RACE

Ferrari NV Price

RACE
$327.85
-$11.84(-3.48%)

*Data last updated: 2026-05-11 14:59 (UTC+8)

As of 2026-05-11 14:59, Ferrari NV (RACE) is priced at $327.85, with a total market cap of $59.95B, a P/E ratio of 35.17, and a dividend yield of 1.24%. Today, the stock price fluctuated between $327.96 and $333.57. The current price is 0.03% above the day's low and 1.71% below the day's high, with a trading volume of 617.80K. Over the past 52 weeks, RACE has traded between $322.67 to $379.61, and the current price is -13.63% away from the 52-week high.

RACE Key Stats

Yesterday's Close$337.46
Market Cap$59.95B
Volume617.80K
P/E Ratio35.17
Dividend Yield (TTM)1.24%
Dividend Amount$4.24
Diluted EPS (TTM)9.03
Net Income (FY)$1.59B
Revenue (FY)$7.14B
Earnings Date2026-07-30
EPS Estimate2.88
Revenue Estimate$2.20B
Shares Outstanding177.68M
Beta (1Y)0.587
Ex-Dividend Date2026-04-21
Dividend Payment Date2026-05-05

About RACE

Ferrari N.V., through its subsidiaries, designs, engineers, produces, and sells luxury performance sports cars. The company offers sports, GT, and special series cars; limited edition hyper cars; one-off and track cars; and Icona cars. It also provides racing cars, and spare parts and engines, as well as after sales, repair, maintenance, and restoration services for cars. In addition, the company licenses its Ferrari brand to various producers and retailers of luxury and lifestyle goods; Ferrari World, a theme park in Abu Dhabi, the United Arab Emirates; and Ferrari Land Portaventura, a theme park in Europe. Further, it provides direct or indirect finance and leasing services to retail clients and dealers; manages racetracks, as well as owns and manages two museums in Maranello and Modena, Italy; and develops and sells a line of apparel and accessories through its monobrand stores. As of December 31, 2021, it had a total of 30 retail Ferrari stores, including 14 franchised stores and 16 owned stores. The company also sells its products through a network of 172 authorized dealers operating 191 points of sale worldwide, as well as through its website, store.ferrari.com. Ferrari N.V. was founded in 1947 and is headquartered in Maranello, Italy.
SectorConsumer Cyclical
IndustryAuto - Manufacturers
CEOBenedetto Vigna
HeadquartersMaranello,MO,IT
Official Websitehttps://www.ferrari.com
Employees (FY)5.71K
Average Revenue (1Y)$1.24M
Net Income per Employee$279.27K

Learn More about Ferrari NV (RACE)

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Ferrari NV (RACE) FAQ

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Ferrari NV (RACE) is currently trading at $327.85, with a 24h change of -3.48%. The 52-week trading range is $322.67–$379.61.

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Ferrari NV (RACE) Latest News

