant than the rate decision itself.
Powell faces the task of addressing internal disagreements among Fed officials. One faction advocates for additional rate reductions citing employment market weakness. Another group expresses concern about potential inflation acceleration driven by surging energy costs.
This marks Powell’s penultimate scheduled press conference before his chairmanship concludes in May.
Oil and the Strait of Hormuz
The Iranian conflict has entered its third week with no resolution in sight. The Strait of Hormuz — a narrow 21-mile channel transporting approximately 14 million barrels of crude daily — continues to experience disruptions.
Iran’s Revolutionary Guard Corps has declared it will prevent “a liter of oil” from traversing the waterway.
Crude prices temporarily exceeded $100 per barrel last Sunday, marking the first such occurrence since Russia’s Ukraine invasion in 2022. After retreating to the $80 range, prices rebounded following drone attacks on critical petroleum infrastructure and production reduction announcements from Gulf nations.
Goldman Sachs projects that sustained closure of the Strait for 60 days would result in fourth quarter Brent crude averaging $93 per barrel. US West Texas Intermediate would average $89 under this scenario.
Wednesday additionally brings February’s Producer Price Index release. The January reading revealed wholesale inflation exceeded forecasts.
Micron and the Earnings Lineup
Micron Technology unveils quarterly results Wednesday. The semiconductor memory manufacturer’s shares have surged more than 300% over the previous twelve months, propelled by artificial intelligence hardware demand. Its most recent quarter showed 60% year-over-year revenue growth and exceeded analyst profit projections.
FedEx delivers earnings Thursday. The logistics giant’s stock has climbed nearly 25% year-to-date. Analysts scrutinize FedEx’s shipping metrics for economic health indicators.
Dollar Tree also announces results, offering perspective on American consumer strength. Its previous report characterized shoppers as “stretched.”
Nuclear energy firm Oklo releases earnings Tuesday. The company recently finalized an agreement with Meta to provide electricity for data center operations.
Alibaba reports Thursday alongside plans for expanded AI investment. Chinese electric vehicle manufacturer Xpeng announces Friday.
Nvidia’s GTC 2026 conference launches Monday featuring a presentation from CEO Jensen Huang.
Perhaps due to its popularity, but Ripple’s token is often the subject of some big price predictions, many of which come from its community, known as the XRP Army, and they are hard to believe, at least at first glance.
One of the latest, though, came from Ali Martinez, a renowned crypto analyst who has shown a lack of bias toward XRP in his commentary. Moreover, he posted a massive, quite unrealistic target (at least for the time being) of $48, but he based it on technical analysis, indicating that this is the potential top during the next bull run, according to the multi-year triangle formation.
While this might sound absurd given XRP’s current price tag of $1.43 and that it would require a 3,300% surge to reach those levels, we decided to ask ChatGPT to dissect this prediction to see if there’s any merit after all.
Reality Check
The AI solution first noted that the multi-year symmetrical triangle has started forming since its 2018 peak, and this measured move is calculated by taking the height of the pattern and projecting it upward from the breakout point. In the asset’s case, the range is quite wide, from $0.20 to $3.84. The current peak was obtained in 2025 at $3.60, while the breakout level is at the whopping $10-$13 zone.
It disclaimed that such measured moves from very large patterns “often exaggerate theoretical targets” because they assume a clean breakout with sustained momentum. If XRP is to reach those levels, its market cap would make it roughly the current size of Apple and 2x that of Bitcoin. To do so, these two factors would need to occur:
- The total crypto market cap would need to expand dramatically (possibly $10-$15 trillion).
- XRP would have to capture a very large share of that capital.
ChatGPT went back to the 2016/2017 cycle when XRP posted a mind-blowing surge of 56,000%, it said, jumping from approximately $0.006 to its then-all-time high of $3.40. In 2020-2021, it gained over 1,000%, but those moves came when XRP was a lot smaller altcoin, which is not the case now.
