COST

Precio en Costco Wholesale Corp

COST
€875,32
-€3,12(-0,35%)

*Datos actualizados por última vez: 2026-05-14 08:42 (UTC+8)

A fecha de 2026-05-14 08:42, Costco Wholesale Corp (COST) tiene un precio de €875,32, con una capitalización de mercado total de €391,27B, un ratio P/E de 51,71 y un rendimiento por dividendo de 0,51%. Hoy, el precio de la acción ha oscilado entre €874,24 y €877,63. El precio actual está 0,12% por encima del mínimo del día y 0,26% por debajo del máximo del día, con un volumen de trading de 1,63M. Durante las últimas 52 semanas, COST ha cotizado entre €799,93 y €890,20, y el precio actual está a -1,67% del máximo de las últimas 52 semanas.

Estadísticas clave de COST

Cierre de ayer€872,38
Capitalización de mercado€391,27B
Volumen1,63M
Ratio P/E51,71
Rendimiento por dividendo (últimos doce meses)0,51%
Cantidad de dividendos€1,25
BPA diluido (últimos doce meses)19,25
Ingresos netos (ejercicio fiscal)€6,91B
Ingresos totales (ejercicio fiscal)€234,96B
Fecha de ganancias2026-07-29
BPA estimado4,95
Estimación de ingresos€58,64B
Acciones en circulación448,51M
Beta (1A)0.908
Fecha exdividendo2026-05-01
Fecha de pago de dividendos2026-05-15

Sobre COST

Costco Wholesale Corporation, junto con sus filiales, se dedica a la operación de almacenes de membresía en Estados Unidos, Puerto Rico, Canadá, Reino Unido, México, Japón, Corea, Australia, España, Francia, Islandia, China y Taiwán. Ofrece productos de marca y de marca propia en una variedad de categorías de mercancía. La compañía ofrece artículos diversos, comestibles secos, caramelos, enfriadores, congeladores, licores y productos de tabaco y delicatessen; electrodomésticos, electrónica, productos de salud y belleza, ferretería, productos para jardín y patio, artículos deportivos, neumáticos, juguetes y productos de temporada, papelería, productos para cuidado del automóvil, sellos, entradas, ropa, pequeños electrodomésticos, muebles, artículos para el hogar, utensilios domésticos, quioscos de pedidos especiales y joyería; y carne, productos agrícolas, delicatessen de servicio y productos de panadería. También opera farmacias, ópticas, centros de comida, centros de audífonos y centros de instalación de neumáticos, además de 636 estaciones de servicio; y ofrece servicios de entrega para negocios, viajes, compras en el mismo día y otros diversos servicios en línea en varios países. Al 29 de agosto de 2021, la compañía operaba 815 almacenes de membresía, incluyendo 564 en Estados Unidos y Puerto Rico, 105 en Canadá, 39 en México, 30 en Japón, 29 en Reino Unido, 16 en Corea del Sur, 14 en Taiwán, 12 en Australia, 3 en España, 1 en Islandia, 1 en Francia y 1 en China. También opera sitios web de comercio electrónico en Estados Unidos, Canadá, Reino Unido, México, Corea del Sur, Taiwán, Japón y Australia. La compañía fue anteriormente conocida como Costco Companies, Inc. y cambió su nombre a Costco Wholesale Corporation en agosto de 1999. Costco Wholesale Corporation fue fundada en 1976 y tiene su sede en Issaquah, Washington.
SectorDefensa del consumidor
IndustriaTiendas de descuento
CEORon Vachris
Sede centralIssaquah,WA,US
Sitio web oficialhttps://www.costco.com
Empleados (año fiscal)341,00K
Ingresos medios (1 año)€689,05K
Ingresos netos por empleado€20,27K

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Costco Wholesale Corp (COST) cotiza actualmente a €875,32, con una variación en 24 h del -0,35%. El rango de trading de 52 semanas es de €799,93 a €890,20.

