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IBM
$229,76
-$1,55(-0,67%)

*Data last updated: 2026-05-10 01:54 (UTC+8)

As of 2026-05-10 01:54, IBM (IBM) is priced at $229,76, with a total market cap of $215,94B, a P/E ratio of 26,06, and a dividend yield of 2,92%. Today, the stock price fluctuated between $224,89 and $230,71. The current price is 2,16% above the day's low and 0,41% below the day's high, with a trading volume of 4,22M. Over the past 52 weeks, IBM has traded between $220,75 to $324,90, and the current price is -29,28% away from the 52-week high.

IBM Key Stats

Yesterday's Close$231,31
Market Cap$215,94B
Volume4,22M
P/E Ratio26,06
Dividend Yield (TTM)2,92%
Dividend Amount$1,69
Diluted EPS (TTM)11,45
Net Income (FY)$10,59B
Revenue (FY)$67,53B
Earnings Date2026-07-22
EPS Estimate3,03
Revenue Estimate$17,83B
Shares Outstanding933,58M
Beta (1Y)0.581
Ex-Dividend Date2026-05-08
Dividend Payment Date2026-06-10

About IBM

International Business Machines Corporation provides integrated solutions and services worldwide. The company operates through four business segments: Software, Consulting, Infrastructure, and Financing. The Software segment offers hybrid cloud platform and software solutions, such as Red Hat, an enterprise open-source solutions; software for business automation, AIOps and management, integration, and application servers; data and artificial intelligence solutions; and security software and services for threat, data, and identity. This segment also provides transaction processing software that supports clients' mission-critical and on-premise workloads in banking, airlines, and retail industries. The Consulting segment offers business transformation services, including strategy, business process design and operations, data and analytics, and system integration services; technology consulting services; and application and cloud platform services. The Infrastructure segment provides on-premises and cloud-based server and storage solutions for its clients' mission-critical and regulated workloads; and support services and solutions for hybrid cloud infrastructure, as well as remanufacturing and remarketing services for used equipment. The Financing segment offers lease, installment payment, loan financing, and short-term working capital financing services. The company was formerly known as Computing-Tabulating-Recording Co. International Business Machines Corporation was incorporated in 1911 and is headquartered in Armonk, New York.
SectorTechnology
IndustryInformation Technology Services
CEOArvind Krishna
HeadquartersArmonk,NY,US
Official Websitehttps://www.ibm.com

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IBM (IBM) Latest News

2026-05-06 20:52IBM Broadens Enterprise AI Suite With New Agent-Based Tools at Think 2026According to IBM, the company announced an expansion of its enterprise AI capabilities at Think 2026 conference in Boston, rolling out new agent-based tools to help organizations embed artificial intelligence into daily operations. Context Studio, now generally available, enables enterprises to create AI agents grounded in their data and processes while maintaining data control within the organization. In a real-world deployment, health system Providence used IBM WatsonX Orchestrate to deploy an AI-powered HR agent integrated with its existing HR platform. Managers now spend 90% less time on hiring steps, job request accuracy improved by 70%, and internal transfers were completed 12 days faster on average, reducing both time-to-fill and transfer costs by 60%.2026-04-22 20:28IBM Stock Falls 8% in After-Hours TradingGate News message, April 22 — IBM shares declined 8% during after-hours trading on Tuesday.2026-03-19 02:012025 年图灵奖揭晓:量子密钥分发协议 BB84 开发者获奖Gate News 消息,3 月 19 日,2025 年图灵奖授予美国 IBM 院士 Charles H. Bennett 和加拿大蒙特利尔大学计算机科学与运筹学系教授 Gilles Brassard。二人被公认为量子信息科学的奠基人,其最著名成果 BB84 协议是世界上第一个量子密钥分发(QKD)协议,标志着量子密码学的诞生。 两人的合作始于 1979 年,当时 Brassard 向 Bennett 提出利用量子力学制造"不可伪造的纸币"的想法。随着量子计算的飞速发展,传统公钥加密体系正面临严峻挑战,量子通信(QKD)与后量子密码(PQC)已成为保障未来数字通信安全的双重核心路径。2026-03-16 09:09a16z 联创:马斯克或已破解最优管理法,每天进行 120 次工程师设计审查Gate News 消息,3 月 16 日,a16z 联合创始人 Andreessen 在访谈中评价马斯克的公司管理方式,称其或许已破解未来 100 年最优的管理模式。该方法的核心是完全绕过中间管理层,CEO 直接与一线工程师对接。马斯克每天进行约 120 次工程师设计审查,每次 5 分钟,每小时 12 次,持续约 10 小时,目标是识别当前最关键的生产瓶颈,并当天亲自配合工程师解决。Andreessen 将这套方法与他在 IBM 实习时见到的"大灰云"管理模式对比:IBM 层层经理将 CEO 与实际技术工作彻底隔绝,CEO 只能收到被粉饰的信息。特斯拉持续领先传统车厂的本质在于,马斯克每年亲手修复 52 次关键生产瓶颈,而传统公司解决同等问题往往需要数月。这套方法还形成了正向人才循环:全球顶尖工程师争相加入马斯克的公司,因为他是唯一能以工程同行身份与一线人员并肩工作的 CEO。Andreessen 坦言这套方法几乎无法复制,他以假想单位"毫马斯克"(milli-Elon)衡量创始人成色:多数创始人处于 0.1 至 1 个 milli-Elon 区间,达到 500 个 milli-Elon 的创始人他会倾囊支持。2026-03-11 03:32IBM 与 Signal、Threema 合作设计抗量子攻击加密消息系统Gate News 消息,3 月 11 日,IBM 研究人员正与加密消息应用 Signal 和 Threema 合作,设计能够抵御量子攻击的消息系统。密码学研究员 Ethan Heilman 指出,由于"先存储,后解密"攻击的可能性,加密消息平台面临的近期量子风险可能比比特币更大——攻击者现在拦截并保存加密数据,待未来量子计算机成熟后破解。Signal 已在 2023 年推出 PQXDH 升级以保护新会话,2025 年通过 SPQR 协议升级将后量子保护扩展到持续消息、通话和媒体。Threema 正与 IBM 合作探索将 NIST 标准化的 ML-KEM 算法集成至其系统。研究同时关注保护元数据,但简单替换现有组件可能导致带宽大幅增加,需从底层重新设计协议。