“Compared with those numbers, 3,300% is not unprecedented in crypto, but it usually happens from much lower starting prices. From a $88 billion market cap – such moves become harder.”
Realistic Targets
After it dismissed the $48 level as a “multi-cycle moonshot” option in which too many factors have to be perfectly aligned, ChatGPT outlined more realistic targets for the cross-border token. Its conservative scenario envisions a substantial rally to somewhere between $3 and $5.
The stronger bull case, in which XRP and the company behind it would have to experience major adoption growth, the ETF inflows would need to skyrocket, and the overall market expansion must be a lot stronger, sees the asset jumping to $8-$12. The probability for this scenario was put at “moderate.”
Even the extreme bull case puts XRP at $15-$25, and nowhere near $48. And this one would be possible if the total market cap reaches $10 trillion, and the cross-border token “captures a large narrative-driven capital inflow.” This probability was set at “low but plausible.”
The post We Asked ChatGPT if XRP Can Indeed Hit $48: Here Is the (Un)Surprising Answer appeared first on CryptoPotato.
Vienna, Austria-based crypto broker Bitpanda is leaning into a strategy it has been quietly building for years: keep its retail business anchored in Europe while expanding globally by supplying crypto infrastructure to banks and financial firms.
The company’s next phase of growth will focus less on raw user numbers and more on geographic reach, Vishal Sacheendran, vice president of global markets strategy and operations, told CoinDesk in an interview.
“It’s about having a footprint in more markets,” Sacheendran said.
That expansion is building on its steady growth. The company, which boasts more than 7 million users, reported this week €371 million ($430 million) in adjusted revenue for 2025, up 16% from the previous year, while its registered user base increased 25% to 7.4 million.
The firm is also weighing a public listing. Bitpanda is reportedly preparing for a potential IPO on the Frankfurt Stock Exchange as early as the first half of 2026, targeting a valuation between EUR 4 billion and EUR 5 billion. The plan comes as multiple crypto exchanges and infrastructure firms have either gone public or are planning to do so.
Bringing crypto to banks
The exchange spent the past decade largely focused on the European Union, where its app allows retail users to trade cryptocurrencies and other assets. But outside Europe, Sacheendran said the strategy needs to change. In some markets — especially smaller ones or those already dominated by global exchanges — launching a consumer app may not make sense.
Instead, Bitpanda wants to work through banks and financial institutions that already have distribution. “We don’t want to compete with exchanges everywhere,” he said. “There’s a big segment of the market that still trusts banks.”
The company formalized that approach earlier in March with the launch of Bitpanda Enterprise, a new institutional offering that packages the firm’s infrastructure for banks, brokers, asset managers, fintechs and corporate clients.
The unit builds on Bitpanda’s existing B2B business, previously known as Bitpanda Technology Solutions, and bundles several services into a single platform. These include API-based investment infrastructure for financial brands, institutional-grade custody, trading liquidity and settlement tools, and payment rails for crypto and stablecoins. The platform also includes token infrastructure for stablecoin issuance and systems designed to support tokenized assets.
UAE launchpad
One early example of that model came in July, when RAKBANK, one of the United Arab Emirates’ oldest lenders, launched crypto trading for retail customers through a partnership with Bitpanda. Instead of building its own infrastructure, the bank plugged into Bitpanda’s platform.
Sacheendran said deals like that often open doors elsewhere. Once one major bank adopts crypto services, others tend to follow. “When a top-tier bank starts offering it, the rest of the market takes notice,” he said.
Bitpanda’s pitch to institutional partners rests heavily on its regulatory positioning. The company has been operating under strict licensing requirements, including the European Union’s MiCA framework, widely seen as one of the most comprehensive crypto regulatory regimes.
Regulatory moat
That regulatory credibility travels, Sacheendran said, especially in emerging markets where regulators are still shaping their approach to digital assets. In many of those regions — including parts of Asia, Latin America and the Middle East — authorities are eager to develop the sector but want partners that already operate within strong compliance frameworks.