2026-05-07 15:02Trump Endorses Crypto-Friendly Politician Barry Moore for Alabama Senate RaceAccording to Foresight News, President Trump recently endorsed Barry Moore for Alabama's U.S. Senate seat, calling him "one of my favorite people" and a "completely reliable MAGA warrior" deserving his "complete and total endorsement." Moore is among the first U.S. Congress members to publicly disclose cryptocurrency holdings and is viewed as a crypto-friendly politician advocating for reduced government regulation of digital assets.2026-05-04 00:20U.S. Voter Trust in Trump's Crypto Regulation Drops to 62% Ahead of 2026 MidtermsAccording to CoinDesk, 62% of U.S. voters do not trust the Trump administration's ability to regulate cryptocurrencies, ahead of the 2026 midterm elections. In a poll of 1,000 registered voters, only 1% cited crypto assets as a key issue in the midterm race, while 36% prioritized the cost of living. Meanwhile, voter perception of the two parties has shifted. When asked which party would better manage cryptocurrency policy, 27% favored the Democratic Party compared to 25% for the Republican Party, with approximately 40% trusting neither party.2026-04-30 06:00Gate Exchange marks its 13th anniversary in Hong Kong, partnering with the Red Bull F1 team to host a cross-industry exhibition and an industry summitGate News, according to an official announcement dated April 30, 2026 Crypto trading platform Gate held a 13th-anniversary series of celebrations in Hong Kong from April 16 to April 22. During the event, Gate partnered with the Red Bull F1 team for a display of a racing parade in Victoria Harbour, followed by an outdoor cross-industry exhibition titled “Racing the Future: Racing the Future” at the seafront promenade of K11 MUSEA. The exhibition showcased the Red Bull F1 team’s brand-new 2026 race car and core equipment, and featured immersive interactive experience areas. On the first day of the opening, on-site foot traffic surpassed 10,000 people. On April 20, Gate held a blue carpet ceremony at K11 MUSEA in Hong Kong. Founder and CEO Dr. Han attended and delivered a speech. Later that evening, the platform hosted the “GATE GALA 13” anniversary banquet at the Hong Kong Royal Garden Hotel, bringing together more than 300 institutional representatives, partners, and industry guests from around the world. Dr. Han delivered a speech titled “How We Grow Together in the Crypto Industry,” and Gate CCO Simon Ren, along with Addis Hu, Global Institutional Head, and others also gave keynote speeches. In addition, Dr. Han delivered a keynote speech titled “Move Everything On-Chain” on the main stage of the Hong Kong Web3 Carnival, and shared industry insights at the event “Web3 Dialogues @ HKU” hosted by The University of Hong Kong. On April 22, Gate also held the “Institutional Circle: AI Reshaping Crypto Liquidity & Market Access” institutional exchange event, focusing on how AI is reshaping the ways crypto liquidity and market access are handled.2026-04-29 09:162U2.ai Completes $1.5M Strategic Funding Round at $30M ValuationAccording to ChainCatcher, 2U2.ai completed a $1.5 million strategic funding round with a $30 million valuation. Investors include CGV, Becker Ventures, K24 Ventures, and Gemhead Capital. The Web3 MemeLayer infrastructure platform has launched its Meme Arms Race points system and will use the funding to enhance product infrastructure, expand ecosystem partnerships, and drive adoption of meme-related applications in Web3.2026-04-22 22:12OpenAI Reaches $1 Trillion Pre-IPO Valuation Amid Race with SpaceX and AnthropicGate News message, April 22 — OpenAI has reached an implied $1 trillion pre-IPO valuation, according to on-chain pre-IPO instruments trading on Jupiter backed by SPV exposure. The valuation has surged 163% since October 2025, when speculation about a potential $1 trillion-plus IPO first emerged. SpaceX is reportedly targeting a valuation exceeding $1.7 trillion, while Anthropic is approaching the same $1 trillion milestone. These three companies are now in a high-stakes race to become the next major public listing. OpenAI's path to this valuation reflects the escalating costs of generative AI. A single ChatGPT exchange can cost $0.01 to $0.10, while high-definition image generation ranges from $0.10 to $0.20. With billions of daily requests in 2026, the computational demands are staggering. GPUs—primarily supplied by Nvidia—cost tens of thousands of dollars each, and cloud access runs several dollars per hour per chip. Industry estimates suggest that infrastructure investment could reach hundreds of billions of dollars by the end of the decade. OpenAI originally aimed to build AI "beneficial to humanity" and prevent a few firms from controlling the field. However, mounting costs forced a shift. In 2019, the company adopted a hybrid structure combining foundation control with capital-raising capabilities. ChatGPT's launch in late 2022 accelerated this transformation, reaching 100 million users in two months and 900 million weekly active users by early 2026. Revenue followed suit: from approximately $200 million in 2022 to over $10 billion in 2025—a 60-fold increase. OpenAI's subscription tiers now range from $20 to $200 monthly for consumers, while enterprise plans cost $25 to $60 per user per month. A company with 10,000 employees can therefore generate several million dollars in annual revenue. Meanwhile, Anthropic faced a pricing backlash when Claude Code appeared to vanish from its $20-per-month Pro tier, seemingly requiring a $100-per-month subscription instead. Anthropic later clarified the pricing page change affected only 2% of new sign-ups and that existing users saw no change. During the confusion, Sam Altman and OpenAI staff used the moment to promote Codex, OpenAI's competing coding tool.

Hot Posts About Ferrari NV (RACE)