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CryptocurrencySniper

2 ore fa
当前A股最耀眼的板块就是“光”,光模块、光纤、光器件、光芯片等概念股均是“热门行业里的热门股”,机构对通信板块的配置比例也高达13.1%,资金抱团现象明显。   对于普通投资者来说,要不要站在“光”里?取决于三件事,一是公司和产业是否看得明白,二是估值是否算得明白,三是是否真正忠于自己。   “抱”与“不抱”并非投资的核心。如果看不清楚,算不明白,仅仅是被市场乐观情绪裹挟,那抱团逐“光”意味着巨大的风险;如果看得清楚,算得明白,忠于自己的原则,那么他人的“抱”与“不抱”都不重要,虽千万人吾往矣。   **能否看得清楚**   巴菲特十年前以350亿美元投资苹果公司,今天总价值已经升至1850亿美元,这无疑是世界上最成功的投资案例之一。   看得清楚,是巴菲特投资苹果公司的前提。在2017年的时候,巴菲特曾在公开场合提到苹果,也是他第一次阐述对于苹果的看法:“苹果公司更像一家消费品公司,而不是科技企业。我们可以用护城河理论去分析苹果公司的商业模式——IBM和苹果的客户是不同的,这是两个不同决策下的项目。”   “光”产业相关公司均不是消费品公司,它们更像IBM,而不是苹果公司。无论是光芯片、还是光模块,它们都是中间品,需要嵌入下游公司的产品,再由下游公司通过产品或服务提供给消费者。   普通投资者很难像消费品那样去直接跟踪“光”公司的相关产品。那么,普通投资者对“光”行业的信息,均来自机构等其他第三方。当这些信息传到普通投资者耳朵中时,信息的时差早已发生。且不说,自己如果是行外人,连信息的真伪都无法辨别。人们大概率玩不好一个自己不懂的游戏。   芒格曾说过,“除非我能比别人更有力地反驳自己的观点,否则我对这个问题没有发言权。”在投资上亦如此,除非你真正懂这个行业和这家公司,否则一定在投资中处于弱势地位,必然会导致上涨时匆忙买入,下跌时急于割肉。   投资的大厦需要建立在“懂”的基础上。在段永平、巴菲特持有苹果公司的十年时间中,苹果公司曾有多次股价“腰斩”。一个不懂苹果公司的人,很难在股价下跌之际坚持住。懂这家公司的标准就是,下跌时有意愿买入更多的股份,而不是逃之夭夭。   **能否算得清楚**   “懂”是定性指标,而以什么样的估值买入则是定量指标。十年之前,当巴菲特出手买入苹果时,苹果公司的动态估值仅有10倍。巴菲特追加买入时,苹果公司的估值也不超过15倍。   即使对于一个现金储备丰富、经营现金流滚滚、分红和回购不断、拥有定价权且占据全球消费者心智份额的头部公司来说,巴菲特也没有盲目出手。只有当定价极度便宜、落在买入舒适区时,他才挥棒击打。   价值投资者本能地对“热门行业里的热门公司”充满警惕,因为这类公司的价格太高,不具有他们追求的安全边际。所谓的安全边际听起来像财务术语,但其实是一种自我保护的思维方式。在这种思维方式下,即使发生了非常糟糕的事情,投资者也不至于亏损太多。   A股逐“光”公司的估值远高于市场整体估值,也高于成熟市场同类公司的估值。投资者可能会用未来三五年的利润增速进行估值,判断该公司并不贵。但投资的难点是,三五年的时间中,公司会面临太多不确定性。如果没有给这种不确定留下足够的空间,那么一旦坏运气来临,估值与股价将大幅跳水。   巴菲特在10倍估值时买入苹果公司,意味着即使苹果公司未来没有增长,10年的时间也可以收回成本。苹果公司已经获取了投资者的心理份额,10年之内竞争格局也不会有太大改变。A股价值投资大佬张尧“20年2000倍”,在过去10年,他对陕西煤业的投资为他带来近10倍的收益,他正是将投资的原则建立在以当前看估值已属便宜、以未来看估值更便宜的基础上。   张尧给出了更清晰的投资标准:投资于以分红的形式5到6年可以回本的公司。张尧的这一衡量标准包含了低估值、高分红、高现金流、利润可持续(并不需要高增长)、公司能见度高等朴实的价投标准。   买得好才能卖得好,安全边际是一种容错机制。长期来说,投资一定会犯错,坏运气也会降临。投资需要为此做出准备,不宜将估值给得激进,为投资的犯错留足余地。   **是否独立决策**   当热门板块持续大幅上涨时,很容易让旁观者失去理性。人很难对抗市场情绪,尤其是当身边的人貌似都在赚大钱的时候。但如果是基于市场情绪做出的决策,那么就像玩一个“击鼓传花”的游戏,投资者在赌自己接的不是“最后一棒”。然而,市场情绪是一种燃料,燃料总有耗尽之时,当它把所有做多的力量吸纳过来时,多空转化总在不经意间发生。   巴菲特近期在接受记者采访时将市场比作“附带赌场的教堂”:人们可以在教堂与赌场之间自由切换。目前身处“教堂”(价值投资)的人仍多于“赌场”(短期投机),但赌场的诱惑力已变得极强。   如果投资者是基于产业、公司和估值独立做出投资的判断,那么“抱”与不“抱”都没关系,不因“抱团”而不投,也不因不“抱团”而不投;但如果基于市场情绪做出的判断,那么就意味着将投资的命运交到了他人的手上。 (文章来源:券商中国)
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SleepTrader