Asia-Pacific illustrates the complexity. The region is “very fragmented,” he said, with different rules in jurisdictions such as Hong Kong, Singapore, Japan and South Korea. Bitpanda’s approach there will be gradual: start small, test demand and scale where the regulatory and commercial conditions align.
On the product side, Bitpanda is evaluating derivatives trading, though Sacheendran noted that regulations differ widely across jurisdictions. He also expects tokenization to become a bigger theme in the coming years, particularly for assets such as bonds, money market funds and real estate.
Those markets could benefit from blockchain’s ability to enable around-the-clock trading and broader investor access, he said.
One area Bitpanda is unlikely to enter directly is stablecoin issuance. “We don’t build a stablecoin,” Sacheendran said, noting that the company prefers to provide infrastructure and operational support for institutions that want to launch their own.
Read more: Stricter MiCA rules could thin crypto industry across the EU, says Swiss wealth manager
Your AI just made several payments while you read that headline. You approved none of them. Visa processed none of them. And if the crypto industry’s biggest bulls are right, that’s not a bug — it’s the entire future of the internet economy.
Coinbase founder Brian Armstrong thinks there will soon be more AI agents than humans making transactions on the internet. Binance founder Changpeng Zhao went further, predicting agents will make one million times more payments than people, all in crypto. The posts landed on the same day last week and lit up crypto X.
The core argument is structural.
AI agents can’t open bank accounts because banks require identity verification that software cannot provide, whereas a crypto wallet only needs a private key. No KYC, no compliance review, no waiting — and that asymmetry is what Armstrong was pointing at.
But the wallet problem is only half the picture. The other half is economics.
Agents don’t shop the way humans do. When an AI agent is executing a task — such as researching a topic, coordinating a supply chain, building a report — it might call dozens of specialized APIs in a single session.
Each call might be worth fractions of a cent, where it pays for GPU compute time, real-time data feeds, web scraping services, or hiring a sub-agent to handle translation. None of these transactions resembles anything Visa or Mastercard was designed to process.
Consider, for a moment, that this story was written by an agent, requested by a “chief” agent at CoinDesk tasked with increasing the site’s authority.
To produce it, that agent would have queried a real-time news API to verify Armstrong’s tweet ($0.002), pulled onchain data to search for volume figures ($0.004), cross-referenced press releases ($0.001), and pinged a financial context model for Visa protocol details ($0.003). It would finally generate the article at an additional cost, paying credits to another AI tool to actually write the piece.
The total cost of reporting is under two cents with six transactions, at the current figures offered by protocols such as x402.
In contrast, Stripe’s minimum processing fee on a single transaction is around $0.30. Running those six payments through a card network would cost more than 100 times the value of the payments themselves.
A human editor reviewing and publishing the piece might then be billed by a sub-agent that handled SEO optimization, another that ran plagiarism checks, and another that formatted for CMS software. Each micropayment is economically absurd on card rails, but trivial onchain.
This is the thesis behind x402, Coinbase’s open payment protocol that embeds stablecoin payments directly into HTTP requests — so an agent can hit a paywall, pay in USDC, and continue its task in the same interaction, no human required. Cloudflare, Circle, AWS, and Stripe are all backing it. Google’s open agent payments standard includes x402 as a settlement layer.
Every industry with high-frequency, low-value data exchange becomes a candidate.
In healthcare, an agent managing a patient’s insurance claim pays per document retrieved from a medical records API. In logistics, a procurement agent auctions freight slots across dozens of carriers in real time, settling the winning bid instantly. In the media, AI crawlers pay per article indexed rather than negotiating bulk licensing deals. In finance, a trading agent pays a specialist model fractions of a cent per risk signal consumed.
A caveat, however, is that the infrastructure is ahead of the demand.