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Últimas notícias sobre Costco Wholesale Corp (COST)

2026-05-13 14:08El Departamento de Defensa de EE. UU. adquirirá más de 10.000 misiles baratos en contenedores a partir de 2027El Departamento de Defensa de EE. UU. anunció el 13 de mayo acuerdos marco con los contratistas de defensa Anduril, CoAspire, Leidos y Zone 5 para misiles containerizados de bajo costo. Bajo el plan, el departamento busca adquirir más de 10.000 unidades en un período de tres años a partir de 2027.2026-05-13 10:29Suiza detiene los pagos al gobierno de EE.UU. por problemas de entrega y costos no resueltosSegún el gobierno de Suiza, el país ha suspendido los pagos al gobierno de EE. UU. debido a cuestiones no resueltas sobre las fechas de entrega y los costos.2026-05-12 14:09Depthfirst detecta fallas críticas de Internet a un décimo del costo del «Mythos» de AnthropicSegún BlockBeats, el 12 de mayo, la startup de ciberseguridad con IA Depthfirst anunció que su modelo de descubrimiento de vulnerabilidades de IA desarrollado internamente encontró múltiples fallas de seguridad críticas que fueron omitidas por el Mythos de Anthropic, afirmando que el coste total era solo una décima parte del de este último. El CEO de Depthfirst, Qasim Mithani, dijo que la empresa puede «completar trabajos por 1.000 USD que Mythos necesitaría 10.000 USD para lograr» optimizando la arquitectura del modelo para el rendimiento en tareas únicas. Depthfirst también lanzó la «Open Defense Initiative», un programa de 5 millones de USD que ofrece sus herramientas de detección de vulnerabilidades de IA a empresas y desarrolladores de código abierto. La empresa descubrió una falla crítica en NGINX, el servidor web más utilizado del mundo, que existe desde 2008 y podría afectar potencialmente a numerosos sitios web a nivel global. Se espera que F5 Networks, que mantiene NGINX, publique un parche esta semana.2026-05-11 08:21Baidu lanza el modelo Ernie 5.1 al 6% del coste de entrenamiento comparableSegún Chosun Daily, Baidu lanzó hoy (11 de mayo) su modelo Ernie 5.1, ofreciendo un rendimiento comparable al de los sistemas líderes con aproximadamente el 6% del coste de preentrenamiento de modelos similares. En el benchmark Arena, Ernie 5.1 ocupó el primer lugar entre los modelos chinos y el cuarto en general, detrás de GPT-5.5 de OpenAI y de Claude Opus 4.6 y 4.7 de Anthropic.

Publicaciones destacadas de Costco Wholesale Corp (COST)