SleepTrader

3 ore fa
_**Jennifer Nelson** is CEO of izzi Software._ * * * **Discover top fintech news and events!** **Subscribe to FinTech Weekly's newsletter** **Read by executives at JP Morgan, Coinbase, Blackrock, Klarna and more** * * * In an industry obsessed with the newest wave of technology, it’s easy to forget that some of the strongest pillars in financial infrastructure have stood for decades. While **fintech** innovation is often framed as a race toward the future, the backbone of global banking quietly remains anchored in systems many wrongly dismiss as relics: the mainframe. This isn’t just a matter of nostalgia or corporate inertia. Mainframes still process the bulk of the world’s financial transactions, with a reliability and scale unmatched by many newer platforms. Their ability to handle vast volumes of data in real time, without compromising security, has made them indispensable in a financial system that depends on both speed and trust. **Yet, for all their critical role, mainframes are often misunderstood**. In today’s climate, where “cloud-first” is the default mantra, it can feel counterintuitive to defend older technologies. But calling the mainframe a legacy system oversimplifies a much more complex truth. To understand why, we need to examine the balance between heritage systems and the modern push toward hybrid infrastructures. **The Case for Modernization with Caution** ------------------------------------------- Financial institutions are under relentless pressure to modernize. Investors, customers, and regulators expect seamless digital services, hardened security, and ever-faster performance. **For many leaders, the temptation is to pursue change aggressively** — to shed old systems and move wholesale to the cloud. But modernization isn’t simply a technical project. It’s a strategic undertaking that carries risks when done hastily. Data that has lived securely inside a mainframe environment for decades becomes exposed the moment it is transferred elsewhere. Applications optimized for the mainframe may stumble when migrated, resulting in costly latency issues. These risks are more than hypothetical — they threaten daily operations, regulatory compliance, and even consumer trust. The lesson is clear: **true modernization isn’t about ripping out the old in favor of the new**. It’s about integrating strengths, phasing updates carefully, and ensuring that the next step forward doesn’t destabilize what already works. **A Skills Gap with Real Consequences** --------------------------------------- **Technology evolves faster than the expertise required to maintain it**. Nowhere is this more apparent than in the mainframe space. For years, banks and financial institutions have relied on a pool of engineers with deep institutional knowledge of IBM Z systems and related platforms. As many of those experts retire, the next generation has yet to fully replace their skill set. This creates a serious challenge. A shallow bench of expertise increases the risk of costly mistakes, even when protections are in place. The resilience of mainframes can’t fully compensate for the human factor. Until new engineers are trained and mentored, banks will face vulnerabilities not because of the technology itself, but because of the narrowing pool of professionals who know how to use it safely. **Security Is Still About People** ---------------------------------- When conversations about cybersecurity arise, much of the focus is on tools and defenses. Yet, time and again, the real weaknesses stem from human behavior. In the mainframe world, this often comes down to how permissions are granted, managed, and revoked. Developers who don’t fully understand the implications of elevated permissions may leave doors open, not out of malice, but out of incomplete training or convenience. Companies that fail to update access when employees shift roles can expose sensitive data unnecessarily. Even with sophisticated technology, the basics of security hygiene remain essential — and too often overlooked. **Introducing Jennifer Nelson** ------------------------------- To put these challenges and opportunities in context, we turned to Jennifer Nelson, CEO of Izzi Software. Nelson has built her career around mainframe systems, spending 15 years at Rocket Software and five years at BMC before broadening her perspective through senior engineering roles outside the IBM Z ecosystem. In 2024, she founded Izzi Software, a company dedicated to acquiring and growing businesses built on IBM Z and IBM Power platforms. Her vantage point — spanning traditional mainframe engineering and modern software leadership — makes her a rare voice in today’s conversation about technology strategy in financial services. **Enjoy the interview!** * * * **1. As fintech races toward cloud-native everything, you’ve argued that the mainframe remains critical to global banking stability. What do you think most innovators get wrong about the role of older systems today?