CoinDesk reported this week that x402 currently processes around $28,000 in daily volume, with Artemis flagging roughly half of observed transactions as artificial activity rather than real commerce. The merchants x402 was built to serve are still rare.
Meanwhile, traditional finance is not standing still. Visa launched its Trusted Agent Protocol last October, and Mastercard completed Europe’s first live AI-agent bank payment inside Santander’s regulated infrastructure last week — both on existing card rails with cryptographic verification layered on top.
The most likely outcome is a split, where regulated commerce stays on card rails, while machine-to-machine payments — such as agents hiring agents, paying per API call, buying compute on demand — migrate to stablecoins because the economics demand it.
The open question is which bucket ends up bigger.
The Ethereum Foundation completed a $10.2 million over-the-counter sale of 5,000 ETH to BitMine at $2,042.96 per token as part of treasury management.
The Ethereum Foundation has completed an over-the-counter sale of 5,000 ETH to BitMine Immersion Technologies for $10.2 million, priced at $2,042.96 per token. The OTC transaction represents a strategic move by the foundation to manage its treasury and fund ongoing operations and ecosystem development initiatives.
The sale signals continued institutional engagement with Ethereum and the foundation’s active approach to treasury liquidity management. OTC deals of this scale are typically used to avoid market impact while securing capital for long-term protocol funding and ecosystem support.
Sources: Cointelegraph | KuCoin Insights | TokenPost | Our Crypto Talk | Coin Bureau
This article was generated automatically by The Defiant’s AI news system from publicly available sources.
Prediction markets have long promised to aggregate insights about future events. Increasingly, those signals are coming not just from people, but from machines.
According to David Minarsch, CEO and co-founder of Valory AG, the team behind the crypto-AI protocol Olas, autonomous AI agents are emerging as powerful tools for trading prediction markets, particularly for retail users trying to compete in an increasingly automated environment.
Valory builds products at the intersection of blockchain and multi-agent systems (MAS), and its current focus is Olas, formerly known as Autonolas. The protocol is designed as infrastructure for autonomous software agents that can run services on blockchains, interact with smart contracts, and cooperate with one another while earning crypto rewards.
The broader vision is what Minarsch calls an “agent economy”. A decentralized ecosystem where autonomous AI agents perform useful tasks and generate value for their users.
One of the most visible experiments in that vision is Polystrat, an AI agent launched on the prediction-market platform Polymarket in February 2026. The agent trades on behalf of users who self-custody and own it, executing strategies continuously around the clock.
“In a nutshell, Polystrat is an autonomous AI agent that trades on Polymarket 24/7 on behalf of its human user,” Minarsch said. The idea is simple: while humans sleep, work or lose focus, the agent keeps trading.
Prediction markets, platforms where users trade contracts tied to real-world outcomes, have surged from niche forecasting tools into a fast-growing corner of fintech over the past few years. The industry’s breakout moment came during the 2024 U.S. presidential election, when trading volumes spiked and the markets gained mainstream visibility, followed by rapid expansion into sports, economics, and crypto-related bets. By 2025, total notional trading volume across major platforms exceeded $44 billion, with monthly activity reaching as much as $13 billion during peak periods.
Today the market is highly concentrated around two dominant players: Kalshi, a U.S.-regulated event-contracts exchange overseen by the Commodity Futures Trading Commission, and Polymarket, a crypto-native platform that operates globally and offers a broader range of prediction markets. Together they account for roughly 85–97% of trading volume in the sector, processing tens of billions of dollars in annual bets on everything from elections and central-bank policy to sports and cultural events
Why machines may outperform humans
The push toward AI-driven trading stems from a simple observation. Much of the intelligence embedded in modern AI models hasn’t yet translated into financial markets.
That realization prompted Valory’s team to begin building what they call a “prediction market economy” on Olas in 2023, an ecosystem where AI agents use prediction tools and data pipelines to forecast outcomes and trade on them.