SleepTrader

SleepTrader

En este momento
_By **Hyunsu Jung**, CEO at Hyperion DeFi._ * * * **_The intelligence layer for fintech professionals who think for themselves._** Primary source intelligence. Original analysis. Contributed pieces from the people defining the industry. **Trusted by professionals at JP Morgan, Coinbase, BlackRock, Klarna and more.** **Join the FinTech Weekly Clarity Circle →** * * * Despite nearly two decades of development, experimentation, and finally adoption, one fundamental question remains unsolved in crypto: how does the value (if any) generated by a blockchain-based platform or product accrue back to its native token? Start with Bitcoin, the de facto face of crypto, which at its peak had several narrative tailwinds — digital gold, inflation hedge and institutional portfolio diversifier. Today, it trades approximately 45% below its all-time high while its physical counterpart proved to be the safe haven asset of choice for investors in times of monetary debasement and persistent volatility. This leaves Bitcoin in strategic limbo and investors uncertain of its value proposition. Ethereum paved the way for public blockchains built for smart contract applications, enabling DeFi (“Decentralized Finance”), stablecoins and permissionless financial services on-chain. Nearly 100 other Layer-1 blockchains followed, raising several billion dollars in aggregate funding to build “better tech”: higher throughput, lower latency blockchains with more flexible consensus mechanisms. But none of those improvements addressed the core problem of sustainable revenue models for supplying blockspace and direct value accrual to token holders. Because of this, most blockchains today are inflationary, issuing their native tokens to subsidize demand, and untethered from the economic activity that they facilitate. Put simply, token supply expands faster than token demand created through real usage. More recently, a new class of high-performance blockchains has emerged, designed around trading and other fee-generating applications. Some of these platforms now generate more daily revenue on average than legacy networks, at times accounting for a meaningful share of total on-chain revenue. In certain cases, a significant portion of that revenue is autonomously routed toward buyback and burn mechanisms tied to the network’s native token. As a result, portions of circulating token supply have been permanently removed from the market over time. In a few instances, these tokens have become structurally deflationary, meaning that the amount removed from circulation on a given day exceeds the amount issued to support network operations. These models are built around offering products that users are willing to pay to use — for example, decentralized exchanges operating seamlessly on-chain with fast execution and low cost. Notably, some of these platforms have been developed without heavy reliance on external funding, reducing potential overhangs on circulating supply. This shift has begun to reframe how investors evaluate token models. Increasingly, there is recognition that many tokens do not represent equity or enforceable claims on future protocol growth and adoption. In practice, these tokens were often artificial digital value created by the protocols to sell on the open market and fund operations. With massive token supply and diminishing organic demand, most tokens will trend in one direction: down. This feedback loop will likely accelerate as more tokens need to be sold to finance continued operating costs in a falling price environment. Because of this, investors are beginning to pay closer attention to token models where supply dynamics are directly linked to real platform usage. In models where fees are consistently used to remove tokens from circulation, sustained user activity can directly impact supply over time. In parallel, many of these networks are reducing emissions and token unlocks over time, further tightening supply dynamics. On the demand side, these tokens often have embedded utility. They may need to be staked to access benefits such as reduced fees, participation in new market deployments or eligibility for incentive mechanisms tied to ecosystem growth. Development teams are also continuing to introduce new demand drivers, particularly through the expansion of financial products on-chain. For example, newer protocol upgrades are enabling use cases like prediction markets, broadening the addressable user base beyond traditional crypto-native participants. As the product base expands, so does user participation, creating a flywheel effect that can accelerate fee generation and the associated removal of tokens from circulating supply. 2026 looks to be the year of the most significant institutional adoption of crypto and blockchain infrastructure. As this occurs, we may also see a shift in how investors assess the digital asset landscape and opportunities in liquid token investing. Due to the structural flaws in many blockchain protocols and their tokens, capital will likely continue migrating toward networks that demonstrate sustainable economic models and clearer pathways for returning value to their ecosystems.
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HighAmbition

