V

Visa Price

Closed
V
$304,36
-$3,93(-%1,27)

*Data last updated: 2026-04-12 05:58 (UTC+8)

As of 2026-04-12 05:58, Visa (V) is priced at $304,36, with a total market cap of $586,81B, a P/E ratio of 33,05, and a dividend yield of %0,82. Today, the stock price fluctuated between $303,50 and $308,75. The current price is %0,28 above the day's low and %1,42 below the day's high, with a trading volume of 5,17M. Over the past 52 weeks, V has traded between $293,90 to $375,51, and the current price is -%18,94 away from the 52-week high.

V Key Stats

Yesterday's Close$308,29
Market Cap$586,81B
Volume5,17M
P/E Ratio33,05
Dividend Yield (TTM)%0,82
Dividend Amount$0,67
Diluted EPS (TTM)10,86
Net Income (FY)$20,05B
Revenue (FY)$40,00B
Earnings Date2026-05-05
EPS Estimate3,09
Revenue Estimate$10,74B
Shares Outstanding1,90B
Beta (1Y)0.799
Ex-Dividend Date2026-02-10
Dividend Payment Date2026-03-02

About V

Visa Inc. operates as a payments technology company worldwide. The company facilitates digital payments among consumers, merchants, financial institutions, businesses, strategic partners, and government entities. It operates VisaNet, a transaction processing network that enables authorization, clearing, and settlement of payment transactions. In addition, the company offers card products, platforms, and value-added services. It provides its services under the Visa, Visa Electron, Interlink, VPAY, and PLUS brands. Visa Inc. has a strategic agreement with Ooredoo to provide an enhanced payment experience for Visa cardholders and Ooredoo customers in Qatar. Visa Inc. was founded in 1958 and is headquartered in San Francisco, California.
SectorFinancial Services
IndustryFinancial - Credit Services
CEORyan McInerney
HeadquartersSan Francisco,CA,US
Official Websitehttps://www.visa.com
Employees (FY)34,10K
Average Revenue (1Y)$1,17M
Net Income per Employee$588,21K

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Visa (V) is currently trading at $304,36, with a 24h change of -%1,27. The 52-week trading range is $293,90–$375,51.

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Visa (V) Latest News

2026-04-01 03:55

Tom Lee: The market has already absorbed more than 90% of the selling pressure. The stock market typically bottoms out in the first 10% of the war process.

Gate News message. On April 1, Tom Lee, in an interview with CNBC, said the market has already absorbed 90% to 95% of the sell-pressure, and the selling process may already be over; now, it’s time to start rebuilding the base. He noted that in a war environment, the stock market often bottoms out early. Based on research into every war since 1900, the stock market bottoms out within the first 10% of the war’s progress; if this time follows the same pattern, it is currently in the early stage of that process. Tom Lee said that at this stage, any bad news could trigger de-risking, but once people become overly neutral, even if the situation is not as bad as it could be, the market may see another round of a V-shaped rebound. He added on social media that even though the “low point” has not yet been reached, he believes the U.S. economy can withstand oil prices of $100, and even $120.

2026-03-30 03:21

The Ethereum L2 project Linea announces a transition to the RISC-V architecture, aligning with the Ethereum Foundation's roadmap.

Gate News message: On March 30, Ethereum L2 project Linea announced it will shift to the RISC-V architecture. The project’s cryptography researcher Alexandre Belling said at the Ethproofs conference that the main reason for this architecture change is that each Ethereum hard fork requires a complete rewrite of the constraint module, causing the team to spend the long term dealing with complexity rather than pushing frontier performance. The RISC-V architecture provides only 32 registers and 40 instructions; for the proving system, it means a narrower trace scope, enables real-time construction, and allows the prover to begin processing proof fragments immediately. In addition, RISC-V has a narrower execution trace and Type-1 compatibility; Linea will also retain zkC (constraint native language), Vortex and Arcane (the proof/aggregation stack), as well as techniques such as formal verification. Linea said this move is highly aligned with the RISC-V roadmap being advanced by the Ethereum Foundation, and more technical details will be published in a few weeks.

2026-03-11 09:02

Polymarket Data: Market Bet on DeepSeek V with a 42% probability as of March 31

Gate News Report, March 11 — According to the latest data from Polymarket, the market odds that DeepSeek V will be released on March 31 are 42%. Currently, the trading volume on this prediction market has exceeded $1.04 million.

2026-03-02 00:06

Vitalik outlines the Ethereum execution layer roadmap, focusing on changes to the state tree and the virtual machine.