Prediction markets themselves are built on probabilistic forecasting. A simple guess about an event, whether a political outcome, economic indicator or sports result, might be no better than a coin flip. But structured data analysis and disciplined trading strategies can change that equation.
“Simply prompting off-the-shelf models with markets usually results in outcomes no better than a coin-flip,” Minarsch said. “But state-of-the-art AI models wrapped in custom workflows, so called prediction tools, have historically shown predictive accuracy up to 70% and higher.”
The results so far suggest that machines may have an advantage. Third-party data indicates that only about 7% to 13% of human traders achieve positive performance on prediction markets, while the majority lose money.
At the same time, machine participation is growing quickly. More than 30% of wallets on Polymarket are already using AI agents, according to analytics platform LayerHub.
Minarsch believes this trend reflects a broader shift: humans are already competing with machines whether they realize it or not. “You have human participants in prediction markets alongside many machines,” he said. “So humans are already in a battle with machines.”
The key difference is that machines are less emotional and better at sticking to consistent strategies.
By making AI agents available to everyday users, Olas aims to level that playing field.
Early traction for autonomous traders
The early performance of Polystrat has been encouraging.
Within roughly a month of launch, the agent executed more than 4,200 trades on Polymarket and recorded single-trade returns as high as 376%, according to data shared by the team.
“Agents tend to do better than humans,” he said. “Polystrat AI agents already outperform human participants in Polymarket, with over 37% of them showing a positive P&L versus less than half that number for human participants.”
Users can configure their own agents depending on strategy preferences, data sources or risk tolerance.
The long tail of prediction markets
Beyond performance, Minarsch believes AI agents could unlock an overlooked opportunity in prediction markets: the “long tail” of niche or localized questions.
Many prediction markets revolve around major global events, elections, macroeconomic data or high-profile sports competitions. But countless smaller questions remain largely unexplored.
“Humans often don’t bother digging for the information,” Minarsch said. “They can’t be bothered to make the effort.” AI agents, by contrast, can analyze large numbers of smaller markets simultaneously.
“The long tail of prediction markets is very interesting for AI agents,” he said. “You just point the agent at the problem and it does the work.”
This could help expand prediction markets as a data-gathering tool for businesses, policymakers and decision-makers. Forecast markets have long been studied as ways to aggregate dispersed knowledge and surface insights that traditional surveys or models might miss.
In that sense, prediction markets may become a kind of upstream technology for decision-making across industries.
Human-AI collaboration
Despite the rise of automation, Minarsch does not see AI agents replacing humans entirely.
Instead, he frames them as complements.
“Humans make choices in a more rushed way, which can be detrimental,” he said. “AI agents can act as something humans rely upon.”
One future direction involves allowing users to augment their agents with proprietary knowledge or specialized data sets. “We see demand from users who want their agent to tap into their own knowledge base or proprietary information,” Minarsch said. “That would allow agents to trade in a more principled way than a human could.”
Over time, the team says prediction models and data pipelines powering these agents have improved significantly, generating sustained alpha when combined with general-purpose large language models.
Risks and regulation
The growth of prediction markets also raises ethical and regulatory questions.
Some critics argue that markets forecasting wars, deaths or disasters could create incentives to manipulate outcomes or profit from harmful events.
Minarsch acknowledged that careful guardrails are needed.
“There needs to be regulation about what kinds of prediction markets should exist,” he said.
At the same time, he believes AI agents could also help detect problematic markets or manipulation attempts by identifying suspicious patterns.
“Agents could spot patterns and help shut down problematic markets,” he said.
Building a user-owned AI economy
For Minarsch, the ultimate goal is not simply better trading strategies.
It is ensuring that everyday users retain a stake in an increasingly automated digital economy.
A future where AI systems perform most economic activity could risk disenfranchising individuals if centralized platforms control the technology. “Olas aims to create a world where human users can be empowered through their AI agents rather than disenfranchised by them.”
To counter that dynamic, the project emphasizes user ownership of AI systems. “We want to create more user-owned agents,” Minarsch said.