** The first thing they get wrong is to call the mainframe a legacy system; that because they were launched more than 60 years ago they’re somehow obsolete. That’s like calling the Windows operating system a legacy platform. It’s just not reality. Mainframes are more relevant today than when they were first invented. Everybody wants data at the speed of light. They want data returned to them as soon as they press the button, no matter where that data sits. And rightly so because the end consumer wouldn’t know, and shouldn’t have to know, the complexities of their request, such as where the data sits. But only mainframes can give you the performance and security in a hybrid environment. Mainframes can ingest data anywhere it sits, analyze it, and report it back, complete with recommendations, better than any other platform, and faster. Show me another system that can ingest data from all across a global network, analyze it, detect anomalies in real-time, and send it right back to the caller.  **He who knows his data best wins because data is as precious as cash capital**. When innovators dismiss mainframes as legacy systems, they’re dismissing their speed and power, and the ability to process massive quantities of data at the speed required for real-time risk detection.  People think the cloud was game-changing and modern, and that mainframes are outdated by comparison. The concept of cloud computing across a network is indeed modern and game-changing for many. But if you’re familiar with mainframe technology, users will recognize it has many of the same characteristics as cloud. For example, when you log into the mainframe you’re logging in to TSO, short for “time sharing option”. You have your own TSO session, or Microsoft Teams ‘instance’. You’re all using the same processors on the mainframe. But when you’re not running a program or batch job, capacity is given to those who need it. You also are logging into an LPAR, or logical partition, complete with dedicated storage, security and privacy. Users on one LPAR can’t access data on another LPAR, unless specifically configured to do so. That’s what the cloud is at its core; sharing resources when you aren’t using them, and securing data dedicated to your instance. But the mainframe’s been using these concepts for years.   **2. Hybrid infrastructure—mixing mainframes with newer cloud layers—is becoming the norm. From your experience, what are the real risk factors introduced when organizations try to modernize too quickly or superficially?** Of the multiple risk factors, I can boil it down to two.  **The first risk is data consumption**. The data on a mainframe is some of the most secure data anywhere. When you take it off the mainframe or make it visible to someone ingesting that data, there's a risk to data privacy and regulation. Who's looking at it? Where is it going when it leaves the mainframe? **The second risk is in optimizing applications to run in a hybrid environment**. Applications optimized for the mainframe may end up running sub-optimally on another server. Latency and performance issues could harm productivity.  **3. You’ve raised the alarm about a skills gap in mainframe expertise. How serious is the institutional risk when fewer engineers know how to operate and secure the systems financial institutions still depend on?** The risk is severe. Newer developers — not just younger, but those new to the industry — will learn and grow their expertise. But until the next generation catches up, there will be an exposure at financial institutions for some time when institutional knowledge is not as deep as it needs to be.  Folks with a shallow depth of experience or knowledge may do things inadvertently to cause risk to data or to an operating system. These systems are resilient and have several layers of protection against human error, but there's still a fair amount of risk until skills are where they need to be. Banks are already battling this skills gap today. **4. Security conversations often focus on tools, but you've pointed out that people are still the frontline. What operational blind spots have you seen emerge most often in the management of mainframe environments?** Managing relevant environments usually centers around elevated permissions. When a software engineer is writing code, they sometimes need an elevated permission to do something specific on the operating system, where they can enable the program to do something more sensitive. If the engineer misunderstands the developer’s best practices when writing software, they won’t know when to go in and out of that elevated authorized state. That state brings more risk, so engineers won’t stay in it long enough to fully understand the best practices when developing for that system. There are also some fundamental security best practices to use in any IT network. When you give special authorization to someone in a certain role, you need a clear process in place to remove that authorization when they switch roles, to ensure you remove access. Much of the time it’s not an issue, if they’re either still an employee of the company or not a bad actor. But there's always a risk when leaving too much sensitive data available to people who no longer need it.  