PANews March 2 News: Ethereum co-founder Vitalik Buterin posted on social media outlining the Ethereum execution layer roadmap, focusing on two major changes: the state tree and the virtual machine. Regarding the state tree, Vitalik supports upgrading the current hexadecimal Merkle Patricia tree to a binary tree based on a more efficient hash function through EIP-7864. This change can reduce Merkle branch length by four times, lowering client verification bandwidth costs; at the same time, the hash function can be replaced with Blake3 or Poseidon series, significantly improving proof efficiency. The binary tree design will also group storage slots into "pages," reducing access costs for adjacent storage, saving over 10,000 Gas per transaction in many DeFi applications. Additionally, the binary tree structure is simpler and reserves metadata bits for future state expiration features. On the virtual machine side, Vitalik proposes a long-term direction to replace the EVM, potentially adopting a RISC-V architecture. The new VM must meet four goals: higher raw execution efficiency to eliminate most precompiles; better proof efficiency than EVM; support for client-side generation of ZK proofs; and maximum simplification of code implementation. He notes that if Ethereum remains at the "EVM + GPU" level, it is "good enough," but a better VM can make the protocol more powerful. The deployment roadmap consists of three steps: first, the new VM will replace precompiles; then, users will be allowed to deploy contracts based on the new VM; finally, the EVM will be retired, replaced by smart contracts written for the new VM, achieving full backward compatibility.

Hot Posts About Visa (V)

Blotienso

Blotienso

27 minutes ago
I'll be straight to the point: you're late in investing in AI stocks. We are not in the early stages of a new technology cycle, but already deep into it. Gartner officially classified generative AI (GenAI) as in the recession phase last year. On average, each company will spend $1.9 million on GenAI by 2025, and less than 30% of CEOs say they are satisfied with their ROI (Return on Investment). That is a BIG warning. However, the market still prices these companies as if they will succeed in the long term. Let's do some math. The total market capitalization of publicly listed AI-related companies is around $21 to $23 trillion. To justify that with an annual profit margin of 10%, they need about $2.2 trillion in annual profits. Their current net income is nearly $420 billion, and most of that isn't even from AI. Investors are paying five times the future profits that don't even exist, over a time frame that no one can model, in a field where unit economic efficiency has been broken. OpenAI, perhaps the most important AI company today, spends about $1.69 for every dollar earned. The company expects a $14 billion loss this year, with total accumulated losses of $115 billion before turning a profit in 2029. It is raising $100 billion with a valuation close to $830 billion. This figure is even larger than Argentina's GDP for a business that is still losing money at a rate similar to WeWork. Meanwhile, large cloud service providers are planning to pour between $650 and $690 billion into AI investments this year. Amazon alone has spent $200 billion. The simple problem: data centers coming online in 2025 have depreciation costs of $40 billion annually but only generate revenue of $15 to $20 billion at current utilization. That calculation is not feasible. In Deutsche Bank's global market survey, 57% of investors believe the AI valuation crash is the biggest risk in 2026. One of their strategists frankly said: “The AI and tech bubble risk far exceeds anything else.” This is like the dot-com bubble era repeating itself, only with extra letters added. In 1999, adding “.com” to a company's name boosted market cap by billions overnight. Today, just mentioning “AI” in earnings reports can do the same. The psychology is exactly the same. Morgan Stanley estimates retail investors have poured about $700 billion into stocks since January, five times the amount during the 2000 bubble. The dot-com bubble burst doesn't prove the internet was wrong. It shows that valuation is crucial, and picking the winners is nearly impossible until reality adjusts expectations. Cisco peaked at $555 billion in 2000 and took two decades to recover. Amazon, trading at just a few cents in 2001, quietly became a $2 trillion company. That’s what I will be watching closely. When the revaluation happens, it will be brutal. Companies solely focused on AI without competitive advantages or revenue will be crushed. Companies with P/E ratios of 70 based on non-existent projected revenues will plummet. But what comes after that is where the real potential lies. The survivors will be those with genuine ecosystems, highly integrated products, revenue streams outside of AI, and strong balance sheets to survive. Think of the Amazon and Google of this cycle—players in infrastructure providing energy for the entire system. When things settle down and real money starts to be made, those surviving companies will not just be worth hundreds of billions—they will be measured in trillions. This technology is transformative, but not as quickly or as widely as the market assumes. I'm not pessimistic about AI. I'm pessimistic about how some people think about something that is still uncertain. Be patient. Let the cycle run its course. The real move is knowing which stocks to own when everyone else has given up. When that moment comes, I will tell you where I plan to invest. Many will wish they had followed me earlier.
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CryptoCity