HighAmbition

Hace 1 minutos
#SpotSilverUp10PercentForTheWeek Silver has delivered a powerful weekly performance, rising more than 10% within a single week and briefly testing the $89+ region after starting from the mid-$79 zone. This move has attracted strong attention from macro traders, hedge funds, and commodities desks because silver is now reacting not only as a traditional safe-haven asset but also as a high-beta macro instrument influenced by liquidity conditions, industrial demand expectations, and currency fluctuations. This analysis expands the structure with deeper price mapping, broader scenario modeling, and additional market drivers shaping silver’s current phase. Weekly Price Action Breakdown and Expanded Structure Silver’s weekly trajectory shows a clear acceleration from accumulation into breakout expansion, followed by momentum continuation. Weekly open: near $79.20 – $79.80 Early support retest: $79.25 low region First breakout impulse: $83.50 – $84.80 zone Strong momentum extension: $86.00 – $87.80 Mid-week continuation: $88.20 – $89.11 peak Total weekly expansion: approximately +10% to +12.5% range Additional intraday structure shows multiple liquidity grabs below $80 followed by aggressive buy-side expansion, confirming institutional participation rather than retail-driven volatility alone. This type of price behavior typically reflects: Liquidity accumulation below key support zones Short liquidation above resistance clusters Momentum re-pricing after multi-week compression Expanded Macro Drivers Behind the Rally 1. Safe-Haven Rotation and Risk Repricing Global risk sentiment has shifted toward defensive positioning. Silver is benefiting from the same macro rotation that typically supports gold, but with higher volatility amplitude. Key drivers: Rising geopolitical uncertainty across major trade routes Elevated global inflation expectations Increased hedging demand in commodity portfolios Silver often reacts more aggressively than gold during macro stress phases due to its smaller liquidity pool and dual demand structure. 2. US Dollar Weakness and Currency Sensitivity A weakening US dollar has played a central role in silver’s upside momentum. Dollar softness increases global purchasing power Commodity pricing becomes more attractive for non-USD buyers Capital inflows into metals increase during FX instability Silver historically shows strong inverse correlation with real USD strength, especially during macro transition phases. 3. Real Yield Compression Dynamics Silver responds strongly to real yield expectations rather than nominal rates alone. When real yields stabilize or decline: Opportunity cost of holding silver decreases Institutional allocations to non-yielding assets rise Momentum flows increase in precious metals Conversely, sharp yield spikes remain a key risk factor for correction phases. Extended Technical Structure and Key Price Mapping Silver is currently transitioning from a consolidation range into a broader expansion structure. Bullish Structure Levels $83.00 – $84.00: Critical reclaimed support zone $85.50: Micro trend stability threshold $87.00 – $88.50: Momentum continuation zone $89.11: Weekly swing high resistance $90.00 – $91.50: Psychological breakout cluster Major Upside Extension Levels $92.80: Intermediate expansion resistance $95.00 – $96.38: Key structural high zone $100.00: Psychological macro milestone level Support Structure $83.00: Primary breakout confirmation level $80.50: Mid-range liquidity support $79.25: Weekly structural base $77.80: Deep retracement support zone Sustained price action above $83 keeps the bullish structure intact, while acceptance above $90 would likely trigger acceleration into higher liquidity zones. Inflation Sensitivity and Data-Driven Volatility Silver remains highly reactive to macroeconomic data, particularly inflation releases and labor market signals. Key sensitivity factors: CPI prints above expectations → bullish volatility spike Cooling inflation → short-term consolidation risk Strong employment data → mixed pressure due to yield reaction The market is currently pricing uncertainty, which increases short-term volatility but supports medium-term directional expansion. Industrial Demand Expansion (Structural Support Layer) Unlike gold, silver maintains strong industrial consumption demand, which provides structural price support even during macro corrections. Major demand sectors: Solar energy infrastructure expansion Semiconductor manufacturing cycles Electric mobility components High-end electronics and medical systems This dual nature (monetary + industrial) creates a hybrid valuation model where silver responds to both macro liquidity and real economy growth cycles. Institutional Positioning and Market Sentiment Market positioning has shifted decisively toward bullish bias following the breakout above $83. Observed flows: Increased call option activity in silver-linked derivatives Short covering above $85–$87 zone Accumulation interest from macro funds during dips ETF inflows showing renewed interest in precious metals exposure However, sentiment is not one-sided: Some traders anticipate consolidation after rapid gains Others expect continuation toward $95+ region This divergence typically results in high volatility compression before next directional impulse. Scenario-Based Price Outlook Bullish Continuation Scenario (Probability: Moderate–High) If silver holds above $83: Short-term range: $86 – $90 Extension target: $92 – $96 Macro breakout scenario: $100 test possible Neutral Consolidation Scenario If momentum slows: Range formation between $83 – $89 Sideways accumulation before next breakout phase Pullback Scenario If profit-taking increases: Retest zones: $83 → $80.50 → $79.25 Healthy correction within broader bullish structure Risk Factors and Volatility Considerations Despite strong momentum, silver remains a high-volatility asset. Key risks: Sharp profit-taking after rapid weekly gains Strong US dollar rebound Unexpected hawkish Fed signals Liquidity-driven stop-loss cascades Even in strong bullish cycles, silver frequently experiences 5–8% pullbacks before continuation moves. Final Market Outlook Silver’s weekly surge reflects a synchronized combination of macro liquidity shifts, dollar weakness, safe-haven rotation, and technical breakout confirmation. The transition from consolidation into expansion suggests that the market is entering a new volatility regime where directional moves become larger and faster. As long as silver maintains structural support above $83, the broader trend remains bullish with potential extension toward $90, $95, and potentially the $100 psychological zone in medium-term scenarios. However, volatility remains elevated, meaning corrective phases will continue to appear even within bullish cycles. Silver is currently positioned in a strong momentum-driven environment where both macro and technical forces are aligned, but disciplined risk management remains essential due to its historically sharp price swings.
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MrDecoder