BeautifulDay

BeautifulDay

8 minutes ago
#CryptoMinersPivotToAIDC The crypto mining industry is entering a major transformation phase as traditional mining operations begin shifting toward AI data center infrastructure. With rising operational costs, increasing mining difficulty, and fluctuating market conditions, many large-scale miners are now looking beyond Bitcoin rewards and exploring artificial intelligence as the next long-term growth opportunity. This transition is not happening randomly. AI development requires enormous computing power, advanced cooling systems, stable electricity, and large-scale hardware deployment. Interestingly, crypto mining companies already possess most of this infrastructure. Mining farms built for high-performance GPU and ASIC operations are now being redesigned to support AI model training, cloud computing, and machine learning workloads. Several mining firms have started converting their facilities into AI-ready data centers because the demand for AI computing continues to rise globally. The rapid expansion of AI technologies across finance, healthcare, robotics, cybersecurity, and automation has created a massive need for processing capacity. Instead of relying entirely on volatile crypto cycles, miners now see AI infrastructure as a more stable and scalable business model. Another important factor behind this shift is energy optimization. Mining companies have spent years securing low-cost power agreements and building energy-efficient operations. These advantages are now becoming extremely valuable for AI computing companies that require continuous power-intensive performance. In many cases, crypto miners are partnering directly with AI firms to lease infrastructure and computing resources. From a market perspective, this trend could reshape both industries. Crypto mining may gradually evolve into a broader digital infrastructure sector, while AI companies gain access to ready-made computing facilities without spending years constructing new centers from scratch. Investors are closely watching this development because it represents a fusion between blockchain infrastructure and artificial intelligence expansion. However, the transition is not without challenges. AI hardware requirements differ from traditional mining systems, and upgrading facilities demands significant capital investment. Companies must also compete with established cloud giants already dominating the AI infrastructure space. Despite this, many miners believe diversification is necessary for long-term survival. The shift toward AI data centers also reflects a broader evolution in technology markets. Infrastructure is becoming more valuable than speculation alone. Companies that can provide scalable computing power, efficient energy management, and advanced processing capabilities may dominate the next decade of digital innovation. As AI adoption accelerates worldwide, crypto miners positioning themselves early in this sector could gain a major competitive advantage. The industry is no longer focused only on mining digital assets; it is increasingly becoming part of the global race for computational power and next-generation technology leadership. #CryptoMinersPivotToAIDC #AIInfrastructure #CryptoMining
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mev_me_maybe

mev_me_maybe

15 minutes ago
Just came across this interesting perspective on enterprise blockchain adoption from Neyma Jahan, founder of Unification, and it's refreshing to see someone actually thinking about real-world utility instead of just coin speculation. Neyma Jahan spent years in IoT before jumping into blockchain in 2017, and his approach is fundamentally different from most projects. Instead of building another speculative token play, he identified a core problem: enterprises and governments are drowning in data silos that can't communicate. The blockchain angle isn't about making money from token volatility—it's about creating trust where it doesn't exist. What caught my attention is the hybrid model. Unification runs both a public Mainchain (fully transparent, community-validated) and Workchains (semi-private deployments for specific communities). Think about it: if you're an insurance consortium tracking patient billing to prevent fraud, you don't need everything on a public blockchain. You need a controlled environment where 10-15 parties can verify transactions immutably without the noise of a global network. The real-world cases are solid. In Latin America, they're tackling insurance fraud by giving each patient-doctor pair a unique identity on a shared Workchain. In motorsports, technical compliance records stay immutable on a semi-private chain so teams can't cheat post-race. In Brazil, they've got 2 million users on a health records system. Imagine forcing 2 million people to hold ETH just to access their medical data—it doesn't work. With Neyma Jahan's model, end users pay nothing, enterprises just pay minimal UND fees when they anchor blocks to the public Mainchain. The governance is interesting too—DSG (Distributed Stake Governance) means the top 96 UND stakers validate blocks every 72 hours using PBFT consensus. It's designed so users are inherently invested in the network's success, not just gambling on price movements. What Neyma Jahan kept emphasizing is this: most blockchain startups are building for investors and speculators, not actual users. They ask "who's my customer?" and the answer is the wrong person. Real adoption comes from solving a business problem so clearly that enterprises actually want to deploy your tech. That's why he compares Unification to Linux or RedHat—the end goal is to be infrastructure that just works, not a coin you trade. Unification was backed by Yellow Capital and Gems Capital, and UND is listed on Digifinex. The vision for 2019 was public mainnet launch in Q3, but the broader mission has always been about proving blockchain doesn't need speculation to drive adoption. Whether that's playing out now is worth watching.
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BlockchainBard