If successful, that model could allow people to deploy autonomous software that generates value on their behalf across markets and services. Prediction markets are just the starting point.
Read more: AI rout hits software stocks, but Grayscale says blockchains stand to benefit
Key Takeaways
- Nvidia commands the AI accelerator market with exceptional revenue performance, profit margins, and free cash generation
- Nvidia’s competitive moat stems from its integrated software-hardware platform, extending beyond processor performance alone
- AMD represents the strongest competition but remains significantly behind in AI chip revenue
- AMD’s investment thesis centers on securing secondary supplier status rather than market leadership
- Investment risks differ: Nvidia confronts growth deceleration while AMD battles execution challenges
Nvidia has established itself as the go-to hardware provider for organizations developing artificial intelligence infrastructure. The company’s data center segment currently generates the majority of its revenue, earnings, and operating cash flow. This positioning has transformed it into one of the most financially dominant hardware enterprises ever created.
The current debate among investors has shifted beyond questioning AI market viability. Instead, the focus centers on whether Nvidia can sustain its aggressive growth trajectory and if AMD possesses the capability to narrow the competitive divide meaningfully.
Why Nvidia’s Competitive Edge Extends Beyond Silicon
Nvidia delivers far more than processing units. The company provides an integrated ecosystem encompassing GPUs, networking infrastructure, complete systems, software frameworks, and comprehensive developer support. This holistic approach has become deeply woven into enterprise AI deployment strategies.
For most enterprises, migrating away from Nvidia would require reconstructing significant portions of their AI technology stack, extending well beyond simple hardware substitution. These elevated transition costs represent Nvidia’s most enduring strategic advantage.
The company’s financial performance validates this market position. Nvidia’s data center segment operates at revenue levels that AMD hasn’t approached. Its profitability and cash flow capabilities provide ongoing resources for continuous innovation and product development.
Understanding AMD’s Position as the Primary Alternative
AMD stands as Nvidia’s most formidable competitor in the AI accelerator landscape. The company operates a well-balanced semiconductor portfolio spanning data center processors, personal computers, gaming hardware, and embedded solutions. AMD’s historical success capturing CPU market share demonstrates proven execution capabilities.
Advanced Micro Devices, Inc., AMD
AMD doesn’t require complete market dominance to deliver shareholder value. Success means establishing itself as a dependable alternative supplier in AI infrastructure while maintaining strength across CPUs and adjacent markets.
This represents an achievable objective. Major cloud providers and enterprise buyers typically prefer vendor diversification for mission-critical components. AMD stands positioned to capitalize on this preference as AI spending patterns stabilize.
Understanding Investment Risks for Both Companies
Nvidia’s primary threat isn’t business failure but rather growth normalization. With revenue concentration in data center AI expenditures, any customer spending slowdown following aggressive buildout phases could dramatically reduce growth rates.
Restrictions on advanced chip exports to Chinese markets continue presenting genuine regulatory headwinds. Additionally, margin compression may emerge as revenue composition shifts toward complex system-level offerings.
AMD’s central challenge revolves around execution capability. The company still trails Nvidia substantially in software ecosystem maturity and the customer integration depth built through years of market leadership. AMD’s investment proposition depends more heavily on future potential than current accomplishments.
While AMD’s AI software tools show improvement, they haven’t achieved the development maturity or market penetration that characterizes Nvidia’s established platform.
Current Competitive Landscape Assessment
Nvidia maintains superiority across most financial benchmarks. The company demonstrates higher profitability, stronger balance sheet cash positions, larger AI-related revenue streams, and deeper ecosystem entrenchment.
AMD presents a compelling growth narrative but operates from a position of market disadvantage. The revenue gap between both companies in AI acceleration remains substantial.
For investment consideration, Nvidia represents exposure to current AI market leadership. AMD offers participation in long-term AI infrastructure market expansion and diversification trends.
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