Furthermore, mainframe system-level data sets allow users to do fundamental things to a system. You only want certain users to have access to those functions. For example, certain security controls can only be toggled at the deeper levels of the operating system. You would be surprised at how often companies leave basic security principles unchecked. There are ways for engineers to do their jobs without having access to those root-level resources, but it's easier to work with that level of access, so companies leave the backdoor open more than they should.  Most employees can be trusted, but these are fundamental principles some financial institutions leave open and forget about. **5. Ransomware attacks are targeting not just endpoints, but core infrastructure. What makes legacy systems both uniquely vulnerable—and, in some cases, more resilient—than newer platforms?** Mainframes have built-in layers of security that most servers just lack. Just because you can log into the mainframe doesn't mean you now have access to business-critical data, which is what ransomware usually locks down. You then have to know where the data is, and how to access that data. And then the data might be compartmented, so an invader only has access to a segment of the data and not everything they need for a successful ransomware attack. And if you don't have access to the storage device, you can't see the data on that device.  **6. From your experience, what does effective modernization actually look like for financial institutions that can't afford to “rip and replace” but need to be future-proofed?** Modernization means different things at different companies because of where they are with the applications they run. Whether B2B or B2C, companies are modernizing continually, upgrading servers and laptops.  The same thing happens with business critical applications. A business might periodically update those applications, but because traditional mainframe applications were developed generations ago, the best thing companies can do is fully assess what each application does end-to-end. That way they can phase their modernization in manageable pieces.  Companies can compartmentalize an application, breaking it into pieces so the different features and functions get upgraded and rewritten slowly over time as is affordable. If you look at modernization as an ongoing process, the urge to improve and iterate becomes continual.  Leaders should always have a proactive mindset. The questions should be: “What can we do now? What can we contain this year? What can we contain in the next two years?” That’s a better approach than “how do we rewrite this whole thing?” You have to iterate on systems and build them out over time. Start by rewriting one feature of a business-critical application, then build on that by adding the rest of the features as you can. Phase changes in a little at a time.  Rip-and-replace is one option. It sounds raw and brutal, but all it really means is to stop using one system to use another. But leadership needs to have the stomach for a big change all at once, and has to approve the budget. The truth is, it’s more just “replace,” because it can take years to complete the procedure.  **7. For tech leaders coming from a cloud-first mindset, what would you say is the most important shift in thinking when engaging with mission-critical mainframe systems?** Learn what the mainframe is actually doing. The Hippocratic Oath says to first do no harm, so learn what the mainframe is responsible for to keep from making harmful errors. Once those with a cloud-first mindset understand the totality of what transactions are coming into the mainframe, the nature of those transactions, and how much their company's revenue depends on those transactions, they'll understand and know how to avoid damaging their company’s performance and profitability. * * * ### **About Jennifer Nelson** Jennifer Nelson has spent the most of her career in the mainframe space, including 15 years at Rocket Software and five years at BMC. In 2019, she transitioned into senior engineering roles at global technology firms outside the Z Systems ecosystem, broadening her perspective and skill set. In early 2024, Nelson began laying the foundation for what would become Izzi Software, a company focused on acquiring and growing software businesses built on IBM Z and IBM Power platforms.
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