BlockchainBard

27 minutes ago
Just noticed something wild in Leopold Aschenbrenner's latest 13F filing—and I mean this guy is genuinely playing a different game than everyone else in the AI hedge fund space. For context, this 24-year-old took his fund from $1 billion to $5.5 billion in about a year. Most people are obsessing over his returns, but what really stands out is the complete portfolio pivot he just executed. And I think most investors are completely missing what he's actually doing. Let me break down what caught my attention. First, the exit. He sold off massive positions in Nvidia, Broadcom, TSMC, and Micron. And I'm talking serious money here—he had $300 million in Nvidia put options that he liquidated. This is the part where most people check out because, well, Nvidia is still the darling of the market. Everyone's watching nvidia premarket stock price movements like it's the heartbeat of AI infrastructure. But Leopold's thesis is that by end of 2025 or early 2026, the market would have fully priced in GPU value. He's not wrong. The GPU boom already happened. Now he's moved on. The real story is where he's putting the money instead. His largest position? Bloom Energy. Twenty percent of his entire portfolio. That's roughly $855 million in a company most people have never heard of. And honestly, when I first saw this I thought it was a mistake. But then I looked into their actual business. Bloom Energy makes oxide fuel cells that convert natural gas directly into usable electricity on-site at data centers. No grid dependency. No waiting for power infrastructure upgrades. Just install it next to your AI data center and you've got power. Their order backlog is sitting at $20 billion. Revenue grew 34% in 2025, and they're projecting 40% growth for 2026. The demand is absolutely crushing supply. Here's what Leopold seems to understand that others don't: the bottleneck isn't chips anymore. It's power. The existing electrical grid was built for humans, not for AI data centers running 24/7. Every major tech company—Google, Meta, Amazon—is now fighting for grid access. But if you own the energy infrastructure instead of depending on it, you've solved the problem before it even exists. It's like he's identifying the real constraint in the AI arms race. Everyone else is still focused on GPU procurement and nvidia premarket stock price movements. Leopold moved past that. He's betting that energy production capacity becomes the new moat. Then there's CoreWeave. He added $300 million to this position, bringing his total exposure to roughly $800 million. CoreWeave is basically the infrastructure layer between raw GPUs and deployed AI applications. They handle the deployment, power distribution, cooling, engineering support—all the physical logistics that Nvidia doesn't touch. He's also holding about 10% of Core Scientific, which supplies energy infrastructure to CoreWeave. So he's essentially double-betting on the GPU deployment infrastructure plus its power requirements. But here's where it gets really interesting. He's been quietly accumulating Bitcoin mining companies. At first glance this seems bizarre. Bitcoin's been in a bear market, crypto's been sideways, so why buy mining operations? The answer is almost embarrassingly simple: these companies already own the two things that are hardest to acquire for AI infrastructure—land and grid access. Obtaining grid connection permits and land use rights typically takes months or years. Leopold just bought companies that already had them. It's like buying a bar that already has a liquor license instead of applying for one yourself and waiting two years. He's essentially fast-tracked his path to having deployable AI infrastructure by acquiring these Bitcoin mining properties and repurposing them. That's not a cryptocurrency bet. That's a real estate and infrastructure play disguised as a crypto investment. The short position is equally revealing. He shorted Infosys, a massive IT outsourcing company whose entire business model is built on providing cheaper labor from India to replace Western IT workers. Leopold's thesis: AI code generation tools like Claude and GPT-4 have reached the point where they can automate not just simple tasks but complex IT processes. The arbitrage that made Infosys profitable—cheap labor—disappears when AI can do it faster and better. It's a bet that's already starting to look prescient. What really ties all this together is the philosophical shift. Leopold's essentially moved from betting on software and chips to betting on physical world assets. Manufacturing capacity, energy production, real estate, permits, grid access—the unglamorous stuff that can't be built with code. This is the part that stuck with me: energy is the only resource nobody has enough of. Whether you're talking about power generation or real estate investment, everything circles back to one core question—who controls the power supply for AI infrastructure? That's why his portfolio looks so different. While everyone else is still analyzing nvidia premarket stock price action and GPU availability, he's already three steps ahead, securing the actual power infrastructure that makes GPUs useful. Bloom Energy for on-site generation, CoreWeave for deployment infrastructure, Bitcoin mining companies for land and permits, and strategic shorts on businesses that lose their competitive advantage in an AI-automated world. The concentrated nature of this portfolio is definitely risky. He's put enormous conviction into specific bets rather than diversifying broadly. But if his thesis is correct—and so far it's been eerily accurate—then the returns could be extraordinary. Growing $1 billion to $5.5 billion in a year isn't luck. It's identifying the real constraint before the market prices it in. I think what's happening here is that Leopold's essentially created a real-time tracking system for AI infrastructure bottlenecks. First it was GPUs. Now it's energy. Next it'll probably be something else nobody's thinking about yet. But the pattern is clear: find what's actually limiting AI deployment, then own the infrastructure that solves it. The question for everyone else is whether they can identify the next bottleneck before Leopold does. Because at this point, betting against his analysis seems like a losing proposition.
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