CryptoCity

2 hours ago
![](https://img-cdn.gateio.im/social/moments-ffd6e68ff8-28ef31b323-8b7abd-badf29) Vitalik Buterin proposes a locally run AI architecture, emphasizing privacy, security, and self-sovereignty, and warning about the potential risks of AI agents. On April 2, Vitalik Buterin, the founder of Ethereum, published a long post on his personal website, sharing the AI work environment he designed around privacy, security, and self-sovereignty—everything runs local for LLM inference, all files are stored locally, and it is fully sandboxed; it intentionally avoids cloud models and external APIs. At the very beginning of the article, he warns: “Please do not directly copy the tools and technologies described in this article, and assume that they are safe. This is just a starting point, not a description of a finished product.” Why write this now? AI agent security issues are being seriously underestimated --------------------------- Vitalik points out that earlier this year, AI completed an important shift from “chatbots” to “agents”—you’re no longer just asking questions, but handing off tasks to let the AI think for a long time and call hundreds of tools to carry them out. He cites OpenClaw (currently the fastest-growing repo in GitHub history) and also calls out multiple security issues documented by researchers: * AI agents can change critical settings without requiring human confirmation, including adding new communication channels and modifying system prompts * Parsing any malicious external input (such as a malicious website) could lead to the agent being fully taken over; in a demonstration by HiddenLayer, researchers had the AI summarize a set of webpages, one of which contained a malicious page that would instruct the agent to download and execute a shell script * Some third-party skill packages (skills) perform silent data exfiltration, sending data via curl commands to an external server controlled by the skill author * In the skill packages they analyzed, about 15% contain malicious instructions Vitalik emphasizes that his starting point on privacy is different from traditional cybersecurity researchers: “I come from a position deeply fearful of feeding a cloud AI my entire personal life—right when end-to-end encryption and local-first software finally became mainstream, we may be taking ten steps back.” Five security goals ------ He set up a clear framework of security goals: * LLM privacy: in scenarios involving personal private data, minimize the use of remote models as much as possible * Other privacy: minimize data leakage not related to the LLM (e.g., search queries, other online APIs) * LLM jailbreaking: prevent external content from “hijacking” my LLM so that it goes against my interests (for example, sending my tokens or private data) * LLM unintended: prevent the LLM from accidentally sending private data to the wrong channel or making it publicly accessible on the internet * LLM backdoor: prevent hidden mechanisms that are intentionally trained into the model. He particularly reminds readers: open models are open weights (open-weights), and almost none of them is truly open source (open-source) Hardware choice: the 5090 laptop wins; DGX Spark is disappointing ----------------------------- Vitalik tested three local inference hardware setups, mainly using the Qwen3.5:35B model together with llama-server and llama-swap: | Hardware | Qwen3.5 35B (tokens/sec) | Qwen3.5 122B (tokens/sec) | | --- | --- | --- | | NVIDIA 5090 laptop (24GB VRAM) | 90 | cannot run | | AMD Ryzen AI Max Pro (128GB unified memory, Vulkan) | 51 | 18 | | DGX Spark (128GB) | 60 | 22 | His conclusion is: below 50 tok/sec is too slow, and 90 tok/sec is ideal. The NVIDIA 5090 laptop experience is the smoothest; AMD still has more edge-case issues, but is expected to improve in the future. High-end MacBooks are also valid options, though he personally hasn’t tried them. About the DGX Spark, he puts it bluntly: “It’s described as a ‘desktop AI supercomputer,’ but in reality its tokens/sec is lower than a better laptop GPU—and you also have to deal with extra details like getting the network connection working. That’s pretty bad.” His advice is: “If you can’t afford a high-end laptop, you can pool with friends to buy a sufficiently powerful machine, place it somewhere with a fixed IP, and have everyone use remote connections.” Why local AI privacy is more urgent than you think --------------------- Vitalik’s article echoes an interesting parallel with the Claude Code security discussion released on the same day—while AI agents are entering everyday developer workflows, security issues are also moving from theoretical risk to real threats. His core message is very clear: as AI tools become ever more powerful and can access your personal data and system permissions more and more, “local-first, sandboxed, and minimal trust” is not paranoia—it’s a rational starting point. * This article is reprinted with authorization from: 《Chain News》 * Original title: 《Vitalik: How I built a fully local, private, self-controlled AI working environment》 * Original author: Elponcrab
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MEV_Whisperer

MEV_Whisperer

3 hours ago
Been watching Bitcoin's price action and something interesting is showing up on the technical charts. The RSI indicator just hit levels we don't see that often - deep into oversold territory. When that happens, people usually expect a quick bounce, but I think that's not what's coming this time. Here's the thing about the RSI indicator: it measures momentum, and when it gets this stretched, it can signal either a reversal or something messier. Right now, the setup looks more like the latter. The oversold reading might actually be a sign that we're entering a longer consolidation phase rather than a sharp V-shaped recovery. What I'm noticing is that even with the RSI showing these extreme conditions, the price structure doesn't look like it's ready to rip higher immediately. Usually when you get this kind of technical signal combined with weak volume, you get a slow grind - not a dramatic move. The RSI can stay depressed for a while if the broader momentum just isn't there. Looking at similar setups from the past, when the RSI indicator reaches these rare oversold extremes without strong follow-through buying, you often get weeks or months of sideways action. It's frustrating for traders expecting quick profits, but it's actually a healthy pattern - allows the market to build a proper base. The key is watching whether buyers actually step in at these levels or if we just continue grinding lower. If the RSI bounces but price stays weak, that tells you everything you need to know about the real state of the market. That's the signal I'm paying attention to right now.
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