MrDecoder

Hace 4 minutos
With **Nvidia** (NVDA +2.33%) scheduled to report its fiscal 2027 first-quarter results on May 20, prediction markets are already humming. On Polymarket, the implied probability that Nvidia will beat expectations sits around 90%. Clearly, the crowd is leaning bullish. But does that mean smart investors should follow prediction markets blindly into earnings season? What is Wall Street expecting for Nvidia's Q1 earnings? ------------------------------------------------------- Among the Wall Street analysts who cover Nvidia, the consensus estimates heading into the Q1 report call for revenue of $78.8 billion and earnings per share (EPS) of $1.77. Some are more optimistic, however. ![](https://img-cdn.gateio.im/social/moments-552bfbc0bf-0758543d64-8b7abd-e5a980) Image source: Nvidia. **Goldman Sachs** analyst James Schneider is forecasting that Nvidia will beat the consensus revenue estimate by about $2 billion. Meanwhile, his fiscal Q2 revenue forecast of $87.7 billion is slightly above Wall Street's average of $86.6 billion, and his Q2 EPS estimate of $2.07 is roughly 6% higher than the average. Expand ![](https://img-cdn.gateio.im/social/moments-b098dfb19d-1abba57262-8b7abd-e5a980) NASDAQ: NVDA ------------ Nvidia Today's Change (2.33%) $5.14 Current Price $225.92 ### Key Data Points Market Cap $5.5T Day's Range $221.56 - $227.84 52wk Range $129.16 - $227.84 Volume 5.2M Avg Vol 170M Gross Margin 71.07% Dividend Yield 0.02% Should investors trust prediction markets? ------------------------------------------ Prediction markets can be useful as sentiment aggregators, but treating these platforms as a genuine trading barometer for a single company is where investors will run into trouble. These platforms reflect "the wisdom of the crowd" in real time, which sounds valid -- until you consider what most people actually know. In the case of Nvidia's quarterly results, the average bettor on Polymarket doesn't have any more information than the generic public does, and that is already priced into Nvidia stock. The informational edge in predicting whether Nvidia will beat expectations belongs to supply chain analysts, channel checks, and institutional desks with deep industry relationships -- not average outsiders trading on bet tickets. Nvidia's implied beat probability in a prediction market tells you more about macro sentiment, not something about the company's actual bookings or chip shipment velocity. And that sentiment gets reflected in its stock price in a similar way. The smarter approach is to look at what has already been reported. Nvidia's largest data center customers recently told investors exactly how much they plan to spend on artificial intelligence (AI) infrastructure this year. The big four hyperscalers -- **Alphabet** (GOOGL +3.97%) (GOOG +4.00%), **Amazon** (AMZN +1.61%), **Meta Platforms** (META +2.31%), and **Microsoft** (MSFT 0.63%) -- are forecasting combined 2026 capital expenditures of more than $700 billion. Meta, Alphabet, and Microsoft also raised their full-year capex guidance during their respective earnings calls. Memory stocks can also serve as a revealing proxy. **Sandisk**'s (SNDK 0.33%) quarterly revenue surged to $5.9 billion, trouncing analyst estimates of $4.7 billion. Moreover, management's guidance for sales of $7.7 billion to $8.3 billion in its next fiscal quarter and up to $33 in EPS far surpassed what the most optimistic models on Wall Street were calling for. When Nvidia's largest customers are spending on AI infrastructure at record rates, and the memory ecosystem around its GPUs continues to accelerate, the implications for the company's own quarterly performance are hard to dismiss. Use dollar-cost averaging instead of playing roulette ----------------------------------------------------- While I am optimistic Nvidia's fiscal Q1 results will exceed expectations, I'm not suggesting you should load up on the stock before May 20. The hyperscaler capex cycle and the tailwinds from memory and storage merely support Nvidia's long-run demand narrative. These industrywide dynamics do not tell you whether Nvidia beating earnings will move the stock, which is already trading near its all-time high. Investors who periodically add to their Nvidia position using a dollar-cost averaging strategy will reliably benefit from the AI infrastructure build-out while avoiding the risks of making ill-timed large bets. This discipline is worth more than a binary wager on a performance that even the most sophisticated analysts on Wall Street could get wrong.
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